Non‐Fragile Sampled‐Data Path Following Control of Autonomous Electric Vehicles With Semi‐Markov Jump Actuator Failures: Tackling Complex Transition Rates

This paper addresses the non‐fragile sampled‐data control problem for path following of autonomous electric vehicles (AEVs) with semi‐Markov jump actuator failures. Firstly, due to the uncertainty of tire dynamics, linear fractional transformation formulations are used to describe the lateral dynamics of AEVs. Secondly, to accurately depict the stochastic actuator failures, the proposed actuator failures model incorporates a semi‐Markov jump process with partially unknown transition rates. Moreover, a non‐fragile control strategy is adopted to enhance the robustness of the controller. Thirdly, a two‐sided looped Lyapunov functional is constructed to alleviate the positivity constraints over the whole sampling interval. Furthermore, based on the two‐sided looped Lyapunov functional and free matrix‐based integral inequality, some sufficient conditions are derived in the form of linear matrix inequalities to ensure the AEVs are stochastically stable with performance. Ultimately, the correlative simulation is carried out to validate the effectiveness of the proposed method.