Title :
Iterative Learning Control of hysteresis nonlinearity system
Author :
Wei, Wang ; Xinlong, Zhao
Author_Institution :
Coll. of Mech. Eng. & Autom., Zhejiang Sci-Tech Univ., Hangzhou, China
Abstract :
Hysteresis nonlinearity can result in the degradation of system performance and even lead to instability. A control method based on ILC (Iterative Learning Control) is proposed to control the nonlinear system with hysteresis. First, appropriate updating law is selected to design the ILC controller. Then optimal control signal is chosen by means of iterative learning. Finally, the system output can continually converge to the expectation. This method has good performance and can improve the precision of system. The simulation result shows the effectiveness of the proposed method.
Keywords :
control nonlinearities; hysteresis; iterative methods; learning systems; optimal control; stability; ILC; hysteresis nonlinearity system; instability; iterative learning control; nonlinear system; optimal control signal; system performance degradation; updating law; Control systems; Fuzzy systems; Hysteresis; Mechatronics; Precision engineering; hysteresis; iterative learning; updating law;
Conference_Titel :
Control Conference (CCC), 2012 31st Chinese
Conference_Location :
Hefei
Print_ISBN :
978-1-4673-2581-3