Title :
Intelligent-based PID fault tolerant tracking control for unknown nonlinear MIMO systems
Author :
Guo, Shu-Mei ; Tsai, Jason S H ; Lin, Yen C. ; Tsai, Tzong-Jiy ; Chen, Chia W.
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Cheng-Kung Univ., Tainan, Taiwan
Abstract :
In this paper, a novel intelligent-based fault tolerant control (FTC) framework is proposed to solve the fault tolerant tracking control problem for unknown nonlinear multi-input multi-output (MIMO) systems. To eliminate the effect of faults, a neural network model adapted with the extended Kalman filter (EKF) is created to online identify the unknown systems, and then the steepest descent and evolutionary programming (EP) method is utilized to find a self-tuning proportional-integral-derivative (PID) controller for the adapted neural network. The resulted PID FTC controller can not only achieve the tracking objective but also can maintain the stability and the expected performance when faults occur in system. Finally, a numerical example is given to illustrate the effectiveness of the proposed methods.
Keywords :
Kalman filters; MIMO systems; adaptive control; evolutionary computation; fault tolerance; neurocontrollers; nonlinear control systems; nonlinear filters; three-term control; tracking; tuning; PID FTC controller; adapted neural network; evolutionary programming method; extended Kalman filter; fault tolerant tracking control problem; intelligent-based PID fault tolerant tracking control; intelligent-based fault tolerant control framework; neural network model; self-tuning proportional-integral-derivative controller; steepest descent; unknown nonlinear MIMO systems; unknown nonlinear multi-input multi-output systems; Control systems; Fault diagnosis; Fault location; Fault tolerant systems; Genetic programming; Intelligent control; MIMO; Neural networks; Nonlinear control systems; Three-term control;
Conference_Titel :
Control and Automation, 2009. ICCA 2009. IEEE International Conference on
Conference_Location :
Christchurch
Print_ISBN :
978-1-4244-4706-0
Electronic_ISBN :
978-1-4244-4707-7
DOI :
10.1109/ICCA.2009.5410494