Event-Driven Cooperative Receding Horizon Control for Multi-Agent Systems in Uncertain Environments

• Published in: IEEE transactions on control of network systems 2018-03, Vol.5 (1), p.409-422
• Main Authors: Khazaeni, Yasaman, Cassandras, Christos G.
• Format: Article
• Language: English
• Subjects: Cooperative control; event-driven control; model predictive control; Multi-agent systems; Optimal control; Optimization; optimization algorithms; path planning; receding horizon control; Space missions; Switches; Trajectory; traveling salesman problem; vehicle routing problem
• ISSN: 2325-5870; 2325-5870; 2372-2533
• DOI: 10.1109/TCNS.2016.2615162

We propose an event-driven Cooperative Receding Horizon (CRH) controller to solve maximum reward collection problems (MRCP) where multiple agents cooperate to maximize the total reward collected from a set of targets in a given mission space. In previous work, a CRH controller was developed and in this paper, we overcome several limitations of this controller, including potential instabilities in the agent trajectories and poor performance due to inaccurate estimation of a reward-to-go function. Rewards are non-increasing functions of time and the environment is uncertain with new targets detected by agents at random time instants. The controller sequentially solves optimization problems over a planning horizon and executes the control for a shorter action horizon, where both are defined by certain events associated with new information becoming available. In contrast to the earlier CRH controller, we reduce the originally infinite-dimensional feasible control set to a finite set at each control update event. We prove some properties of this new controller and include simulation results showing its improved performance.