基于双层不变集的多智能体系统事件触发分布式预测控制

针对含有扰动的多智能体系统，提出了基于双层不变集的事件触发鲁棒分布式预测控制策略。在分布式控制结构下，对每个智能体构建了目标函数含有耦合关联项的事件触发分布式预测控制优化问题。利用输入状态稳定性理论，推导出与子系统自身信息以及邻域子系统信息相关的事件触发条件。每个智能体判断事件触发条件，仅当条件满足时，才进行分布式预测控制优化问题的求解以及子系统之间的信息交互。利用双层不变集来保证扰动作用下多智能体系统的鲁棒性能，并在此基础上给出保证算法递推可行性和闭环稳定性的充分条件。最后通过车辆控制系统对算法进行仿真分析，验证了算法的有效性。

Event-Triggered Distributed Predictive Control for Multi-agent Systems on Two-Layer Invariant Sets

In recent years, multi-agent systems have become one of the hot topics in the field of control research area due to their wide applications in chemical process system, transportation system, smart grid system, and so on. On the other hand, distributed predictive control (DPC) can effectively deal with the hard constraints and make use of the predictive information to estimate the interaction between subsystems in the future. However, for multi-agent systems with limited resources, traditional DPC based on time-triggered mechanism may cause unnecessary waste of resources, if the subsystems update the control laws periodically even if the performance of system has met the requirements. The event triggering mechanism working in a non-periodic way can balance resources consumption and systems performance effectively. In this paper, an event-triggered robust distributed predictive control strategy based on two-layer invariant sets is proposed for multi-agent systems subject to disturbances. Under the distributed control structure, the event-triggered predictive control optimization problem is established for each subsystem by means of the coupled cost function based on event triggered instant. By using the theory of input-to-state stability (ISS), the event-triggered condition is derived, which involves the subsystem''s own information and the information from other neighbour subsystems. When the event-triggering condition is satisfied, the measurement state of subsystem is transmitted to the controller for solving the distributed predictive control optimization problem, and then, the information will be exchanged with neighbours. By introducing two-layer invariant sets, the robustness of the multi-agent systems with disturbances can be guaranteed and sufficient conditions are obtained for ensuring the recursive feasibility and system closed-loop stability. Finally, the proposed algorithm is simulated and the effectiveness is illustrated by a vehicle control system. It is shown from the simulation results that the proposed algorithm can reduce the computational and communication consumption without increasing the complexity of the DPC algorithm.