Adaptive fuzzy T-S control based on local linear integral controllers
Applications of Large Scale Industrial Systems, Volume # 1 | Part# 1
Ruiyun Qi; Mietek A. Brdys
Digital Object Identifier (DOI)
indirect adaptive control,fuzzy control,Takagi-Sugeno (T-S) models,local linear controller
A Takagi-Sugeno (T-S) fuzzy model based adaptive control algorithm for a class of multiple-input-multiple-output (MIMO) nonlinear uncertain systems is presented in this paper. The T-S model consists of a set of linear local models which can be considered as the linearization models of the nonlinear systems in different operating regions. Local integral controllers are designed based on local linear fuzzy models and combined to generate the overall controller using fuzzy weighted integration. The consequent parameters of the T-S model can be updated online in the presence of external disturbances and parameter perturbations. Stability analysis shows all the signals in the closed-loop system are bounded. Simulation results on tracking control of a two-link robot manipulator are given to illustrate the effectiveness of the proposed method.
 B. Kosko (1994), "Fuzzy systems as universal approximtors," IEEE Trans. Computers, vol. 43, pp. 1329-1333.  R. Rovatti (1998), "Fuzzy piecewise multilinear and piecewise linear systems as universal approximators in Sobolev norm," IEEE Trans. Fuzzy Syst., vol. 6, pp. 235-249.  M. A. Brdys and G. J. Kulawski (1999), "Dynamic neural controllers for indunction motor," IEEE Trans. Neural Networks, vol. 10, no. 2, pp. 340- 355.  G. J. Kulawski and M. A. Brdys (2000), "Stable adaptive control with recurrent networks," Automatica, vol. 36, pp. 5-22.  Z.-P. Jiang and Y. Wang (2001), "Input-to-state stability for discrete-time nonlinear systems," Automatica, vol. 37, pp. 857-869.  Y. Jin (2003), Advanced fuzzy systems design and applications. Heidelberg, NY: Physica-Verl.  G. Tao (2003), Adaptive design and analysis. Hoboken, NJ: John Wiley & Sons, Inc.  Q. Sun, R. Li and P. Zhang (2003), "Stable and optimal adaptive fuzzy control of complex systems using fuzzy dynamic model," Fuzz. Sets and Syst., vol 133, pp. 1-17.  C.-W. Park and Y.-W. Cho (2004), "T-S Model Based Indirect Adaptive Fuzzy Control Using Online Parameter Estimation," IEEE Trans. On Syst. Man. And Cyber., Part B, Vol. 34, pp. 2293-2302.  N. Li, S.-Y. Li and Y.-G. Xi (2004), "Multi-model predictive control based on the Takagi-Sugeno fuzzy models: a case study," IEEE Trans. On Syst. Man. And Cyber., part B, vol. 34, No. 1, pp. 788-795.  R. Qi and M.A. Brdys (2005), "Adaptive fuzzy modelling and control for discrete-time nonlinear uncertain systems," in Proc. Of the 2005 American Control Conference, pp. 1108- 1113.