Intelligent sensor fault detection and identification for temperature control
ICCOMP'07 Proceedings of the 11th WSEAS International Conference on Computers
Implementation of intelligent active fault tolerant control system
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part I
Multi-agent systems in control engineering: a survey
Journal of Control Science and Engineering
Combining adaptive with artificial intelligence and nonlinear methods for fault tolerant control
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part III
Expert Systems with Applications: An International Journal
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Fault tolerant control of dynamic processes is investigated in this paper using an auto-tuning PID controller. A fault tolerant control scheme is proposed composing an auto-tuning PID controller based on an adaptive neural network model. The model is trained online using the extended Kalman filter (EKF) algorithm to learn system post-fault dynamics. Based on this model, the PID controller adjusts its parameters to compensate the effects of the faults, so that the control performance is recovered from degradation. The auto-tuning algorithm for the PID controller is derived with the Lyapunov method and therefore, the model predicted tracking error is guaranteed to converge asymptotically. The method is applied to a simulated two-input two-output continuous stirred tank reactor (CSTR) with various faults, which demonstrate the applicability of the developed scheme to industrial processes.