Fault-Tolerant Control

This chapter investigates online fault accommodation control problems under various system failures. The focus is on the unanticipated system failures in the general formulation. The effectiveness of the developed online fault accommodation technique for unanticipated system failures is demonstrated through the simulation study. Simulation results indicate that, under the Levenberg-Marquardt training algorithm with Bayesian regularization the online learning of the unanticipated failure dynamics usually converges within 10 iterations, and the online simulation speed can reach two to three time-steps per second under the Intel Pentium II 450 dual processors. A complete architecture for intelligent fault diagnosis and accommodation is also presented by incorporating the proposed intelligent fault-tolerant control technique with a cost-effective fault-detection scheme and a multiple model based failure diagnosis process to efficiently handle the false alarms and the accommodation of the anticipated failure modes. Simulation results indicate that unnecessary control effort and computational complexity are significantly reduced in online situations when the failures are anticipated. Under the multiple model-based failure diagnosis process together with the post failure control actions, a successful fault isolation mission is quickly reached through the multiple model failure recognition. System performance recovery can be obtained through the multiple models switching in the post failure control actions.

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