Adaptive PID Controller for Nonlinear Systems using Fuzzy Model

퍼지 모델을 이용한 비선형 시스템의 적응 PID 제어기

  • 김종화 (부경대학교 대학원 전자공학과) ;
  • 이원창 (부경대학교 대학원 전자공학과) ;
  • 강근택 (부경대학교 대학원 전자공학과)
  • Published : 2003.02.01


This paper presents an adaptive PID control scheme for nonlinear system. TSK(Takagi-Sugeno-Kang) fuzzy model is used to estimate the error of control input, and the parameters of PID controller are adapted using the error. The parameters of TSK fuzzy model also adapted to plant. The proposed algorithm allows designing adaptive PID controller which Is adapted to the uncertainty of nonlinear plant and the change of parameters. The usefulness of the proposed algorithm is also certificated by the several simulations.


  1. IEEE Trans. on Syst., Man, and Cybern. v.31 Online learning in adaptive neurocontrol schemes with a sliding mode algorithm Venelinov Topalov, A.;Kaynak, O.
  2. Proc. of the 3rd World Congress on Intelligent Control and Automation v.2 Neural metwork based online self-learning adaptive PID control Wang Beilei;Zhao Lin;Tan Zhenfan
  3. Proc. KES'98 Second International Conference on Knowledge-Based Intelligent Electronic Systems v.2 Adaptive PID control using a genetic algorithm Van Rensburg, P.J.;Shaw, I.S.;Van Wyk, J.D.
  4. Proc. IEEE International Conference on Control Applications Hybrid real time adaptive PID control system for turning Carrukki, F.J.;Haddouche, K.;Rotella, F.
  5. Proc. IEEE International Conference on Fuzzy Systems v.1 Design of TSK fuzzy controller based on TSK fuzzy model using pole placement Kang, G.;Lee W.;Sugeno, M.
  6. Proc. IEEE International Conference on Fuzzy Systems v.1 Stability analysis of TSK fuzzy systems Kang, G.;Lee, W.;Sugeno, M.
  7. システム制御 v.25 no.8 線形離散時間システムの同定手法 中溝高好
  8. Adaptive Control Systems R. Isermann;K. Lachmann;D. Matko