| 1. |
- Alanwar, Amr, et al.
(författare)
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Privacy-preserving set-based estimation using partially homomorphic encryption
- 2023
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Ingår i: European Journal of Control. - : Elsevier BV. - 0947-3580 .- 1435-5671. ; 71, s. 100786-
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Tidskriftsartikel (refereegranskat)abstract
- The set-based estimation has gained a lot of attention due to its ability to guarantee state enclosures for safety-critical systems. However, collecting measurements from distributed sensors often requires out-sourcing the set-based operations to an aggregator node, raising many privacy concerns. To address this problem, we present set-based estimation protocols using partially homomorphic encryption that pre-serve the privacy of the measurements and sets bounding the estimates. We consider a linear discrete-time dynamical system with bounded modeling and measurement uncertainties. Sets are represented by zonotopes and constrained zonotopes as they can compactly represent high-dimensional sets and are closed under linear maps and Minkowski addition. By selectively encrypting parameters of the set repre-sentations, we establish the notion of encrypted sets and intersect sets in the encrypted domain, which enables guaranteed state estimation while ensuring privacy. In particular, we show that our protocols achieve computational privacy using the cryptographic notion of computational indistinguishability. We demonstrate the efficiency of our approach by localizing a real mobile quadcopter using ultra-wideband wireless devices.
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| 2. |
- Alanwar, Amr, et al.
(författare)
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Robust data-driven predictive control using reachability analysis
- 2022
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Ingår i: European Journal of Control. - : Elsevier BV. - 0947-3580 .- 1435-5671. ; 68
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Tidskriftsartikel (refereegranskat)abstract
- We present a robust data-driven control scheme for an unknown linear system model with bounded process and measurement noise. Instead of depending on a system model in traditional predictive con-trol, a controller utilizing data-driven reachable regions is proposed. The data-driven reachable regions are based on a matrix zonotope recursion and are computed based on only noisy input-output data of a trajectory of the system. We assume that measurement and process noise are contained in bounded sets. While we assume knowledge of these bounds, no knowledge about the statistical properties of the noise is assumed. In the noise-free case, we prove that the presented purely data-driven control scheme results in an equivalent closed-loop behavior to a nominal model predictive control scheme. In the case of measurement and process noise, our proposed scheme guarantees robust constraint satisfaction, which is essential in safety-critical applications. Numerical experiments show the effectiveness of the proposed data-driven controller in comparison to model-based control schemes.
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| 3. |
- Bernardo, Carmela, 1993-, et al.
(författare)
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Finite-time convergence of opinion dynamics in homogeneous asymmetric bounded confidence models
- 2022
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Ingår i: European Journal of Control. - : ELSEVIER. - 0947-3580 .- 1435-5671. ; 68
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Tidskriftsartikel (refereegranskat)abstract
- Bounded confidence opinion dynamics are dynamic networks in which agents are connected if their opinions are similar, and each agent updates her opinion as the average of the neighbors’ opinions. In homogeneous asymmetric Heglselmann–Krause (HK) models, all agents have the same confidence thresholds which could be different for the selection of upper and lower neighbors. This paper provides conditions for the convergence of the opinions to consensus and to clustering for this class of HK models. A new tighter bound on the time interval for reaching the steady state is also provided.
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| 4. |
- Chaffey, Thomas, et al.
(författare)
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Circuit analysis using monotone+skew splitting
- 2023
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Ingår i: European Journal of Control. - 0947-3580.
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Tidskriftsartikel (refereegranskat)abstract
- It is shown that the behavior of an m-port circuit of maximal monotone elements can be expressed as a zero of the sum of a maximal monotone operator containing the circuit elements, and a structured skew-symmetric linear operator representing the interconnection structure, together with a linear output transformation. The Condat–Vũ algorithm solves inclusion problems of this form, and may be used to solve for the periodic steady-state behavior, given a periodic excitation at each port, using an iteration in the space of periodic trajectories.
