ADAPTIVE MINIMUM VARIANCE CONTROL FOR STOCHASTIC FUZZY T-SARMAX MODEL

摘要

Adaptive minimum variance control for stochastic T-S fuzzy ARMAX model is addressed in this study. From the fuzzy ARMAX model, a fuzzy one-step ahead prediction model is first Introduced. A stochastic gradient algorithm is then proposed to Identify the parameters of the related one-step-ahcad predictor. Under the direct adaptive control scheme, minimum variance control is applied to find the control law to make the output track a desired reference signal. Stability and performance of the adaptive stochastic fuzzy control system are rigorously derived. Simulation study is also made to verify the developed results.