| 1. |
- Bahraini, Masoud, 1991, et al.
(author)
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Communication Demand Minimization for Perturbed Networked Control Systems with Coupled Constraints
- 2023
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In: Proceedings of the IEEE Conference on Decision and Control. - 2576-2370 .- 0743-1546. ; , s. 3468-3473
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Conference paper (peer-reviewed)abstract
- Communication scheduling is needed when control loops of several safety-critical systems are closed through a shared communication medium. To enable schedulability, control for each system is designed primarily to minimize its communication demand. In this paper, we study communication demand minimization for a class of perturbed multi-agent networked control systems with a shared communication medium and subject to input and coupled state constraints. First, a framework to design communication schedule and control is recalled such that state and input constraints are satisfied under no coupling assumption. Then, a heuristic method is proposed to decouple state constraints such that the overall communication demand of the systems is minimized. Effectiveness of the proposed results are illustrated through a numerical example.
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| 2. |
- Bahraini, Masoud, 1991, et al.
(author)
-
Optimal scheduling and control for constrained multi-agent networked control systems
- 2022
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In: Optimal Control Applications and Methods. - : Wiley. - 1099-1514 .- 0143-2087. ; 43:1, s. 23-43
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Journal article (peer-reviewed)abstract
- In this paper, we study optimal control and communication schedule co-design for multi-agent networked control systems, with assuming shared parallel communication channels and uncertain constrained linear time-invariant discrete-time systems. To that end, we specify the communication demand for each system using an associated robust control invariant set and reachability analysis. We use these communication demands and invariant sets to formulate tube-based model predictive control and offline/online communication schedule co-design problems. Since the scheduling part includes an infinite dimension integer problem, we propose heuristics to find suboptimal solutions that guarantee robust constraints satisfaction and recursive feasibility. The effectiveness of our approach is illustrated through numerical simulations.
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| 3. |
- Bahraini, Masoud, 1991, et al.
(author)
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Robust Control Invariance for Networked Control Systems with Output Feedback
- 2022
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In: Proceedings of the IEEE Conference on Decision and Control. - 0743-1546 .- 2576-2370. ; 2022-December, s. 7676-7681
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Conference paper (peer-reviewed)abstract
- This paper focuses on robust output feedback design for multi-agent networked control systems with a shared communication medium, where each system is subject to state and input constraints. We first compute the communication demand for each system given constant observer and controller gains; we argue that minimization of the communication demand with respect to the control or observer gains is very hard. Then, given a constant observer gain, we compute the minimum communication demand for each system and a corresponding control policy using model predictive control; we argue that the second approach is less difficult to solve and results in a communication demand which is no larger than for a linear controller. We illustrate and compare these design methods by a numerical example.
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| 4. |
- Bahraini, Masoud, 1991, et al.
(author)
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Scheduling and Robust Invariance in Networked Control Systems
- 2022
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In: IEEE Transactions on Automatic Control. - 0018-9286 .- 1558-2523. ; 67:6, s. 3075-3082
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Journal article (peer-reviewed)abstract
- In Networked Control Systems (NCS), impairments of the communication channel can be disruptive to stability and performance. In this paper, we consider the problem of scheduling the access to limited communication resources for a number of decoupled systems subject to state and input constraints, whose loops need to be closed over the network. The schedule must be designed to robustly preserve the invariance property of each system, which in turn guarantees constraint satisfaction. To that end, we first focus on systematic offline scheduling design to preserve robust invariance, and afterwards on online scheduling design with the aim of improving performance and compensating for packet losses while guaranteeing recursive schedulability.
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| 5. |
- Batkovic, Ivo, 1992, et al.
(author)
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A Computationally Efficient Model for Pedestrian Motion Prediction
- 2018
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Conference paper (peer-reviewed)abstract
- We present a mathematical model to predict pedestrian motion over a finite horizon, intended for use in collision avoidance algorithms for autonomous driving. The model is based on a road map structure, and assumes a rational pedestrian behavior. We compare our model with the state-of-the art and discuss its accuracy, and limitations, both in simulations and in comparison to real data.
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| 6. |
- Batkovic, Ivo, 1992, et al.
(author)
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Experimental Validation of Safe MPC for Autonomous Driving in Uncertain Environments
- 2023
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In: IEEE Transactions on Control Systems Technology. - 1063-6536 .- 1558-0865. ; 31:5, s. 2027-2042
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Journal article (peer-reviewed)abstract
- The full deployment of autonomous driving systems on a worldwide scale requires that the self-driving vehicle can be operated in a provably safe manner, i.e., the vehicle must be able to avoid collisions in any possible traffic situation. In this article, we propose a framework based on model predictive control (MPC) that endows the self-driving vehicle with the necessary safety guarantees. In particular, our framework ensures constraint satisfaction at all times while tracking the reference trajectory as close as obstacles allow, resulting in a safe and comfortable driving behavior. To discuss the performance and real-time capability of our framework, we provide first an illustrative simulation example, and then, we demonstrate the effectiveness of our framework in experiments with a real test vehicle.
