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Fault diagnosis scheme for nonlinear stochastic systems with time-varying fault: application to the rigid spacecraft control

Hong Quang Nguyen, Sergej Celikovsky
This paper studies the problem of the fault estimation for a class of time-varying faults using output probability density function (PDF). In particular, the spacecraft control system is studied. First, the attitude control of the nonlinear model with uncertainties is given. Then, the measured output is viewed as a stochastic process and its PDF is modeled, which leads to a deterministic dynamical model including nonlinearities and uncertainties. A new adaptive fault diagnosis algorithm is
proposed to improve the performance of the fault estimation.
The proposed algorithm contains both the proportional and the integral term. The proportional term can improve the speed of the fault estimation, while the integral term can eliminate estimation error. Then, based on the linear matrix inequality (LMI) technique, a feasible algorithm is explored to find the designed parameters. Finally, simulation results of the spacecraft are given to show the efficiency of the proposed approach. CYBERNETICS AND PHYSICS, VOL. 1, NO. 3, 2012 , 179–187.
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