| 1. |
- Varga, Balázs, 1990, et al.
(författare)
-
Robust tracking controller design for active dolly steering
- 2018
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Ingår i: Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering. - : SAGE Publications. - 2041-2991 .- 0954-4070. ; 232:5, s. 695-706
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Forskningsöversikt (refereegranskat)abstract
- In this paper different actuation level steering control methods for an A-double vehicle combination (tractor-semitrailer-dolly-semitrailer) are proposed. The aim of the paper is to show viability of advanced actuation control strategies on a practical vehicular application. Three different types of robust controllers are proposed: a robust Proportional Integral Derivative (PID) controller, an output feedback linear Hinf controller and an induced L2-norm minimizing Linear Parameter Varying (LPV) controller. All controllers are augmented with anti-windup compensators to respect steering angle and steering rate limits. Each model based controller robustly rejects external disturbances and tracks a reference steering angle, generated by motion control system. Frequency- and time domain analysis proves that Hinf and LPV controllers outperform PID controller in terms of reference tracking and disturbance rejection. Comparative simulation scenarios are provided on the basis of Volvo Group Trucks Technology’s high fidelity vehicle simulator.
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| 2. |
- Andersson, Viktor, 1995, et al.
(författare)
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Controlled Decent Training
- 2023
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- In this work, a novel and model-based artificial neural network (ANN) training method is developed supported by optimal control theory. The method augments training labels in order to robustly guarantee training loss convergence and improve training convergence rate. Dynamic label augmentation is proposed within the framework of gradient descent training where the convergence of training loss is controlled. First, we capture the training behavior with the help of empirical Neural Tangent Kernels (NTK) and borrow tools from systems and control theory to analyze both the local and global training dynamics (e.g. stability, reachability). Second, we propose to dynamically alter the gradient descent training mechanism via fictitious labels as control inputs and an optimal state feedback policy. In this way, we enforce locally H2 optimal and convergent training behavior. The novel algorithm, Controlled Descent Training (CDT), guarantees local convergence. CDT unleashes new potentials in the analysis, interpretation, and design of ANN architectures. The applicability of the method is demonstrated on standard regression and classification problems.
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| 3. |
- Andersson, Viktor, 1995, et al.
(författare)
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Controlled Descent Training
- 2024
-
Ingår i: International Journal of Robust and Nonlinear Control. - 1099-1239 .- 1049-8923.
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Tidskriftsartikel (refereegranskat)abstract
- In this work, a novel and model-based artificial neural network (ANN) training method is developed supported by optimal control theory. The method augments training labels in order to robustly guarantee training loss convergence and improve training convergence rate. Dynamic label augmentation is proposed within the framework of gradient descent training where the convergence of training loss is controlled. First, we capture the training behavior with the help of empirical Neural Tangent Kernels (NTK) and borrow tools from systems and control theory to analyze both the local and global training dynamics (e.g. stability, reachability). Second, we propose to dynamically alter the gradient descent training mechanism via fictitious labels as control inputs and an optimal state feedback policy. In this way, we enforce locally H2 optimal and convergent training behavior. The novel algorithm, Controlled Descent Training (CDT), guarantees local convergence. CDT unleashes new potentials in the analysis, interpretation, and design of ANN architectures. The applicability of the method is demonstrated on standard regression and classification problems.
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| 4. |
- Varga, Balázs, 1990, et al.
(författare)
-
Constrained Policy Gradient Method for Safe and Fast Reinforcement Learning: a Neural Tangent Kernel Based Approach
- 2021
-
Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- This paper presents a constrained policy gradient algorithm. We introduce constraints for safe learning with the following steps. First, learning is slowed down (lazy learning) so that the episodic policy change can be computed with the help of the policy gradient theorem and the neural tangent kernel. Then, this enables us the evaluation of the policy at arbitrary states too. In the same spirit, learning can be guided, ensuring safety via augmenting episode batches with states where the desired action probabilities are prescribed. Finally, exogenous discounted sum of future rewards (returns) can be computed at these specific state-action pairs such that the policy network satisfies constraints. Computing the returns is based on solving a system of linear equations (equality constraints) or a constrained quadratic program (inequality constraints). Simulation results suggest that adding constraints (external information) to the learning can improve learning in terms of speed and safety reasonably if constraints are appropriately selected. The efficiency of the constrained learning was demonstrated with a shallow and wide ReLU network in the Cartpole and Lunar Lander OpenAI gym environments. The main novelty of the paper is giving a practical use of the neural tangent kernel in reinforcement learning.
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| 5. |
- Varga, Balázs, 1990, et al.
(författare)
-
Data-driven distance metrics for kriging - Short-term urban traffic state prediction
- 2023
-
Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; 24:6, s. 6268-6279
-
Tidskriftsartikel (refereegranskat)abstract
- Estimating traffic flow states at unmeasured urban locations provides a cost-efficient solution for many ITS applications. In this work, a geostatistical framework, kriging is extended in such a way that it can both estimate and predict traffic volume and speed at various unobserved locations, in real-time. In the paper, different distance metrics for kriging are evaluated. Then, a new, data-driven one is formulated, capturing the similarity of measurement sites. Then, with multidimensional scaling the distances are transformed into a hyperspace, where the kriging algorithm can be used. As a next step, temporal dependency is injected into the estimator via extending the hyperspace with an extra dimension, enabling for short horizon traffic flow prediction. Additionally, a temporal correction is proposed to compensate for minor changes in traffic flow patterns. Numerical results suggest that the spatio-temporal prediction can make more accurate predictions compared to other distance metric-based kriging algorithms. Additionally, compared to deep learning, the results are on par while the algorithm is more resilient against traffic pattern changes.
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| 6. |
- Varga, Balázs, 1990, et al.
(författare)
-
Deep Q-learning: a robust control approach
- 2023
-
Ingår i: International Journal of Robust and Nonlinear Control. - : Wiley. - 1099-1239 .- 1049-8923. ; 33:1, s. 526-544
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Tidskriftsartikel (refereegranskat)abstract
- This work aims at constructing a bridge between robust control theory and reinforcement learning. Although, reinforcement learning has shown admirable results in complex control tasks, the agent’s learning behaviour is opaque. Meanwhile, system theory has several tools for analyzing and controlling dynamical systems. This paper places deep Q-learning is into a control-oriented perspective to study its learning dynamics with well-established techniques from robust control. An uncertain linear time-invariant model is formulated by means of the neural tangent kernel to describe learning. This novel approach allows giving conditions for stability (convergence) of the learning and enables the analysis of the agent’s behaviour in frequency-domain. The control-oriented approach makes it possible to formulate robust controllers that inject dynamical rewards as control input in the loss function to achieve better convergence properties. Three output-feedback controllers are synthesized: gain scheduling H2, dynamical Hinf, and fixed-structure Hinf controllers. Compared to traditional deep Q-learning techniques, which involve several heuristics, setting up the learning agent with a control-oriented tuning methodology is more transparent and has well-established literature. The proposed approach does not use a target network and randomized replay memory. The role of the target network is overtaken by the control input, which also exploits the temporal dependency of samples (opposed to a randomized memory buffer). Numerical simulations in different OpenAI Gym environments suggest that the Hinf controlled learning can converge faster and receive higher scores (depending on the environment) compared to the benchmark Double deep Q-learning.
