Self-tuning predictive PID controller using wavelet type-2 fuzzy neural networks
Chi‐Huang Lu, Chi-Ming Liu, Chin‐Chi Cheng, Jheng-Yu Guo · 2012
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.