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This paper is concerned with the event-triggered anti-disturbance control of Markov jump systems with general transition probabilities. The associated multiple disturbances cover matched and unmatched cases. Two dynamic triggering mechanisms are constructed by utilizing the tanh -function to adjust thresholds varying with input error. An adaptive disturbance observer is presented in terms of a row-by-row configuration to estimate unknown matched disturbance. According the mechanisms, corresponding composite state-feedback controllers are proposed by integrating threshold bound and adaptive estimation. Resorting to the Lyapunov stability theory and the stochastic analysis technique, the resulted closed-loop system is stochastically bounded with the required H ∞ performance. A structured separation method is utilized to solve the controller gain in terms of linear matrix inequalities. Finally, the validity of proposed schemes is verified by a numerical simulation comparison. [ABSTRACT FROM AUTHOR]

This paper is dedicated to a proportional–integral intermediate estimator based fault-tolerant control method for Markov jump systems with event-triggered inputs. A proportional–integral type intermediate estimator is established to reconstruct sensor and actuator faults, as well as system states. A dynamic event-triggered mechanism is designed to reduce unnecessary transmissions between the controller and the actuator. A threshold-dependent fault-tolerant controller is established to actively compensate for actuator faults. Finsler's lemma is adopted to decouple the control gain, the observer gain and the Lyapunov variable. At last, the proposed estimation method is verified by a comparison example. • A PI–type intermediate observer is designed to obtain better estimation performance. • A threshold-dependent triggering scheme is designed to reduce the network burden. • A structured separation method is adopted to address complex couplings between gains. [ABSTRACT FROM AUTHOR]