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| 7. |
- Varga, Balázs, 1990, et al.
(författare)
-
Energy-aware predictive control for electrified bus networks
- 2019
-
Ingår i: Applied Energy. - : Elsevier BV. - 1872-9118 .- 0306-2619. ; 252
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Tidskriftsartikel (refereegranskat)abstract
- For an urban bus network to operate efficiently, conflicting objectives have to be considered: providing sufficient service quality while keeping energy consumption low. The paper focuses on energy efficient operation of bus lines, where bus stops are densely placed, and buses operate frequently with possibility of bunching. The proposed decentralized, bus fleet control solution aims to combine four conflicting goals incorporated into a multi-objective, nonlinear cost function. The multi-objective optimization is solved under a receding horizon model predictive framework. The four conflicting objectives are as follows. One is ensuring periodicity of headways by watching leading and following vehicles i.e. eliminating bus bunching. Equal headways are only a necessary condition for keeping a static, predefifined, periodic timetable. The second objective is timetable tracking, and passenger waiting time minimization. In case of high passenger demand, it is desirable to haste the bus in order to prevent bunching. The final objective is energy efficiency. To this end, an energy consumption model is formulated considering battery electric vehicles with recuperation during braking. Alternative weighting strategies are compared and evaluated through realistic scenarios, in a calibrated microscopic traffic simulation environment. Simulation results confirm of 3-8% network level energy saving compared to bus holding control while maintaining punctuality and periodicity of buses.
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| 8. |
- Varga, Balazs, et al.
(författare)
-
Network-Level Optimal Control for Public Bus Operation
- 2020
-
Ingår i: IFAC-PapersOnLine. - : Elsevier BV. - 2405-8963. ; 53:2, s. 15003-15010
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Konferensbidrag (refereegranskat)abstract
- The paper presents modeling, control and analysis of an urban public transport network. First, a centralized system description is given, built up from the dynamics of individual buses and bus stops. Aiming to minimize three conflicting goals (equidistant headways, timetable adherence, and minimizing passenger waiting times), a reference tracking model predictive controller formulated based on the piecewise-affine system model. The closed-loop system is analyzed with three methods. Numerical simulations on a simple experimental network showed that the temporal evolution of headways and passenger numbers could maintain their periodicity with the help of velocity control. With the help of randomized simulation scenarios, sensitivity of the system is analyzed. Finally, infeasible regions for the bus network control was sought using by formulating an explicit model predictive controller.
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| 9. |
- Varga, Balazs, et al.
(författare)
-
Optimal headway and schedule control of public transport buses
- 2017
-
Ingår i: Proceedings of Swedish transportation research conference Stockholm 17-18 October 2017.
-
Konferensbidrag (refereegranskat)abstract
- This paper presents a model-based multiobjective control strategy to reduce bus bunching and hence improve public transport reliability. Our goal is twofold. First, we define a proper model, consisting of multiple static and dynamic components. Bus-following model captures the longitudinal dynamics taking into account the interaction with the surrounding traffic. Furthermore, bus stop operations are modeled to estimate dwell time. Second, a shrinking horizon model predictive controller (MPC) is proposed for solving bus bunching problems.The model is able to predict short time-space behavior of public transport buses enabling constrained, finite horizon, optimal control solution to ensure homogeneity of service both in time and space. In this line, the goal with the selected rolling horizon control scheme is to choose a proper velocity profile for the public transport bus such that it keeps both timetable schedule and a desired headway from the bus in front of it (leading bus). The control strategy predicts the arrival time at a bus stop using a passenger arrival and dwell time model. In this vein, the receding horizon model predictive controller calculates an optimal velocity profile based on its current position and desired arrival time. Three different weighting strategies are proposed to test (i) timetable only, (ii) headway only or (iii) balanced timetable - headway tracking. The controller is tested in a high fidelity traffic simulator with realistic scenarios. The behavior of the system is analyzed by considering extreme disturbances. Finally, the existence of a Pareto front between these two objectives is also demonstrated.
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| 10. |
- Varga, Balázs, 1990, et al.
(författare)
-
Optimal headway merging for balanced public transport service in urban networks
- 2018
-
Ingår i: IFAC-PapersOnLine. - : Elsevier BV. - 2405-8963. ; 51:9, s. 416-421
-
Konferensbidrag (refereegranskat)abstract
- This paper presents a velocity control/advise algorithm relying on vehicle-to-vehicle communication, to ensure the headway homogeneity of buses on a joint corridor, i.e. when multiple lines merge and travel on the same route. The proposed control method first schedules merging buses prior to entering a common line. Second, based on the position and velocity of the bus ahead of the controlled one, a shrinking horizon model predictive controller (MPC) calculates a proper velocity profile for the merging bus. The model is able to predict short time- space behavior of public transport buses enabling constrained, finite horizon, optimal control solution to reach the merging point with equidistant headways, taking all buses from different lines into account. The controller is tested in a high fidelity traffic simulator with realistic scenarios.
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| 11. |
- Varga, Balázs, 1990, et al.
(författare)
-
Optimally combined headway and timetable reliable public transport system
- 2018
-
Ingår i: Transportation Research, Part C: Emerging Technologies. - : Elsevier BV. - 0968-090X. ; 92, s. 1-26
-
Tidskriftsartikel (refereegranskat)abstract
- This paper presents a model-based multiobjective control strategy to reduce bus bunching and hence improve public transport reliability. Our goal is twofold. First, we define a proper model, consisting of multiple static and dynamic components. Bus-following model captures the longitudinal dynamics taking into account the interaction with the surrounding traffic. Furthermore, bus stop operations are modeled to estimate dwell time. Second, a shrinking horizon model predictive controller (MPC) is proposed for solving bus bunching problems. The model is able to predict short time-space behavior of public transport buses enabling constrained, finite horizon, optimal control solution to ensure homogeneity of service both in time and space. In this line, the goal with the selected rolling horizon control scheme is to choose a proper velocity profile for the public transport bus such that it keeps both timetable schedule and a desired headway from the bus in front of it (leading bus). The control strategy predicts the arrival time at a bus stop using a passenger arrival and dwell time model. In this vein, the receding horizon model predictive controller calculates an optimal velocity profile based on its current position and desired arrival time. Four different weighting strategies are proposed to test (i) timetable only, (ii) headway only, (iii) balanced timetable - headway tracking and (iv) adaptive control with varying weights. The controller is tested in a high fidelity traffic simulator with realistic scenarios. The behavior of the system is analyzed by considering extreme disturbances. Finally, the existence of a Pareto front between these two objectives is also demonstrated.
