Research On Sliding Mode Control Of Uncertain Markov Jump Systems

As a special switching system,Markov jump system has attracted more and more attention because it can describe all kinds of complex practical systems in industrial production.In addition,the uncertainties and external disturbances in real life usually affect the stability of the system,and the sliding mode control method can well deal with the external disturbances and uncertainties in Markov jump system.Therefore,the sliding mode control problem of Markov jump system has been widely concerned and some remarkable achievements have been made.However,with the widespread use of computers in complex control systems,the transmission channel of the system is inevitably affected by cyber attacks and signal congestion,it undoubtedly adds some new difficulties to the research of sliding mode control of Markov jump system.This paper studies this kind of problem.In this paper,several kinds of complex situations of Markov system are analyzed,and the sliding mode control of Markov jump system under complex situations such as unmeasurable system state,partially unknown transition probability and actuator attacks is studied.The specific contents are as follows:For Markov systems with unmeasurable system state and partially unknown transition probability,the sliding mode control problem based on bilateral event-triggered mechanism is studied.Firstly,a two-sided event-triggered condition is designed to solve the problem of network channel blocking.Secondly,a state observer is designed to estimate the system state.Based on Lyapunov theory andH_?performance index,the condition of sliding mode is obtained,which is asymptotically stable and has certain anti-interference ability.Finally,according to the event-triggered mechanism,the event-triggered sliding mode controller is designed to ensure that the system state can reach the strip area of the sliding mode surface in a limited timeAn adaptive sliding mode controller for Markov systems under actuator attacks is studied.Firstly,the neural network technology is used to approximate the attack of actuator.Then the adaptive sliding mode control method is used to compensate the unknown upper and lower bounds for nonlinearities,external disturbances and uncertainties problems.According to Lyapunov theory,the condition of stochastic stability of the closed-loop system is given.Finally,the reachability of the system state is analyzed.For Markov systems with partially unknown transition probability,the sliding mode control problem based on event-triggered mechanism is studied.Firstly,a variable threshold trigger condition is designed for network channel congestion.Based on Lyapunov theory andH_?performance index,the condition for the closed-loop system to be stable is given.Finally,a sliding mode controller based on event-triggered mechanism is designed to ensure that the system state can enter the strip of sliding mode surface.