Event-Triggered Distributed MPC for Cyber-Physical Systems: An Adaptive Dual-Horizon Mechanism

This paper aims to propose a new event-triggered distributed model predictive control framework based on an adaptive dual-horizon (prediction and control horizon) mechanism for multi-agent cyber-physical systems (CPS) with additive disturbances. Firstly, the control horizon is introduced into the constrained optimal control problem (OCP) of multi-agent CPS to reduce the number of independent variables and improve the rapidity of the algorithm. Secondly, a periodic event-triggered mechanism with Zeno-free behavior is designed based on state error information, which can more efficiently reduce the frequency of solving OCP. Then, adaptive prediction horizon and control horizon contraction mechanisms are designed, effectively reducing the computational complexity of solving OCP for the controller at the triggering moment. In addition, sufficient conditions are provided through theoretical analysis to guarantee the recursive feasibility of algorithm and the stability of the closed-loop system. Finally, the effectiveness of the proposed algorithm is verified through simulation and experimentation example of networked multi-robot system, and the results showed that the algorithm can effectively reduce communication resource consumption and computational complexity in solving OCP while ensuring the expected cooperative control effect. Note to Practitioners—The feature of this paper is to propose a new distributed model predictive control method for control engineers of CPS, such as aircraft formation, vehicle formation, and multi-robot systems. The aim is to effectively reduce the online computational complexity and the impact of high communication rates on control performance. Specifically, we achieved rapid solution of OCP and efficient utilization of communication resources through time-varying prediction and control horizons, and lowering the sampling and communication frequency through event-triggered mechanisms. It should be emphasized that the proposed mechanisms may require the multicore computation unit to implement, as the computation of the OCP and the verification of the event triggered condition need to be performed simultaneously. To facilitate the application of the method, practical experiments on multi-robot systems have also been conducted, providing practical implementation guidelines.