Dual Self-Triggered Model-Predictive Control for Nonlinear Cyber-Physical Systems
针对带控制约束的非线性信息物理系统，提出一种双自触发模型预测控制策略，通过设计两种触发机制来降低通信负载，并保证算法可行性与闭环稳定性。
This article is concerned with the event-based model-predictive control (MPC) problem of nonlinear cyber-physical systems with control constraints. A novel dual self-triggered MPC strategy is proposed to significantly reduce communication loads. In particular, two triggering mechanisms with two different optimal control problems are appropriately designed by considering whether the system state belongs to the terminal set. We prove that the strategy guarantees the algorithm feasibility and the closed-loop stability if the controller parameters satisfy the proposed conditions. Simulation and comparison studies verify effectiveness and advantages over the existing results.