Mixed Time/Event-Triggered Model Predictive Tracking Control for Networked Mobile Robots

Focusing on the tracking control challenges in networked mobile robot systems, this research formulates a mixed time/event-triggered model predictive control (MPC) method. The method integrates time-triggered and event-triggered mechanisms, where the time-triggered module improves the performance of the MPC, and the event-triggered module reduces the resource consumption without sacrificing the control performance. The MPC algorithm is developed based on the auxiliary optimization problem (OP), which is constrained by linear matrix inequalities. The feasibility of the auxiliary OP is evaluated, and the mean square stability of the closed-loop system is investigated. The research results are expected to save network resources while ensuring the performance of networked mobile robots and provide strong support for practical applications of networked mobile robots.