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| 12. |
- Varga, Balázs, et al.
(författare)
-
Public transport trajectory planning with probabilistic guarantees
- 2020
-
Ingår i: Transportation Research Part B: Methodological. - : Elsevier BV. - 0191-2615. ; 139, s. 81-101
-
Tidskriftsartikel (refereegranskat)abstract
- The paper proposes an eco-cruise control strategy for urban public transport buses. The aim of the velocity control is ensuring timetable adherence, while considering upstream queue lengths at traffic lights in a probabilistic way. The contribution of the paper is twofold. First, the shockwave profile model (SPM) is extended to capture the stochastic nature of traffic queue lengths. The model is adequate to describe frequent traffic state interruptions at signalized intersections. Based on the distribution function of stochastic traffic volume demand, the randomness in queue length, wave fronts, and vehicle numbers are derived. Then, an outlook is provided on its applicability as a full-scale urban traffic network model. Second, a shrinking horizon model predictive controller (MPC) is proposed for ensuring timetable reliability. The intention is to calculate optimal velocity commands based on the current position and desired arrival time of the bus while considering upcoming delays due to red signals and eventual queues. The above proposed stochastic traffic model is incorporated in a rolling horizon optimization via chance-constraining. In the optimization, probabilistic guarantees are formulated to minimize delay due to standstill in queues at signalized intersections. Optimization results are analyzed from two particular aspects, (i) feasibility and (ii) closed-loop performance point of views. The novel stochastic profile model is tested in a high fidelity traffic simulator context. Comparative simulation results show the viability and importance of stochastic bounds in urban trajectory design. The proposed algorithm yields smoother bus trajectories at an urban corridor, suggesting energy savings compared to benchmark control strategies.
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| 13. |
|
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| 14. |
- Auriol, Jean, et al.
(författare)
-
Mean-square exponential stabilization of coupled hyperbolic systems with random parameters
- 2023
-
Ingår i: IFAC-PapersOnLine. - 2405-8963. ; 56:2, s. 8153-8158
-
Konferensbidrag (refereegranskat)abstract
- In this paper, we consider a system of two coupled scalar-valued hyperbolic partial differential equations (PDEs) with random parameters. We formulate a stability condition under which the classical backstepping controller (designed for a nominal system whose parameters are constant) stabilizes the system. More precisely, we guarantee closed-loop mean-square exponential stability under random system parameter perturbations, provided the nominal parameters are sufficiently close to the stochastic ones on average. The proof is based on a Lyapunov analysis, the Lyapunov functional candidate describing the contraction of L2-norm of the system states. An illustrative traffic flow regulation example shows the viability and importance of the proposed result
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| 15. |
- Bae, Sangjun, 1986, et al.
(författare)
-
A Game Approach for Charging Station Placement Based on User Preferences and Crowdedness
- 2022
-
Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; 23:4, s. 3654-3669
-
Tidskriftsartikel (refereegranskat)abstract
- The placement of electric vehicle charging stations (EVCSs), which encourages the rapid development of electric vehicles (EVs), should be considered from not only operational perspective such as minimizing installation costs, but also user perspective so that their strategic and competitive charging behaviors can be reflected. This paper proposes a methodological framework to consider crowdedness and individual preferences of electric vehicle users (EVUs) in the selection of locations for fast-charging stations. The electric vehicle charging station placement problem (EVCSPP) is solved via a decentralized game theoretical decision-making algorithm and k-means clustering algorithm. The proposed algorithm, referred to as k-GRAPE, determines the locations of charging stations to maximize the sum of utilities of EVUs. In particular, we analytically present that 50% of suboptimality of the solution can be at least guaranteed, which is about 17% better than the existing game theoretical based framework. We show a few variants to describe the utility functions that may capture the difference in preferences of EVUs. Finally, we demonstrate the viability of the decision framework via three real-world data-based experiments. The results of the experiments, including a comparison with a baseline method are then discussed.
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| 16. |
|
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| 17. |
- Bae, Sangjun, et al.
(författare)
-
Personalized Dynamic Pricing Policy for Electric Vehicles: Reinforcement learning approach
- 2024
-
Ingår i: Transportation Research, Part C: Emerging Technologies. - 0968-090X. ; 161
-
Tidskriftsartikel (refereegranskat)abstract
- With the increasing number of fast-electric vehicle charging stations (fast-EVCSs) and the popularization of information technology, electricity price competition between fast-EVCSs is highly expected, in which the utilization of public and/or privacy-preserved information will play a crucial role. Self-interest electric vehicle (EV) users, on the other hand, try to select a fast-EVCS for charging in a way to maximize their utilities based on electricity price, estimated waiting time, and their state of charge. While existing studies have largely focused on finding equilibrium prices, this study proposes a personalized dynamic pricing policy (PeDP) for a fast-EVCS to maximize revenue using a reinforcement learning (RL) approach. We first propose a multiple fast-EVCSs competing simulation environment to model the selfish behavior of EV users using a game-based charging station selection model with a monetary utility function. In the environment, we propose a Q-learning-based PeDP to maximize fast-EVCS' revenue. Through numerical simulations based on the environment: (1) we identify the importance of waiting time in the EV charging market by comparing the classic Bertrand competition model with the proposed PeDP for fast-EVCSs (from the system perspective); (2) we evaluate the performance of the proposed PeDP and analyze the effects of the information on the policy (from the service provider perspective) and the robustness of the proposed approach; and (3) it can be seen that privacy-preserved information sharing can be misused by artificial intelligence-based PeDP in a certain situation in the EV charging market (from the customer perspective).
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| 18. |
- Basso, Rafael, 1979, et al.
