Design of new fault diagnosis and fault tolerant control scheme for non-Gaussian singular stochastic distribution systems. (English) Zbl 1257.93110

Yao, Lina; Qin, Jifeng; Wang, Hong; Jiang, Bin

Automatica 48, No. 9, 2305-2313 (2012).

Summary: New Fault Diagnosis (FD) and Fault Tolerant Control (FTC) algorithms for non-Gaussian singular Stochastic Distribution Control (SDC) systems are presented in this paper. Different from general SDC systems, in singular SDC systems, the relationship between the weights and the control input is expressed by a singular state space model, which increases the difficulty in the FD and FTC design. The proposed approach relies on an iterative learning observer (ILO) for fault estimation. The fault may be constant, fast-varying or slow-varying. Based on the estimated fault information, the fault tolerant controller can be designed to make the post-fault Probability Density Function (PDF) still track the given distribution. Simulations are given to show the effectiveness of the proposed FD and FTC algorithms.

MSC:

93E12	Identification in stochastic control theory
93B35	Sensitivity (robustness)
93C15	Control/observation systems governed by ordinary differential equations
68T05	Learning and adaptive systems in artificial intelligence

Keywords:

fault diagnosis; iterative learning observer; fault tolerant control; singular stochastic distribution systems; probability density function; iterative learning observer (ILO); probability density function (PDF)

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