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| 5. |
- Charitidou, Maria, et al.
(författare)
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An MILP approach for persistent coverage tasks with multiple robots and performance guarantees
- 2022
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Ingår i: European Journal of Control. - : Elsevier. - 0947-3580 .- 1435-5671. ; 64
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Tidskriftsartikel (refereegranskat)abstract
- Multiple robots are increasingly being considered in a variety of tasks requiring continuous surveillance of a dynamic area, examples of which are environmental monitoring, and search and rescue missions. Motivated by these applications, in this paper we consider the multi-robot persistent coverage control problem over a grid environment. The goal is to ensure a desired lower bound on the coverage level of each cell in the grid, that is decreasing at a given rate for unoccupied cells. We consider a finite set of candidate poses for the agents and introduce a directed graph with nodes representing their admissible poses. We formulate a persistent coverage control problem as a MILP problem that aims to maximize the coverage level of the cells over a finite horizon. To solve the problem, we design a receding horizon scheme (RHS) and prove its recursive feasibility property by introducing a set of time-varying terminal constraints to the problem. These terminal constraints ensure that the agents are always able to terminate their plans in pre-determined closed trajectories. A two-step method is proposed for the construction of the closed trajectories, guaranteeing the satisfaction of the coverage level lower bound constraint, when the resulting closed trajectories are followed repeatedly. Due to the special structure of the problem, agents are able to visit every cell in the grid repeatedly within a worst-case visitation period. Finally, we provide a computational time analysis of the problem for different simulated scenarios and demonstrate the performance of the RHS problem by an illustrative example.
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| 6. |
- Čičić, Mladen, 1991-, et al.
(författare)
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Platoon-actuated variable area mainstream traffic control for bottleneck decongestion
- 2022
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Ingår i: European Journal of Control. - : Elsevier BV. - 0947-3580 .- 1435-5671. ; 68
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Tidskriftsartikel (refereegranskat)abstract
- In this paper a platoon-actuated mainstream traffic control is proposed to decongest bottlenecks due to recurrent and nonrecurrent events. Indeed, differently from traditional mainstream control strategies, i.e., control strategies applied with fixed actuators, platoon-actuated control can be applied at any location on the freeway. In this work, the control actions to be communicated to the platoons, i.e., speed and configuration, are defined by means of a predictive control law based on traffic and platoon state detected in an area identified immediately upstream of the bottleneck. The main peculiarity of this scheme is that the size of the controlled area is dynamically adjusted based on the predicted congestion at the bottleneck. This approach keeps the control law computation burden low, while not sacrificing much control performance. Specifically, the number of platoons to be controlled and the time at which the platoons begin to be controlled depend on the size of the controlled area. Simulation results reported in the paper show the effectiveness of the proposed scheme, eliminating from 60% to 80% of the delay incurred from congestion compared with the uncontrolled case, depending on the level of traffic.
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| 7. |
- Dhar, Abhishek, et al.
(författare)
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Initial Excitation based Discrete-time Multi-Model Adaptive Online Identification
- 2022
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Ingår i: European Journal of Control. - Amsterdam, Netherlands : Elsevier. - 0947-3580 .- 1435-5671. ; 68
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Tidskriftsartikel (refereegranskat)abstract
- This paper proposes a novel multi-model adaptive identification (MMAI) algorithm for discrete-time linear time invariant (LTI) uncertain systems with tunable performance. The uncertain plant parameter vector is assumed to belong to a known convex hull of a finite number of vertices; these vertices are considered as initial choice of vertices of an adaptive model parameter set. The estimated parameter, corresponding to the uncertain plant parameter, is computed at every instant as a convex combination of the model set vertices. To update the vertices of the adaptive model parameter set, a switched adaptive update law is proposed, along with a novel discrete-time initial excitation (IE) condition, which is imposed on the regressor signal. The proposed discrete-time IE condition is online verifiable and is milder than persistence of excitation (PE) condition, required for parameter convergence in classical adaptive estimation routines. The switched adaptive law guarantees exponential convergence of the vertices of the model set as well as the estimated parameter, to the true plant parameter, provided the regressor signal satisfies the IE condition. The properties of the designed MMAI strategy are validated through suitable simulation examples.