(författare)
-
Dynamic Stochastic Electric Vehicle Routing with Safe Reinforcement Learning
- 2022
-
Ingår i: Transportation Research Part E: Logistics and Transportation Review. - : Elsevier BV. - 1366-5545. ; 157:157
-
Tidskriftsartikel (refereegranskat)abstract
- Dynamic routing of electric commercial vehicles can be a challenging problem since besides the uncertainty of energy consumption there are also random customer requests. This paper introduces the Dynamic Stochastic Electric Vehicle Routing Problem (DS-EVRP). A Safe Reinforcement Learning method is proposed for solving the problem. The objective is to minimize expected energy consumption in a safe way, which means also minimizing the risk of battery depletion while en route by planning charging whenever necessary. The key idea is to learn offline about the stochastic customer requests and energy consumption using Monte Carlo simulations, to be able to plan the route predictively and safely online. The method is evaluated using simulations based on energy consumption data from a realistic traffic model for the city of Luxembourg and a high-fidelity vehicle model. The results indicate that it is possible to save energy at the same time maintaining reliability by planning the routes and charging in an anticipative way. The proposed method has the potential to improve transport operations with electric commercial vehicles capitalizing on their environmental benefits
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| 19. |
- Basso, Rafael, 1979, et al.
(författare)
-
Electric vehicle routing problem – a nested two level approach
- 2017
-
Ingår i: Proceedings of Swedish transportation research conference Stockholm 17-18 October 2017.
-
Konferensbidrag (refereegranskat)abstract
- Some of the main constraints of electric vehicles are related to their battery, in terms of energy capacity, time to recharge, weight and cost. One of the most important consequences is a limitation in driving range, which especially impacts commercial vehicles. Therefore in order to plan routes for this kind of vehicle, it is necessary to precisely estimate the energy required to drive and plan for charging whenever needed. This paper introduces the Two-stage Electric Vehicle Routing Problem (2sEVRP) that considers detailed information about the paths when estimating energy consumption and planning the routes. First, a method to calculate cost parameters for the road network is outlined including topography, speed, powertrain efficiency and the effect of acceleration and braking at traffic lights and intersections. Second, an integrated two-stage approach is described, which finds the best paths between pairs of nodes and then finds the best routes including battery and time-window constraints. Energy consumption is used as cost function including payload and auxiliary systems. The road cost parameters are aggregated to generate the path cost parameters that are used in the routing problem. In this way all the details of the paths are taken into account when computing energy demand for the routes. Last, numerical experiments were conducted with the road network from Gothenburg-Sweden and high-fidelity vehicle model simulations, focusing on trucks for urban distribution of goods. The results indicate that time and energy estimation are signeficantly more precise than existing methods. Consequently it is possible to generate important savings and be sure that the planned routes are feasible.
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| 20. |
- Basso, Rafael, 1979, et al.
(författare)
-
Electric Vehicle Routing Problem with Machine Learning for Energy Prediction
- 2021
-
Ingår i: Transportation Research Part B: Methodological. - : Elsevier BV. - 0191-2615. ; 145, s. 24-55
-
Tidskriftsartikel (refereegranskat)abstract
- Routing electric commercial vehicles requires taking into account their limited driving range, which is affected by several uncertain factors such as traffic conditions. This paper presents the time-dependent Electric Vehicle Routing Problem with Chance- Constraints (EVRP-CC) and partial recharging. The routing method is divided into two stages, where the first finds the best paths and the second optimizes the routes. A probabilistic Bayesian machine learning approach is proposed for predicting the expected energy consumption and variance for the road links, paths and routes. Hence it is possible to consider the uncertainty in energy demand by planning charging within a confidence interval. The energy estimation is validated with data from electric buses driving a public transport route in Gothenburg-Sweden as well as with realistic simulations for 24 hours traffic in the city of Luxembourg connected to a high fidelity vehicle model. Routing solutions are compared with a deterministic formulation of the problem similar to the ones found in the literature. The results indicate high accuracy for the energy prediction as well as energy savings and more reliability for the routes.
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| 21. |
- Basso, Rafael, 1979, et al.
(författare)
-
Energy consumption estimation integrated into the Electric Vehicle Routing Problem
- 2019
-
Ingår i: Transportation Research Part D: Transport and Environment. - : Elsevier BV. - 1361-9209. ; 69, s. 141-167
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Tidskriftsartikel (refereegranskat)abstract
- When planning routes for fleets of electric commercial vehicles, it is necessary to precisely predict the energy required to drive and plan for charging whenever needed, in order to manage their driving range limitations. Although there are several energy estimation models available in the literature, so far integration with Vehicle Routing Problems has been limited and without demonstrated accuracy. This paper introduces the Two-stage Electric Vehicle Routing Problem (2sEVRP) that incorporates improved energy consumption estimation by considering detailed topography and speed profiles. First, a method to calculate energy cost coefficients for the road network is outlined. Since the driving cycle is unknown, the model generates an approximation based on a linear function of mass, as the latter is only determined while routing. These coefficients embed information about topography, speed, powertrain efficiency and the effect of acceleration and braking at traffic lights and intersections. Secondly, an integrated two-stage approach is described, which finds the best paths between pairs of destinations and then finds the best routes including battery and time-window constraints. Energy consumption is used as objective function including payload and auxiliary systems. The road cost coefficients are aggregated to generate the path cost coefficients that are used in the routing problem. In this way it is possible to get a proper approximation of the complete driving cycle for the routes and accurate energy consumption estimation. Lastly, numerical experiments are shown based on the road network from Gothenburg-Sweden. Energy estimation is compared with real consumption data from an all-electric bus from a public transport route and with high-fidelity vehicle simulations. Routing experiments focus on trucks for urban distribution of goods. The results indicate that time and energy estimations are significantly more precise than existing methods. Consequently the planned routes are expected to be feasible in terms of energy demand and that charging stops are properly included when necessary.
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| 22. |
- Basso, Rafael, 1979, et al.
(författare)
-
Traffic aware electric vehicle routing
- 2016
-
Ingår i: IEEE Conference on Intelligent Transportation Systems, Rio de Janeiro, Brazil,November 1-4. ; , s. Art no 7795588, Pages 416-421
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Konferensbidrag (refereegranskat)abstract
- Since the main constraint of electric vehicles is range due to limited battery capacity, the focus for routing these kind of vehicles should be energy consumption minimization. And since energy consumption depends on several aspects, this article introduces a new model for route optimization of Electric Commercial Vehicles, with a realistic energy consumption model based on factors such as road inclination, weight and speed. The main new feature is to consider average speed for the road network at different times during the day, with the vehicle adapting to traffic flow. Several experiments were performed to evaluate the impact of different elements in energy consumption. As a result a few topics are recommended for future work.
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| 23. |
- Cao, Danni, et al.
