Abstract—In this paper, a self-tuning fuzzy iterative learning control algorithm is proposed to ensure the improvement and enhancement in the performance of the control system by using the benefits of both feedback control due to fuzzy controller and feed forward compensation due to iterative learning controller (ILC) merged in the same control system structure. The performance of proposed algorithm was assessed in a mechatronic system to illustrate the validation of the proposed procedure and the effectiveness of the self-tuning fuzzy iterative learning controller. The simulations results show that the proposed self-tuning fuzzy iterative learning control (STFILC) can reduce the trajectory error in far less number of iterations.
Index Terms—Iterative learning control (ILC), fuzzy control system, self-tuning, X-Y table, computer numerical controlled (CNC) machines.
The authors are with the Industrial Electronics and Control Engineering Department, Faculty of Electronic Engineering Menouf, Minoufiya University, Menouf, 32952, Minoufiya, Egypt (e-mail: email@example.com, drmoh_2000@ yahoo.com, firstname.lastname@example.org).
Cite: Osama Elshazly, Mohammad El-Bardini, and Nabila M. El-Rabaie, "Development of Self -Tuning Fuzzy Iterative Learning Control for Controlling a Mechatronic System," International Journal of Information and Electronics Engineering, vol. 2, no. 4, pp. 565-569, 2012.