|Fault Diagnosis and Model Predictive Tolerant Control for Non-Gaussian Stochastic Distribution Control Systems based on T-S Fuzzy Model
Lina Yao and Yanna Zhang
International Journal of Control, Automation, and Systems, vol. 15, no. 6, pp.2921-2929, 2017
Abstract : "A Takagi-Sugeno (T-S) fuzzy model is applied to approximate the nonlinear dynamics of stochastic
distribution control (SDC) systems, in which linear radial basis function (RBF) neural network is adopted to approximate
the output probability density function (PDF) of non-Gaussian SDC systems. Considering the situation
that fault may occur, a fuzzy adaptive fault diagnosis observer is designed to estimate the fault value. Besides,
the Lyapunov stability theory is used to analyse the stability of the observation error system. Based on the fault
estimation information and model predictive control (MPC) algorithm, the active fault tolerant control strategy is
given. Finally, a simulation example is given to verify the effectiveness of the proposed control algorithm."
Keyword : "Fault diagnosis, model predictive control, probability density function, radial basis function, T-S fuzzy model."