(författare)
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A Platoon Regulation Algorithm to Improve the Traffic Performance of Highway Work Zones
- 2021
-
Ingår i: Computer-Aided Civil and Infrastructure Engineering. - : Wiley. - 1093-9687 .- 1467-8667. ; 36:7, s. 941-956
-
Tidskriftsartikel (refereegranskat)abstract
- This paper presents a cooperative traffic control strategy to increase the capacity of non-recurrent bottlenecks such as work zones by making full use of the spatial resources upstream of work zones. The upstream area is divided into two zones: the regulation area and the merging area. The basic logic is that a large gap is more efficient in accommodating merging vehicles than several small and scattered gaps with the same total length. In the regulation area, a non-linear programming model is developed to balance both traffic capacity improvements and safety risks. A two-step solving algorithm is proposed for finding optimal solutions. In the merging area, the sorting algorithm is used to design lane changing trajectories based on the regulated platoons. A case study is conducted, and the results indicate that the proposed model is able to significantly improve work zone capacity with minor disturbances to the traffic.
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| 24. |
- Chugh, Tushar, 1989, et al.
(författare)
-
Robust H-infinity Position Control for Vehicle Steering
- 2021
-
Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- This paper presents a robust position controller for an electric power assisted steering and a steer-by-wire force-feedback system. A typical position controller is required for the driving automation and the vehicle motion control functions. The same controller could also be used to realize the haptic functions for steering feedback. The driver’s physical impedance causes a parametric uncertainty during the steering wheel coupling. As a consequence, a classical (single variable) position controller becomes less robust and suffers a tracking performance loss. Therefore, a multi-variable robust position controller is proposed to mitigate the effect of uncertainty. An investigation is performed by including the sensed torque signal in a classical position controller. Finally, a robust solution is synthesized using the LMI-H-infinity optimization. With this, a desired loop gain shape is achieved: (a) a large loop gain at low frequencies for performance; and (b) a small loop gain at high frequencies for robustness. Frequency response comparison of different controllers on real hardware is presented. Experiments and simulation results clearly illustrate the improvements in reference tracking and robustness with an optimal torque feedback in the proposed H-infinity position controller.
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| 25. |
- Csikos, A, et al.
(författare)
-
Network traffic flow optimization under performance constraints
- 2017
-
Ingår i: Transportation Research, Part C: Emerging Technologies. - : Elsevier BV. - 0968-090X. ; 83, s. 120-133
-
Tidskriftsartikel (refereegranskat)abstract
- In this paper, a model-based perimeter control policy for large-scale urban vehicular networks is proposed. Assuming a homogeneously loaded vehicle network and the existence of a well-posed Network Fundamental Diagram (NFD), we describe a protected network throughout its aggregated dynamics including nonlinear exit flow characteristics. Within this framework of constrained optimal boundary flow gating, two main performance metrics are considered: (a) first, connected to the NFD, the concept of average network travel time and delay as a performance metric is defined; (b) second, at boundaries, we take into account additional external network queue dynamics governed by uncontrolled inflow demands. External queue capacities in terms of finite-link lengths are used as the second performance metric. Hence, the corresponding performance requirement is an upper bound of external queues. While external queues represent vehicles waiting to enter the protected network, internal queue describes the protected network’s aggregated behavior.By controlling the number of vehicles joining the internal queue from the external ones, herewith a network traffic flow maximization solution subject to the internal and external dynamics and their performance constraints is developed. The originally non-convex optimization problem is transformed to a numerically efficiently convex one by relaxing the performance constraints into time-dependent state boundaries. The control solution can be interpreted as a mechanism which transforms the unknown arrival process governing the number of vehicles entering the network to a regulated process, such that prescribed performance requirements on travel time in the network and upper bound on the external queue are satisfied. Comparative numerical simulation studies on a microscopic traffic simulator are carried out to show the benefits of the proposed method.
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| 26. |
- Csikos, Alfred, et al.
(författare)
-
Switching CTM for mode dependent travel delay minimisation
- 2016
-
Ingår i: Symposium on Management of Future motorway and urban Traffic Systems Chania, Greece, June 2 - 3, 2016.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- The Lighthill-Whitham-Richards (LWR) model, provides the most simple, first-order description of continuum traffic flow. The consistent numeric solution of the LWR model is the Godunov-scheme, leading to Cell Transmission model. In the discrete model, state dynamics are represented through Godunov fluxes, the flow values between neighbouring segments. The non-continuous model has been formalized and analyzed as a switching system in a number of works. Although these descriptions of the model have been used for control synthesis, they use simplifying assumptions on the initial or the boundary conditions. The model is formalized as a switching system in for uncontrolled systems, assuming arbitrary initial and boundary conditions.
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| 27. |
- Csikos, Alfred, et al.
(författare)
-
Towards a robust traffic admission control in homogeneous urban vehicular networks under QoS constraints
- 2018
-
Ingår i: 2018 European Control Conference (ECC). - 9781538653036 ; , s. 1307-1313
-
Konferensbidrag (refereegranskat)abstract
- In this paper, we consider the problem of con- trolling the input flow to a homogeneous urban vehicular network such that certain Quality of Service (QoS) constraints are preserved. In such a network, we model the system with two types of queues: external and internal. External queues represent vehicles waiting to enter the urban vehicular network under control, and the internal queue is used to describe the network’s aggregated behavior based on the Network Fundamental Diagram (NFD). While most of the works assume perfect knowledge of the NFD describing the urban vehicular network, in reality we can only approximate it. On these grounds, by taking a model of the NFD with uncertainties, we propose a robust control design approach in order to gate input flow to a protected urban vehicular network such that travel time Quality of Service (QoS) constraints are preserved within the network. The proposed controller is compared via simulations with controllers assuming perfect knowledge of the NFD and it is shown that it can provide a larger stability region.
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| 28. |
- Csikos, A, et al.
(författare)
-
Traffic flow optimization with QoS constrained network admission control
- 2017
-
Ingår i: IFAC-PapersOnLine. - : Elsevier BV. - 2405-8963. ; 50:1, s. 5275-5280
-
Konferensbidrag (refereegranskat)abstract
- The paper proposes a control design method in order to gate input flow to a protected urban vehicular network such that travel time Quality of Service (QoS) constraints are preserved within the network. In view of the network to be protected (also called the region), two types of queues are distinguished: external and internal. While external queues represent vehicles waiting to enter the protected network, an internal queue can be used to describe the network's aggregated behaviour. By controlling the number of vehicles entering the internal queue, the travel time within the network subject to the vehicular conservation law and the Network Fundamental Diagram (NFD) can be subsequently controlled. The admission controller can thus be interpreted as a mechanism which transforms the unknown arrival process governing the number of vehicles entering the network to a regulated process, such that prescribed QoS requirements on travel time in the network and upper bound on the external queue are satisfied. The admission control problem is formulated as a constrained convex optimization problem and a Model Predictive Control (MPC) problem. A case study demonstrates the benefits of the admission control mechanisms proposed.
