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Self-tuning predictive PID controller using wavelet type-2 fuzzy neural networks

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4 Author(s)
Chi-Huang Lu ; Dept. of Electr. Eng., Hsiuping Univ. of Sci. & Technol., Taichung, Taiwan ; Chi-Ming Liu ; Chin-Chi Cheng ; Jheng-Yu Guo

This paper presents a predictive proportionalintegral-derivative (PID) controller based on wavelet type-2 fuzzy neural network (WT2FNN) for a class of nonlinear systems. The WT2FNN is employed to estimate the nonlinear function of the controlled system and the predictive PID controller is derived via a predictive performance criterion. The stability analysis of the closed-loop control system is presented by the discrete Lyapunov stability theorem. Numerical simulations that the proposed self-tuning predictive PID control law give satisfactory tracking and disturbance rejection performances.

Published in:

Fuzzy Theory and it's Applications (iFUZZY), 2012 International Conference on

Date of Conference:

16-18 Nov. 2012

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