Sensor Fault Estimation and Fault-Tolerant Control for a Class of Takagi-Sugeno Markovian Jump Systems with Partially Unknown Transition Rates Based on the Reduced-Order Observer

摘要

This paperaddresses the problem on sensor fault estimation and fault-tolerant control for a class of Takagi-Sugeno Markovian jump systems,which are subjected to sensor faults and partially unknown transition rates.First,the original plant is extended to a descriptor system,where the original states and the sensor faults are assembled into the new state vector.Then,a novel reduced-order observer is designed for the extended system to simultaneously estimate the immeasurable states and sensor faults.Second,by using the estimated states obtained from the designed observer,a statefeedback fault-tolerant control strategy is developed to make the resulting closed-loop control system stochastically stable.Based on linear matrix inequality technique,algorithms are presented to compute the observer gains and control gains.The effectiveness of the proposed observer and controller are validated by a numerical example and a compared study,respectively,and the simulation results reveal that the proposed method can successfully estimate the sensor faults and guarantee the stochastic stability of the resulting closed-loop system.