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| 8. |
- Farjadnia, Mahsa, et al.
(författare)
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Robust data-driven predictive control of unknown nonlinear systems using reachability analysis
- 2023
-
Ingår i: European Journal of Control. - : Elsevier BV. - 0947-3580.
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Tidskriftsartikel (refereegranskat)abstract
- This work proposes a robust data-driven predictive control approach for unknown nonlinear systems in the presence of bounded process and measurement noise. Data-driven reachable sets are employed for the controller design instead of using an explicit nonlinear system model. Although the process and measurement noise are bounded, the statistical properties of the noise are not required to be known. By using the past noisy input-output data in the learning phase, we propose a novel method to over-approximate exact reachable sets of an unknown nonlinear system. Then, we propose a data-driven predictive control approach to compute safe and robust control policies from noisy online data. The constraints are guaranteed in the control phase with robust safety margins by effectively using the predicted output reachable set obtained in the learning phase. Finally, a numerical example validates the efficacy of the proposed approach and demonstrates comparable performance with a model-based predictive control approach.
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| 9. |
- García-Mañas, Francisco, et al.
(författare)
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A practical solution for multivariable control of temperature and humidity in greenhouses
- 2024
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Ingår i: European Journal of Control. - 0947-3580. ; 77
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents a simple and effective control solution to regulate temperature and humidity inside a greenhouse, which are the main climatic variables affecting crop growth and health. A multivariable control strategy with inverted decoupling is proposed in two schemes. The nighttime control scheme uses heating and dehumidification, and the daytime control scheme uses natural ventilation, dehumidification, and humidification. A system identification methodology is used to obtain low-order linear models from data measured in a greenhouse. This simplifies the design of proportional–integral (PI) controllers and allows the use of well-known control techniques. For instance, anti-windup is used to deal with the saturation of the actuators and for a bumpless transfer mechanism to switch between the nighttime and the daytime control schemes. Setpoint weighting is used for the humidity controllers to attenuate undesired effects on the temperature control loop when the humidity setpoint is changed. Furthermore, split range control is used for the first time to control humidity by combining a heat-pump dehumidifier and a fogging system. The control solution presented in this work allows the integral absolute error to be reduced, on average, by 88.5% for the interactions affecting the temperature control loop, and by 85.6% for the humidity control loop, compared to decentralized PI control. The control schemes have been tested in simulation with real disturbance data from a Mediterranean greenhouse and in preliminary form in a real facility to conclude that the proposed multivariable control strategy could be effective in decoupling the temperature and the humidity control loops.
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| 10. |
- Garin, Federica, et al.
(författare)
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Strong structural input and state observability of linear time-invariant systems : Graphical conditions and algorithms
- 2021
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Ingår i: European Journal of Control. - : ELSEVIER. - 0947-3580 .- 1435-5671. ; 58, s. 27-42
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Tidskriftsartikel (refereegranskat)abstract
- The paper studies input and state observability (ISO) of discrete-time linear time-invariant network systems whose dynamics are affected by unknown inputs. More precisely, we aim at reconstructing the initial state and the sequence of unknown inputs from the system outputs, and we will use the term ISO when the input reconstruction is possible with delay one, namely the inputs up to time k - 1 and the states up to time k can be obtained from the outputs up to time k, while the term unconstrained ISO will refer to the case where there is some arbitrary delay in the input reconstruction. We focus on the problem of s-structural ISO (resp. s-structural unconstrained ISO) wherein the objective is to find conditions such that for all system matrices that carry the same network structure, the resulting system is ISO (resp. unconstrained ISO). We provide first a graphical characterization for s-structural unconstrained ISO, and subsequently, sufficient conditions and necessary conditions for s-structural ISO. For the latter, under the assumption of zero feedthrough, these conditions coincide and characterise ISO. The conditions presented are in terms of existence of suitable uniquely restricted matchings in bipartite graphs associated with the structured system. In order to test these conditions, we present polynomial-time algorithms. Finally, we discuss an equivalent reformulation of the main conditions in terms of coloring algorithms as in the literature of zero forcing sets.