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| 29. |
- Csikos, Alfred, et al.
(författare)
-
Variable speed limit design based on mode dependent Cell Transmission Model
- 2017
-
Ingår i: Transportation Research, Part C: Emerging Technologies. - : Elsevier BV. - 0968-090X. ; 85, s. 429-450
-
Tidskriftsartikel (refereegranskat)abstract
- In this paper a mode dependent variable speed limit (VSL) control strategy is developed for motorway networks. The suggested rolling horizon and coordinated algorithm uses switching mode Cell Transmission Model (CTM) and purports to maximize network throughput. In this line, first, a VSL signal scheduled piecewise affine switching mode CTM is derived based on the polyhedral description of Godunov fluxes. Second, a two-stage, coordinated, rolling horizon VSL sequence generation procedure is proposed. The set of possible VSL signs is selected by applying input constraints in order to eliminate spatial and temporal VSL oscillations. Then, the set of modes is further reduced according to the stable and adjacent reachable modes of the switching mode CTM. Over the remaining set of input signals, network capacity is maximized with the help of solving a mixed integer optimization problem under the form of reference density tracking objective. The method is implemented in simulation environment to demonstrate its computational efficiency and viability to attenuate shockwaves.
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| 30. |
- Dabiri, Azita, 1984, et al.
(författare)
-
Coordinted risk aware ramp metering
- 2016
-
Ingår i: Symposium on Management of Future motorway and urban Traffic Systems Chania, Greece, June 2 - 3, 2016.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- As one of the indisputable causes of congestions in motorways, traffic incidents are regarded as an importantfactor in reducing throughput of motorway networks. Congestions created by non-recurrent traffic conditionsmight have serious long-lasting effects and block upstream off-ramps and on-ramps. Hence, one of the mostimportant challenges for traffic engineers and scientists is to create Intelligent Transportation Systems (ITS)solutions resilient to off-nominal traffic condition. In this direction, analysing the traffic behaviour in occurrence of incident has been targeted in numerous studies. In one of the recent works, it has been shown how to connect incident traffic flow models to driver behavior with the help of novel incident parameterisation for macroscopic flow models. Having such parameterisation in macroscopic model is especially beneficial when traffic management and control is targeted.
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| 31. |
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| 32. |
- Dabiri, Azita, 1984, et al.
(författare)
-
Distributed dynamic output feedback control for discrete-time linear parameter varying systems
- 2016
-
Ingår i: Proceedings of IEEE Conference on Decision and Control, Las Vegas, USA, December 12-14, 2016. - 0743-1546. - 9781509018376 ; , s. Art no 7799203, Pages 6080-6085
-
Konferensbidrag (refereegranskat)abstract
- Proposed in this note, is a method for scheduleddistributed dynamic output feedback controller design. The underlying large-scale system is assumed to be the interconnection of Linear Parameter Varying (LPV) discrete time sub-systems. Following the concept of Integral Quadratic Constraints, robust LPV controller is developed aiming at L2 norm minimisation. The interconnection of the controller has been selected to be identical to the spacial distribution of the sub-systems to secure the level of sparsity in communication topology. By using agentwise full block multipliers in the design phase, distributed output feedback controller design framework is obtained by thesequential use of elimination and dualization lemmas. In order to show the benefits of the suggested methodology, numerical simulation tests are carried out to control the traffic flow in a motorway segment by means of on-ramp input flow gating.
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| 33. |
- Dabiri, Azita, 1984, et al.
(författare)
-
Distributed LPV state-feedback control under control input saturation
- 2017
-
Ingår i: IEEE Transactions on Automatic Control. - 0018-9286 .- 1558-2523. ; 62:5, s. 2450-2456
-
Tidskriftsartikel (refereegranskat)abstract
- Developed in this note is a scheduled state-feedback controller synthesis method for discrete-time Linear Parameter Varying (LPV) systems subjected to control input saturation constraints. The static state-feedback gain is scheduled with an exact replica of the parameter matrix. The saturation effect is modeled by introducing time-varying parameters as functions of the control inputs, which are also used to schedule the controller. The synthesis method is then specialized to distributed state-feedback by imposing a particular structure on the feedback gain matrix. An explicit formula is also derived for the computation of the distributed control input from a nonlinear equation. The viability of the proposed method is tested in a simulation environment, for a ramp meter traffic flow control problem.
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| 34. |
- Dabiri, Azita, 1984, et al.
(författare)
-
Distributed LPV State-Feedback Control with Application to Motorway Ramp Metering
- 2015
-
Ingår i: In proceedings of European Control Conference, ECC’15, July 15-17, Linz, Austria. - 9783952426937 ; , s. 1480-1485
-
Konferensbidrag (refereegranskat)abstract
- In this paper, we develop a distributed state-feedbackcontroller synthesis algorithm for a discrete-time LPVsystem that is composed of the interconnection of severalsubsystems each scheduled by its own parameters. A set ofLMI conditions are derived for robust L2-gain performanceof such a system in the framework of multiplier-based LPVsynthesis. The results have been oriented to be applied intraffic flow control in motorways by ramp metering. First,with the use of a proper transformation, the nonlineartraffic flow model has been represented as theinterconnection of LPV subsystems. Then the developedsynthesis results have been used to design a gain-scheduleddistributed state-feedback controller that keeps thedensity of all segments around a desired value by the useof ramp metering.
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| 35. |
- Dabiri, Azita, 1984, et al.
(författare)
-
Distributed ramp metering - a constrained discharge flow maximisation approach
- 2017
-
Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; 18:9, s. 2525-2538
-
Tidskriftsartikel (refereegranskat)abstract
- Considered in this note is a novel model-based, coordinated ramp metering strategy. It aims at maximising the discharge flow in motorway networks by minimising the divergence of the traffic density from its critical value caused by unknown demand flow. The suggested synthesis algorithm casts the traffic control objective into the form of an induced $\mathcal{L}_2$ norm minimisation problem. Hence, we purport rejecting the effect of disturbance on the overall network performance output while the ramp input flow is subjected to constraints. With such a problem formulation, it is not required to know the disturbance input in order to find the proper control input. Without any central decision unit (traffic control centre), ramp meters coordinate by sharing their local variables with solely their neighbour units (upstream and downstream) to achieve the global performance goal. Under some network symmetry conditions, a compositionally inexpensive distributed flow control method is suggested to address scalability issues. The method is implemented in simulation environment and compared to other control algorithms in two comprehensive case studies.
