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Adaptive fuzzy generalized predictive control based on Discrete-Time T-S fuzzy model

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3 Author(s)
Mendes, J. ; Dept. of Electr. & Comput. Eng. (DEEC-UC), Univ. of Coimbra, Coimbra, Portugal ; Araújo, R. ; Souza, F.

The paper presents an adaptive fuzzy predictive control based on discrete-time Takagi-Sugeno (T-S) fuzzy model. The proposed controller is based on Generalized predictive control (GPC) algorithm, and a discrete-time T-S fuzzy model is employed to approximate the unknown nonlinear process. To provide a better accuracy in identification of unknown parameters of the model, it is proposed an on-line adaptive law which ensures that the tracking error remains bounded. The stability of closed-loop control system is proved/studied via the Lyapunov stability theory. To validate the theoretical developments and to demonstrate the performance of the proposed control is simulated as nonlinear system a laboratory-scale liquid-level process. The simulation results show that the proposed method has a good performance and disturbance rejection capacity in industrial process.

Published in:

Emerging Technologies and Factory Automation (ETFA), 2010 IEEE Conference on

Date of Conference:

13-16 Sept. 2010