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| 11. |
- Kyuroson, Alexander, et al.
(författare)
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Towards fully autonomous orbit management for low-earth orbit satellites based on neuro-evolutionary algorithms and deep reinforcement learning
- 2024
-
Ingår i: European Journal of Control. - : Elsevier. - 0947-3580 .- 1435-5671.
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Tidskriftsartikel (refereegranskat)abstract
- The recent advances in space technology are focusing on fully autonomous, real-time, long-term orbit management and mission planning for large-scale satellite constellations in Low-Earth Orbit (LEO). Thus, a pioneering approach for autonomous orbital station-keeping has been introduced using a model-free Deep Policy Gradient-based Reinforcement Learning (DPGRL) strategy explicitly tailored for LEO. Addressing the critical need for more efficient and self-regulating orbit management in LEO satellite constellations, this work explores the potential synergy between Deep Reinforcement Learning (DRL) and Neuro-Evolution of Augmenting Topology (NEAT) to optimize station-keeping strategies with the primary goal to empower satellite to autonomously maintain their orbit in the presence of external perturbations within an allowable tolerance margin, thereby significantly reducing operational costs while maintaining precise and consistent station-keeping throughout their life cycle. The study specifically tailors DPGRL algorithms for LEO satellites, considering low-thrust constraints for maneuvers and integrating dense reward schemes and domain-based reward shaping techniques. By showcasing the adaptability and scalability of the combined NEAT and DRL framework in diverse operational scenarios, this approach holds immense promise for revolutionizing autonomous orbit management, paving the way for more efficient and adaptable satellite operations while incorporating the physical constraints of satellite, such as thruster limitations.
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| 12. |
- Mascherpa, Michele, et al.
(författare)
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Estimating pollution spread in water networks as a Schrödinger bridge problem with partial information
- 2023
-
Ingår i: European Journal of Control. - : Elsevier Ltd. - 0947-3580 .- 1435-5671.
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Tidskriftsartikel (refereegranskat)abstract
- Incidents where water networks are contaminated with microorganisms or pollutants can result in a large number of infected or ill persons, and it is therefore important to quickly detect, localize and estimate the spread and source of the contamination. In many of today's water networks only limited measurements are available, but with the current internet of things trend the number of sensors is increasing and there is a need for methods that can utilize this information. Motivated by this fact, we address the problem of estimating the spread of pollution in a water network given measurements from a set of sensors. We model the water flow as a Markov chain, representing the system as a set of states where each state represents the amount of water in a specific part of the network, e.g., a pipe or a part of a pipe. Then we seek the most likely flow of the pollution given the expected water flow and the sensors observations. This is a large-scale optimization problem that can be formulated as a Schrödinger bridge problem with partial information, and we address this by exploiting the connection with the entropy regularized multimarginal optimal transport problem. The software EPANET is used to simulate the spread of pollution in the water network and will be used for testing the performance of the methodology. © 2023 The Author(s)
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| 13. |
- Naha, Arunava, et al.
