Optimal Output Tracking for Switched Systems Under DoS Attacks: A Model-Free Adaptive Predictive Control Method

Abstract

This paper studies a new resilient event-triggered model-free adaptive predictive control (MFAPC) method with anti-attacks for disturbed switched nonlinear systems in non-ideal network. The switched nonlinear systems are transformed into equivalent dynamic data models by dynamic linearization. Considering the denial of service (DoS) attacks in non-ideal network environment, an anti-attacks method based on a hold mechanism and a resilient event-triggering strategy (RETS) is considered, which reduces attacks impact on system performance. A parameter estimator is given to estimate the external disturbance and further obtain accurate system models. In addition, a new tracking error boundedness analysis method is given by using the average dwell time (ADT) technique and Lyapunov function. Finally, motor simulation results are given to verify the applicability of the proposed method.