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| 36. |
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| 37. |
- Dabiri, Azita, 1984, et al.
(författare)
-
Freeway traffic incident reconstruction – A bi-parameter approach
- 2015
-
Ingår i: Transportation Research, Part C: Emerging Technologies. - : Elsevier BV. - 0968-090X. ; 58, s. 585-597
-
Tidskriftsartikel (refereegranskat)abstract
- The paper suggests a novel alternative to generalized traffic incident descriptions within the macroscopic traffic model framework. The contribution of the paper is twofold. First, by extending already existing second order macroscopic conservation laws to characterize off-nominal traffic conditions, we define two main incident parameters such as direct and indirect ones. Physical interpretations of this incident parametrization is provided. These incident indicators are relative in view of the nominal traffic flow model parameters and carries physically meaningful macroscopic content. Second, the paper proposes to use a constrained and nonlinear, joint traffic state- and incident parameter reconstruction method and validates the suggested modeling idea via real traffic measurements fitting. Evaluation of the numerical results demonstrate the effectiveness of the methodology.
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| 38. |
- Dabiri, Azita, 1984, et al.
(författare)
-
Incident description in METANET model
- 2013
-
Ingår i: 2nd National Conference in Transportation, October 2013, Gothenburg.
-
Konferensbidrag (övrigt vetenskapligt/konstnärligt)
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| 39. |
- Dabiri, Azita, et al.
(författare)
-
Incident indicators for freeway traffic flow models
- 2022
-
Ingår i: Communications in Transportation Research. - : Elsevier BV. - 2772-4247. ; 2:December
-
Tidskriftsartikel (refereegranskat)abstract
- Developed in this paper is a traffic flow model parametrised to describe abnormal traffic behaviour. In large traffic networks, the immediate detection and categorisation of traffic incidents/accidents is of capital importance to avoid breakdowns, further accidents. First, this claims for traffic flow models capable to capture abnormal traffic condition like accidents. Second, by means of proper real-time estimation technique, observing accident related parameters, one may even categorize the severity of accidents. Hence, in this paper, we suggest to modify the nominal Aw-Rascle (AR) traffic model by a proper incident related parametrisation. The proposed Incident Traffic Flow model (ITF) is defined by introducing the incident parameters modifying the anticipation and the dynamic speed relaxation terms in the speed equation of the AR model. These modifications is proven to have physical meaning. Furthermore, the characteristic properties of the ITF model is discussed in the paper. A multi stage numerical scheme is suggested to discretise in space and time the resulting non-homogeneous system of PDEs. The resulting systems of ODE is then combined with receding horizon estimation methods to reconstruct the incident parameters. Finally, the viability of the suggested incident parametrisation is validated in a simulation environment.
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| 40. |
- Dabiri, Azita, 1984, et al.
(författare)
-
Incident parameter estimation
- 2013
-
Ingår i: Proc. of European Control Conference ECC’13, July 17-19, Zurich, Switzerland.. - : IEEE. - 9783033039629 ; , s. 3518-3523
-
Konferensbidrag (refereegranskat)abstract
- The paper proposes a sampled data based estimation methodology to reconstruct local incident parameter of the macroscopic Incident Traffic Flow (ITF) models. The key idea in ITF models is to dynamically relax the traffic mean speed to the traffic equilibrium one based of an time and space varying incident term. First, the analysis of incident corrupted traffic flow models, described as an in-homogeneous nonlinear Partial Differential Equation (PDE), is presented in continuous time. Second, space and time discretization techniques are applied to derive traffic management oriented ITF models. Online parameter estimation is suggested to capture the severity of incident throughout the proposed parameter, i.e. to estimate the incident parameter. Numerical example is carried out to show the viability of macroscopic incident parameter estimation technique using data obtained from a high-fidelity microscopic simulation.
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| 41. |
- Dabiri, Azita, 1984, et al.
(författare)
-
Incident parameter scheduled freeway traffic control - A ramp meter approach
- 2014
-
Ingår i: IFAC Proceedings Volumes (IFAC-PapersOnline). - : Elsevier BV. - 2405-8963 .- 1474-6670. - 9783902823625 ; 19, s. 11338-11343
-
Konferensbidrag (refereegranskat)abstract
- A novel model based local ramp metering method is presented in the paper by means of incident scheduled freeway traffic control solution. First, second order macroscopic freeway model is used with appropriate incident parametrization to describe eventual and unattended traffic variation caused by off-nominal traffic conditions (e.g. accidents). These traffic anomalies are captured by adequate model parameters, i.e. incident parameters that can be on-line estimated. The paper is motivated by incident scheduled ramp-meter solution to encounter real-time incident parameter information. The main idea is to use local freeway control solution triggered by available incident parameter values. The proposed approach is local in the sense of considering only non-coordinated ramp meter solution, first. Furthermore, we apply locally optimal (linearized) control solution to satisfy throughput maximization objective. The formal controller synthesis involves parameters to correct, compensate the effect of incidents. The proposed method is evaluated and compared to other existing approach by using simulation environment.
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| 42. |
- Dabiri, Azita, 1984, et al.
(författare)
-
Traffic incident aware coordination of ramp meters
- 2017
-
Ingår i: Proceedings of Swedish transportation research conference Stockholm 17-18 October 2017.
-
Konferensbidrag (refereegranskat)abstract
- As one of the indisputable causes of congestions in motorways, traffic incidents are regarded as an important factor in reducing throughput of motorway networks. A novel model based local ramp metering method is presented in the paper by means of incident scheduled freeway traffic control solution. Traffic anomalies are captured by adequate model parameters, i.e. incident parameters that can be on-line estimated. The paper is motivated by incident scheduled ramp-meter solution to encounter real-time incident parameter information. The main idea is to use local freeway control solution triggered by available incident parameter values. The proposed approach is local in the sense of considering only non-coordinated ramp meter solution, first. Furthermore, we apply locally optimal (linearized) control solution to satisfy throughput maximization objective. The formal controller synthesis involves parameters to correct, compensate the effect of incidents.
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| 43. |
- Dong, J, et al.
(författare)
-
Fault detection for LPV systems using model parameters that can be estimated via linear least squares
- 2014
-
Ingår i: International Journal of Robust and Nonlinear Control. - : Wiley. - 1099-1239 .- 1049-8923. ; 24:14, s. 1989-1999
-
Tidskriftsartikel (refereegranskat)abstract
- This paper presents a fault detection approach for discrete-time affine linear parameter varying systems with additive faults. A finite horizon input-output linear parameter varying model is used to obtain a linear in the model parameter regression residual form. The bias in the residual term vanishes because of quadratic stability of an underlying observer. The new methodology avoids projecting the residual onto a parity space, which in real time requires at least quadratic computational complexity. When neglecting the bias, the fault detection is carried out by an χ2 hypothesis test. Finally, the algorithm uses model parameters that can be identified prior to the on-line fault detection with linear least squares. A realtime experiment is carried out to demonstrate the viability of the proposed method.
