IDENTIFICATIONANDCONTROL OF NONLINEAR SYSTEMS USINGMULTIPLE GENERALIZED PREDICTIVE CONTROL BASED NEURO-FUZZYMODEL
Nguyen Tuan Hung · 2014
This thesis presents an approach of identification and control of nonlinear processes by using Multiple Generalized Predictive Control (MGPC) based Neurofuzzy model. Firstly, the dynamic characteristics of a nonlinear system is identified by a Neuro-fuzzy model which is formulated as an alternative form as multiple linear Auto-Regressive Exogenous (ARX) sub models. Subsequently, the MGPC are designed in which each GPC is based on the sub ARX model working cooperatively with other GPCsto control the nonlinearsystem.