Abstract
The proportional-integral-derivative (PID) controller is widely used in process control engineering. However, the parameter updating of PID controller has been a challenging issue for control engineers. A new approach to apply iterative learning control (ILC) scheme for updating the PID parameters, is presented in this paper. The quadratic performance index is employed to optimize the parameters of the PID controller and then an optimal PID type iterative learning control (ILC) scheme is established for discrete linear time-invariant (LTI) systems. In addition, the convergence analysis of optimal ILC of PID type is well described by using Lyapunov composite energy function. The tracking performance of the desired output can be enhanced by the proper choice of penalty matrices. The resultant performance using proposed methodology is significantly improved in term of convergence as compared to available methods in the literature. Simulation examples are also given also to demonstrate the effectiveness of the proposed scheme.
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Recommended by Associate Editor Vu Nguyen under the direction of Editor Young IL Lee. This work is partly financially supported by the High-tech Research and Development Program of China (2014AA041802). The first author is also thankful to the China Scholarship Council (CSC) for providing financial support for his Ph.D. studies at Dalian University of Technology, China.
Shao Cheng is a Professor, a Head of Institute of Advanced Control Technology, Dalian University of Technology, Dalian, P. R. China. Dean of Liaoning Province Key Laboratory of Advanced Control System for Industrial Equipment. He received his Ph.D. degree and Master’s degree in Control Science and Engineering at Northeastern University, P. R. China in 1992 and 1986, respectively, and a Bachelor’s degree in Mathematics at Liaoning University, P. R. China in 1982. His research interests include control theory in intelligent manufacturing, advanced process control, robust adaptive control, intelligent measurement and control.
Furqan Memon received his B.E. degree in Electronic Engineering from Mehran University of Engineering and Technology, Pakistan, in 2007, and a Master’s degree from National University of Science and Technology, Pakistan, in 2011. At present, he is pursuing a Ph.D. degree from Institute of Advanced Control Technology, Dalian University of Technology, Dalian, PR. China. His research interests include robotics, robust & optimal control and iterative learning control.
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Memon, F., Shao, C. An Optimal Approach to Online Tuning Method for PID Type Iterative Learning Control. Int. J. Control Autom. Syst. 18, 1926–1935 (2020). https://doi.org/10.1007/s12555-018-0840-0
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DOI: https://doi.org/10.1007/s12555-018-0840-0