IEEE Transactions on Automatic Control, Vol.65, No.3, 955-969, 2020
An Improved Homogeneous Polynomial Approach for Adaptive Sliding-Mode Control of Markov Jump Systems With Actuator Faults
This paper investigates an adaptive sliding-mode controller design problem for a class of Markov jump systems with actuator faults. First, a more extensive faults model, which includes actuator loss of effectiveness, outage and stuck, is established. Moreover, a novel sliding surface function is designed and sufficient conditions are established to ensure stochastic stability of the Markov jump systems with known transition probability. Second, based on the adaptive sliding-mode algorithm and the fault compensation algorithm, a comprehensive control law is synthesized not only to overcome the boundary restrictions of actuator loss effectiveness and external disturbances, but also to ensure the properties of stochastic stability and the reachability of the sliding-mode dynamics. Third, an improved stochastically stability criterion, in the case of Markov jump system with uncertain transition probability, is derived based on the homogeneous polynomial matrix technique. Finally, two simulation examples are provided to support the feasibility and effectiveness of the proposed control algorithms.