In this paper, the hidden Markov model method is used to represent the asynchronous mode variations between the original systems and the fault estimator. The robust H ∞ performance index is employed when calculating the fault estimator gain, which effectively suppresses the effect of noise on fault estimation performance. The derived conditions of linear matrix inequalities ensure that the error system is stochastically stable, and a prescribed robust H ∞ performance index requirement is satisfied. The explicit numerical solutions are obtained on the asynchronous fault estimator gains via resolving the derived conditions of linear matrix inequalities. Finally, the effectiveness and applicability of developed theoretical results are verified through a numerical example and a practical single-link robot arm application.

In this article, a novel active fault-tolerant control (AFTC) design method is developed by using the switching linear parameter varying (LPV) controller with inexact fault-effect parameters. The LPV controller is not only considered as a gain-scheduled controller varying with the operating points, but also an AFTC controller varying with the fault-effect parameters, which can be obtained via the fault estimator in real-time. The inexact measurement of fault-effect parameters is considered for the first time in this article. To cover large parameters variation, a class of switched LPV fault-tolerant controller is designed to work in the multiple partitioned parameters subregions. The dynamic output feedback controller model is constructed to perform the switched LPV fault-tolerant control task under the mode-dependent average dwell time constraint. By using the multiple parameter-dependent Lyapunov function approach, sufficient conditions with less conservatism are obtained, such that the corresponding closed-loop systems are globally uniformly exponentially stable and satisfy an upper bound of weighted l 2 -gain performance indexes. Finally, effectiveness and applicability of the developed approaches are validated via an active magnetic bearing system.

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