(författare)
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Quickest physical watermarking-based detection of measurement replacement attacks in networked control systems
- 2023
-
Ingår i: European Journal of Control. - : Elsevier. - 0947-3580 .- 1435-5671. ; 71
-
Tidskriftsartikel (refereegranskat)abstract
- In this paper, we propose and analyze an attack detection scheme for securing the physical layer of a networked control system (NCS) with a wireless sensor network against attacks where the adversary replaces the true observations with stationary false data. An independent and identically distributed watermarking signal is added to the optimal linear quadratic Gaussian (LQG) control inputs, and a cumulative sum (CUSUM) test is carried out using the joint distribution of the innovation signal and the watermarking signal for quickest attack detection. We derive the expressions of the supremum of the average detection delay (SADD) for a multi-input and multi-output (MIMO) system under the optimal and sub-optimal CUSUM tests. The SADD is asymptotically inversely proportional to the expected Kullback–Leibler divergence (KLD) under certain conditions. The expressions for the MIMO case are simplified for multi-input and single-output systems and explored further to distil design insights. We provide insights into the design of an optimal watermarking signal to maximize KLD for a given fixed increase in LQG control cost when there is no attack. Furthermore, we investigate how the attacker and the control system designer can accomplish their respective objectives by changing the relative power of the attack signal and the watermarking signal. Simulations and numerical studies are carried out to validate the theoretical results.
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| 14. |
- Niazi, Muhammad Umar B., et al.
(författare)
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Resilient set-based state estimation for linear time-invariant systems using zonotopes
- 2023
-
Ingår i: European Journal of Control. - : Elsevier BV. - 0947-3580 .- 1435-5671. ; 74
-
Tidskriftsartikel (refereegranskat)abstract
- This paper considers the problem of set-based state estimation for linear time-invariant (LTI) systems under time-varying sensor attacks. Provided that the LTI system is stable and observable via every single sensor and that at least one sensor is uncompromised, we guarantee that the true state is always contained in the estimated set. We use zonotopes to represent these sets for computational efficiency. However, we show that intelligently designed stealthy attacks may cause exponential growth in the algorithm's worst-case complexity. We present several strategies to handle this complexity issue and illustrate our resilient zonotope-based state estimation algorithm on a rotating target system.
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| 15. |
- Parvini Ahmadi, Shervin, 1989-, et al.
(författare)
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Distributed optimal control of nonlinear systems using a second-order augmented Lagrangian method
- 2023
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Ingår i: European Journal of Control. - : Elsevier. - 0947-3580 .- 1435-5671. ; 70
-
Tidskriftsartikel (refereegranskat)abstract
- In this paper, we propose a distributed second-order augmented Lagrangian method for distributed optimal control problems, which can be exploited for distributed model predictive control. We employ a primal-dual interior-point approach for the inner iteration of the augmented Lagrangian and distribute the corresponding computations using message passing over what is known as the clique tree of the problem. The algorithm converges to its centralized counterpart and it requires fewer communications between sub-systems as compared to algorithms such as the alternating direction method of multipliers. We illustrate the efficiency of the framework when applied to randomly generated interconnected sub-systems as well as to a vehicle platooning problem.
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| 16. |
- Persson, Linnea, et al.
(författare)
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An optimization algorithm based on forward recursion with applications to variable horizon MPC
- 2024
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Ingår i: European Journal of Control. - : ELSEVIER. - 0947-3580 .- 1435-5671. ; 75
-
Tidskriftsartikel (refereegranskat)abstract
- We consider optimization algorithms designed for variable horizon model predictive control. Traditionally, such problems are considered intractable for real-time applications that require fast computations, as they need to solve multiple optimal control problems with varying horizons at each sampling instance. The main contribution is an algorithm that efficiently solves multiple optimal control problems with different prediction horizons in a recursive manner. This algorithm has been successfully implemented and integrated into the OSQP solver, resulting in a real-time controller that is both fast and reliable. To assess the effectiveness of the approach, we conducted evaluations in both a realistic simulation environment and on real hardware during outdoor flight experiments. Specifically, we focused on two distinct rendezvous maneuvers for autonomous landings of unmanned aerial vehicles. The results obtained from these evaluations further validate the practicality and efficacy of the proposed algorithm. (c) 2023 The Author(s). Published by Elsevier Ltd on behalf of European Control Association. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )
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| 17. |
- Ramakrishna, Raksha, et al.
