Control and Optimization for Event-triggered Networked Autonomous Multi-agent Systems
Final Report Abstract
Within this project we studied novel distributed control algorithms for networked multiagent systems (MAS). The steady developments in the area of (wireless) communication technology enables the use of MAS in applications like surveillance and search and rescue. In such systems the communication bandwidth can be seen as a limited resource. As such, it becomes crucial to transmit new data only when necessary. In this project we have developed novel event-triggered control and communication strategies for a variety of problems from MAS literature, like consensus and coverage control. Up until now, results considered simple linear, single integrator systems. However, many real-world systems, like robots, are described by nonlinear dynamical equations. We provide novel results for systems with such complex dynamics. In addition, we studied the application of different MAS concepts in the context of cooperative manipulation. We chose this scenario, since it requires a high degree of coordination, showcasing the strength of our algorithms. In this context, we have developed a novel distributed control algorithm with event-triggered communication and provide a thorough study about the effects of the event-triggered communication in such a system. As a different application of MAS theory, social networks can be modelled as multiagent networks. By applying concepts from system and control engineering, we develop novel models and study the manipulability of opinion dynamics and the effects of mass media on the opinion formation. Finally, we have studied advanced control schemes for MAS. With rising computational resources, it becomes more feasible to integrate data-driven strategies in MAS control algorithms. In this context we provide novel results for data-driven coordination in the presence uncertain or unknown interaction dynamics. In addition, we provide novel distributed strategies for link manipulation of the underlying communication topology in a MAS network. We show that this improves network resilience and controls epidemic spreading.
Publications
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Distributed Topology Manipulation to Control Epidemic Spreading Over Networks. IEEE Transactions on Signal Processing, 67(5), 1163-1174.
Xue, Dong & Hirche, Sandra
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Finite‐time distributed topology design for optimal network resilience. IET Control Theory & Applications, 13(17), 2792-2799.
Xue, Dong & Hirche, Sandra
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Human–Robot Team Interaction Through Wearable Haptics for Cooperative Manipulation. IEEE Transactions on Haptics, 12(3), 350-362.
Music, Selma; Salvietti, Gionata; Dohmann, Pablo Budde gen.; Chinello, Francesco; Prattichizzo, Domenico & Hirche, Sandra
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Polarizability, Consensusability, and Neutralizability of Opinion Dynamics on Coopetitive Networks. IEEE Transactions on Automatic Control, 64(8), 3339-3346.
Liu, Fangzhou; Xue, Dong; Hirche, Sandra & Buss, Martin
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Distributed Control for Cooperative Manipulation With Event-Triggered Communication. IEEE Transactions on Robotics, 36(4), 1038-1052.
Dohmann, Pablo Budde gen. & Hirche, Sandra
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Event-Triggered Consensus for Euler-Lagrange Systems with Communication Delay. IFAC-PapersOnLine, 53(2), 2777-2782.
Dohmann, Pablo Budde gen. & Hirche, Sandra
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Fully Distributed Cooperation for Networked Uncertain Mobile Manipulators. IEEE Transactions on Robotics, 36(4), 984-1003.
Ren, Yi; Sosnowski, Stefan & Hirche, Sandra
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Opinion Behavior Analysis in Social Networks Under the Influence of Coopetitive Media. IEEE Transactions on Network Science and Engineering, 7(3), 961-974.
Xue, Dong; Hirche, Sandra & Cao, Ming
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Data-driven output synchronization of heterogeneous leader-follower multi-agent systems. 2021 60th IEEE Conference on Decision and Control (CDC) (2021, 12, 14), 466-471. American Geophysical Union (AGU).
Jiao, Junjie; van Waarde, Henk J.; Trentelman, Harry L.; Camlibel, M. Kanat & Hirche, Sandra
