An adaptive PID controller

Jen Yang Chen, Chuan Hsi Liu, Chang Wei Fan, Haw Yun Shin, Mao Hsu Yen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This paper proposes an adaptive proportional -integral-derivative (PID) controller which integrates the fuzzy sets with the Cerebella Model Articulation Controller (CMAC). Three gain parameters of PID controller, constructed by three fuzzy CMAC (FCMAC) models, are real-time modified in the sense of adaptation to solve the tracking control problem of a class of nonlinear systems. The proposed PID controller is first used to approximate an ideal control, and then based on the estimated approximation error bound an appended controller is designed to assure the system stability. Both controllers are derived from the Lyapunov stability analysis, so that the system tracking ability and the error convergence can be guaranteed in the closed-loop control system. Finally, we apply the proposed control scheme to two nonlinear systems to show the satisfactory performances.

Original languageEnglish
Title of host publication2010 International Conference on Machine Learning and Cybernetics, ICMLC 2010
Pages884-889
Number of pages6
DOIs
Publication statusPublished - 2010 Nov 15
Event2010 International Conference on Machine Learning and Cybernetics, ICMLC 2010 - Qingdao, China
Duration: 2010 Jul 112010 Jul 14

Publication series

Name2010 International Conference on Machine Learning and Cybernetics, ICMLC 2010
Volume2

Other

Other2010 International Conference on Machine Learning and Cybernetics, ICMLC 2010
CountryChina
CityQingdao
Period10/7/1110/7/14

Keywords

  • Adaptive control
  • CMAC
  • Fuzzy sets
  • PID controller
  • System stability

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Human-Computer Interaction

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  • Cite this

    Chen, J. Y., Liu, C. H., Fan, C. W., Shin, H. Y., & Yen, M. H. (2010). An adaptive PID controller. In 2010 International Conference on Machine Learning and Cybernetics, ICMLC 2010 (pp. 884-889). [5580596] (2010 International Conference on Machine Learning and Cybernetics, ICMLC 2010; Vol. 2). https://doi.org/10.1109/ICMLC.2010.5580596