To diagnose the fault of attitude sensors in satellites, this paper proposes a novel approach based on the Kalman filter of the discrete-time descriptor system. By regarding the sensor fault term as the auxiliary stat...To diagnose the fault of attitude sensors in satellites, this paper proposes a novel approach based on the Kalman filter of the discrete-time descriptor system. By regarding the sensor fault term as the auxiliary state vector, the attitude measurement system subjected to the attitude sensor fault is modeled by the discrete-time descriptor system. The condition of estimability of such systems is given. And then a Kalman filter of the discrete-time descriptor system is established based on the methodology of the maximum likelihood estimation. With the descriptor Kalman filter, the state vector of the original system and sensor fault can be estimated simultaneously. The proposed method is able to esti-mate an abrupt sensor fault as well as the incipient one. Moreover, it is also effective in the multiple faults scenario. Simulations are conducted to confirm the effectiveness of the proposed method.展开更多
This paper addresses 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.Fi...This paper addresses 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 state- feedback 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.展开更多
基金supported by the National Natural Science Foundation of China (60874054)
文摘To diagnose the fault of attitude sensors in satellites, this paper proposes a novel approach based on the Kalman filter of the discrete-time descriptor system. By regarding the sensor fault term as the auxiliary state vector, the attitude measurement system subjected to the attitude sensor fault is modeled by the discrete-time descriptor system. The condition of estimability of such systems is given. And then a Kalman filter of the discrete-time descriptor system is established based on the methodology of the maximum likelihood estimation. With the descriptor Kalman filter, the state vector of the original system and sensor fault can be estimated simultaneously. The proposed method is able to esti-mate an abrupt sensor fault as well as the incipient one. Moreover, it is also effective in the multiple faults scenario. Simulations are conducted to confirm the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation under Grant No.61803256Shanghai Sailing Plan under Grant No.17YF1407300in part by the Talent Program of Shanghai University of Engineering Science
文摘This paper addresses 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 state- feedback 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.