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| 44. |
- Keskin, Furkan, 1988, et al.
(författare)
-
Altruistic Control of Connected Automated Vehicles in Mixed-Autonomy Multi-Lane Highway Traffic
- 2020
-
Ingår i: IFAC-PapersOnLine. - : Elsevier BV. - 2405-8963. ; 53:2, s. 14966-14971
-
Konferensbidrag (refereegranskat)abstract
- We consider the problem of altruistic control of connected automated vehicles (CAVs) on mixed-autonomy multi-lane highways to mitigate moving traffic jams resulting from car-following dynamics of human-driven vehicles (HDVs). In most of the existing studies on CAVs in multi-lane settings, vehicle controller design philosophy is based on a selfish driving strategy that exclusively addresses the ego vehicle objectives. To improve overall traffic smoothness, we propose an altruistic control strategy for CAVs that aims to maximize the driving comfort and traffic efficiency of both the ego vehicle and surrounding HDVs. We formulate the problem of altruistic control under a model predictive control (MPC) framework to optimize acceleration and lane change sequences of CAVs. In order to efficiently solve the resulting non-convex mixed-integer nonlinear programming (MINLP) problem, we decompose it into three non-convex subproblems, each of which can be transformed into a convex quadratic program via penalty based reformulation of the optimal velocity with relative velocity (OVRV) car-following model. Simulation results demonstrate significant improvements in traffic flow via altruistic CAV actions over selfish strategies on both single- and multi-lane roads.
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| 45. |
- Keskin, Furkan, 1988, et al.
(författare)
-
Freeway Traffic Jam Mitigation via Connected Automated Vehicles
- 2019
-
Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- We consider the problem of altruistic control of connected automated vehicles (CAVs) on multi-lane highways to mitigate phantom traffic jams resulting from car-following dynamics of human-driven vehicles (HDVs). In most of the existing studies on CAVs in multi-lane settings, vehicle controller design philosophy is based on a selfish driving strategy that exclusively addresses the ego vehicle objectives. To improve overall traffic smoothness, we propose an altruistic control strategy for CAVs that aims to maximize the driving comfort and traffic efficiency of both the ego vehicle and surrounding HDVs. We formulate the problem of altruistic control under a model predictive control (MPC) framework to optimize acceleration and lane change sequences of CAVs. Simulation results demonstrate significant improvements in traffic flow via altruistic CAV actions over selfish strategies.
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| 46. |
- Kovacs, L., et al.
(författare)
-
Robust servo control of a novel type 1 diabetic model
- 2011
-
Ingår i: Optimal Control Applications and Methods. - : Wiley. - 1099-1514 .- 0143-2087. ; 32:2, s. 215-238
-
Tidskriftsartikel (refereegranskat)abstract
- Robust servo control of a model-based biomedical application is presented in the article. The glucose-insulin control of type 1 diabetic patients is considered to be solved using the results of post-modern robust control principles. The paper uses a recently published glucose-insulin model and presents the transformation of the model to describe the dynamics of type 1 diabetes mellitus. The nonlinear plant is then linearized at a given steady state point. In order to characterize the uncertainty around the nominal model in frequency domain, a parametric nonlinear model sensitivity analysis is performed using gridding method. The aim of the paper is to underline the viability of the robust servo, linear mu-control algorithm tested in highly nonlinear closed-loop simulation environment. Using two degree-of-freedom robust controller, the structured singular value of the closed-loop is designed to fulfill the robust performance requirements and assure glucose level control. Glucose level tracking is ensured under simulated and realistic exogenous meal disturbances.
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| 47. |
- Kovacs, Péter, 1987, et al.
(författare)
-
On the convergence of driver centric zone pricing for traffic networks
- 2018
-
Ingår i: RM18: Swedish Control Confrence 2018 (Reglermöte 2018). - : EasyChair.
-
Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Congestion fees with dynamical zone pricing provide an easy-to-implement solution to urban traffic control agencies for improved efficiency of the traffic network. In order to design a pricing strategy it is necessary to understand how it affects the route choices of drivers in the system. This work explores this question by providing an idealized dynamical model for re-routing as traffic flows change to cheaper routes. Results show a convergence to a Wardrop-equilibrium, which is also proven formally and demonstrated via simulation.
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| 48. |
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| 49. |
- Kulcsár, Balázs Adam, 1975, et al.
(författare)
-
Impulse response parameter based internal model control for discrete-time LPV systems
- 2014
-
Ingår i: 13th European Control Conference, ECC 2014, Strasbourg Convention and Exhibition Center, Place de Bordeaux, Strasbourg, France, 24-27 June 2014. - 9783952426913 ; , s. 424-429
-
Konferensbidrag (refereegranskat)abstract
- This paper presents a novel impulse response parameter based solution for internal model control (IMC) within the linear parameter varying framework. First, based on a discrete-time state-space representation, a finite horizon vector autoregressive model with exogenous disturbance (VARX) is obtained to describe the I/O relationship of an affine LPV plant. In this paper, inversion of the VARX model w.r.t. control input directly leads to a IMC law where analytic solution can be derived for unconstrained and optimal reference tracking error minimization. When the bias term in the finite horizon I/O predictor is neglected, asymptotic properties of closed-loop IMC is analyzed. The VARX parameters of the I/O LPV model can be factorized into a scheduling dependent data matrix and a sequence of constant impulse response parameters (IRPs). The latter part can consistently be identified from data as a single least-squares problem. Without the need to build or identify an LPV state-space model, this methodology is able to address IMC tracking error minimization by using IRPs. The viability of the proposed method is numerically tested in simulation environment.
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| 50. |
- Kulcsár, Balázs Adam, 1975, et al.
(författare)
-
Integrated robust control/fault diagnosis design for LPV systems under input constraints
- 2012
-
Ingår i: European Workshop on Advanced Control and Diagnosis ACD’12.
-
Konferensbidrag (refereegranskat)abstract
- This paper proposes a joint controller and fault estimator design for continuous-time Linear Parameter Varying systems. In the presented problem statement, the structure of the modeling uncertainty couples the controller and fault estimator synthesis. Furthermore, as in most of the cases, control input actions are subjected to hard physical constraints, this paper aims at developing an integrated methodology where these bounds can explicitly be taken into considerations.
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