Abstract
Digital PID controllers design method in a parameter space is proposed in this article. Sensitivity analysis is processed to meet specifications in gain margin and phase margin. The stability boundary is plotted based on the proposed method in this article. The genetic algorithm is used for integral absolute error, integral time-weighted absolute error, integral square error, and integral time-weighted square error. A design procedure is proposed in this article. The design procedure is applied for a model of a boiler and a model with time delay. Computer simulation results show that the proposed method is effective.
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Recommended by Associate Editor Yingmin Jia under the direction of Editor Euntai Kim. This article was supported by the Ministry of Science and Technology, Taiwan, R.O.C. with MOST107-2218-E-032-004.
Jau-Woei Perng was born in Hsinchu, Taiwan, in 1973. He received the B.S. and M.S. degrees in electrical engineering from the Yuan Ze University, Chungli, Taiwan, in 1995 and 1997, respectively, and the Ph.D. degree in electrical and control engineering from the National Chiao Tung University (NCTU), Hsinchu, Taiwan, in 2003. From 2004 to 2008, he was a Research Assistant Professor with the Department of Electrical and Control Engineering, NCTU. Since 2008, he has been with the Department of Mechanical and Electromechanical Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan, where he is currently an Associate Professor. His research interests include robust control, nonlinear control, fuzzy logic control, neural networks, mobile robots, systems engineering and intelligent vehicle control.
Shan-Chang Hsieh received the B.S. degree from National Kaohsiung Normal University, Taiwan, R.O.C., in 1998. Currently he is working toward a Ph.D. in the area of control systems engineering at National Sun Yat-Sen University, Kaohsiung, Taiwan, R.O.C.. His research interests include control theories, nonlinear systems and applications of control systems.
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Perng, JW., Hsieh, SC. Design of Digital PID Control Systems Based on Sensitivity Analysis and Genetic Algorithms. Int. J. Control Autom. Syst. 17, 1838–1846 (2019). https://doi.org/10.1007/s12555-018-0570-3
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DOI: https://doi.org/10.1007/s12555-018-0570-3