Adaptive neural model-based fault tolerant control for multi-variable processes
Engineering Applications of Artificial Intelligence
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Fault diagnosis and accommodation (FDA) for nonlinear multivariables system under multi-fault are investigated in the paper. A complete FDA architecture is proposed by incorporating the intelligent fault tolerant control strategy with a cost-effective fault detection and diagnosis (FDD) scheme based on a multiple-model. The schem efficiently handles the accommodation of both the anticipated and unanticipated failures in online situations. The three-tank with multiple sensor fault concurrence is simulated, the simulating result shows that the fault detection and tolerant control strategy has stronger robustness and tolerant fault ability.