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| 7. |
- Batkovic, Ivo, 1992, et al.
(author)
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Model Predictive Control for Safe Autonomous Driving Applications
- 2023
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In: Lecture Notes in Intelligent Transportation and Infrastructure. - Cham : Springer International Publishing. - 2523-3459 .- 2523-3440. ; Part F1376, s. 255-282
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Book chapter (other academic/artistic)abstract
- Although Model Predictive Control is widely used in motion planning and control for autonomous driving applications, accommodating closed-loop stability with respect to an arbitrary reference trajectory and avoidance of pop-up or moving obstacles is still an open problem. While it is well-known how to design a closed-loop stable MPC with respect to a reference trajectory that satisfies the system dynamics, this chapter discusses how to guarantee stability of a vehicle motion planner and controller when a user-provided arbitrary reference is used. Furthermore, the proposed MPC scheme enables recursive collision-avoidance constraint satisfaction in the presence of pop-up or moving obstacles (e.g., pedestrians, cyclists, human-driven vehicles), provided that their predicted future motion trajectory is available together with some uncertainty bound and satisfies some mild requirement. The proposed motion planner and controller is demonstrated through simulations.
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| 8. |
- Batkovic, Ivo, 1992, et al.
(author)
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Real-Time Constrained Trajectory Planning and Vehicle Control for Proactive Autonomous Driving with Road Users
- 2019
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In: 2019 18th European Control Conference, ECC 2019. - 9783907144008 ; , s. 256-262
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Conference paper (peer-reviewed)abstract
- For motion planning and control of autonomous vehicles to be proactive and safe, pedestrians' and other road users' motions must be considered. In this paper, we present a vehicle motion planning and control framework, based on Model Predictive Control, accounting for moving obstacles. Measured pedestrian states are fed into a prediction layer which translates each pedestrians' predicted motion into constraints for the MPC problem. Simulations and experimental validation were performed with simulated crossing pedestrians to show the performance of the framework. Experimental results show that the controller is stable even under significant input delays, while still maintaining very low computational times. In addition, real pedestrian data was used to further validate the developed framework in simulations.
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| 9. |
- Batkovic, Ivo, 1992, et al.
(author)
-
Safe Trajectory Tracking in Uncertain Environments
- 2023
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In: IEEE Transactions on Automatic Control. - 0018-9286 .- 1558-2523. ; 68:7, s. 4204-4217
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Journal article (peer-reviewed)abstract
- In Model Predictive Control (MPC) formulations of trajectory tracking problems, infeasible reference trajectories and a-priori unknown constraints can lead to cumbersome designs, aggressive tracking, and loss of recursive feasibility. This is the case, for example, in trajectory tracking applications for mobile systems in the presence of constraints which are not fully known a-priori. In this paper, we propose a new framework called Model Predictive Flexible trajectory Tracking Control (MPFTC), which relaxes the trajectory tracking requirement. Additionally, we accommodate recursive feasibility in the presence of a-priori unknown constraints, which might render the reference trajectory infeasible. In the proposed framework, constraint satisfaction is guaranteed at all times while the reference trajectory is tracked as good as constraint satisfaction allows, thus simplifying the controller design and reducing possibly aggressive tracking behavior. The proposed framework is illustrated with three numerical examples.
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| 10. |
- Charalambous, Themistoklis, 1981, et al.
(author)
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On the Resource Allocation Problem in Wireless Networked Control Systems
- 2017
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In: IEEE Conference on Decision and Control. - : IEEE. - 0743-1546. - 9781509028733 ; 2018-January, s. 4147-4154
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Conference paper (peer-reviewed)abstract
- This paper considers the scheduling problem of a decentralized system where a number of dynamical subsystems with no computational power are scheduled to transmit their measurements via a resource-limited communication network to a remote decision maker who acts as an estimator, controller and scheduler for the subsystems. We propose a new approach for communication resource allocation for a wide class of ob- jective functions, for both coupled and decoupled systems, and for both scheduling observations as well as control commands. This framework allows to schedule over a finite horizon and can explicitly deal with stochastic channels. For decoupled subsystems, we propose the notion of cost of information loss (CoIL) and we demonstrate that the communications resource allocation problem can be directly expressed in terms of CoIL functions as an assignment-type optimization problem. Illustra- tive examples demonstrate how communication resources affect the performance of the system.
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