(författare)
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Sequential Experiment Design for Parameter Estimation of Nonlinear Systems using a Neural Network Approximatort
- 2023
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Ingår i: European Journal of Control. - : Elsevier BV. - 0947-3580 .- 1435-5671. ; 74
-
Tidskriftsartikel (refereegranskat)abstract
- We consider the problem of sequential parameter estimation of a nonlinear function under the Bayesian setting. The designer can choose inputs for a sequence of experiments to obtain an accurate estimate of the system parameters based on observed outputs, while complying with a constraint on the expected outputs of the system. We quantify the accuracy of the obtained estimate in terms of the pound 2 norm. We propose to solve the problem by casting it as the problem of minimizing the Bayesian Mean Square Error (BMSE) of the parameter estimate subject to a constraint on the expected deviation of the output from the desired target value. We develop a greedy policy to solve the problem in the sequential setting, and we characterize the solution structure based on analytical results for the Gaussian case. For a computationally tractable update of the posterior, we propose the use of a surrogate model combined with approximate Bayesian computation. We evaluate the proposed approach on the use case of smart road compaction, where the goal is to estimate asphalt parameters while reaching the desired compaction level, by choosing the value of the loading pressure. Simulation results on a synthetic road compaction dataset show the efficacy of the proposed solution scheme in both parameter estimation and effective compaction of the road.
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| 18. |
- Rikos, Apostolos, et al.
(författare)
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Distributed computation of exact average degree and network size in finite time under quantized communication
- 2023
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Ingår i: European Journal of Control. - : Elsevier BV. - 0947-3580 .- 1435-5671. ; 74
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Tidskriftsartikel (refereegranskat)abstract
- We consider the problems of computing the average degree and the size of a given network in a distributed fashion and under quantized communication. More specifically, we present two distributed algorithms, which rely on quantized operation (i.e., nodes process and transmit quantized messages) and are able to obtain the exact solutions in a finite number of steps. During the operation of our algorithms, each node can determine in a distributed manner whether convergence has been achieved and correspondingly terminate its operation. For terminating the operation of our algorithms, we assume a known bound for the network diameter. To the best of the authors' knowledge, these algorithms are the first to find exact solutions (i.e., with no error in the final result) under quantized communication. Note that our network size calculation algorithm is the first in the literature to calculate the exact size of a network in a finite number of steps without introducing a final error; in other algorithms, this error can be either due to quantization or asymptotic convergence. In our case, no error is introduced since the desired result is calculated in the form of a fraction involving an integer numerator and an integer denominator. We demonstrate the operation of our algorithms and their potential advantages through simulations.
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| 19. |
- Taghavian, Hamed, 1992-, et al.
(författare)
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Preservation of external positivity in discretization of linear systems
- 2021
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Ingår i: European Journal of Control. - : Elsevier BV. - 0947-3580 .- 1435-5671. ; 62, s. 69-74
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Tidskriftsartikel (refereegranskat)abstract
- We study the preservation of impulse response non-negativity, also known as external positivity, for general discretization methods. The results yield new subsets in the space of transfer function coefficients which ensure external positivity. Consequently, linear programming approaches for designing controllers ensuring monotonic step responses are derived for both continuous and discrete-time systems.
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| 20. |
- Wachel, Pawe l, et al.
(författare)
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Decentralized diffusion-based learning under non-parametric limited prior knowledge
- 2024
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Ingår i: European Journal of Control. - : Elsevier BV. - 0947-3580 .- 1435-5671. ; 75
-
Tidskriftsartikel (refereegranskat)abstract
- We study the problem of diffusion-based network learning of a nonlinear phenomenon, m, from local agents' measurements collected in a noisy environment. For a decentralized network and information spreading merely between directly neighboring nodes, we propose a non-parametric learning algorithm, that avoids raw data exchange and requires only mild a priori knowledge about m. Non-asymptotic estimation error bounds are derived for the proposed method. Its potential applications are illustrated through simulation experiments.
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