THE RBF-ARX MODEL BASED MODELING AND PREDICTIVE CONTROL FOR A CLASS OF NONLINEAR PROCESSES

Abstract This paper considers modeling and control problems of the non-stationary nonlinear processes whose dynamics depends on the working point. A hybrid RBF-ARX model-based predictive control (MPC) strategy without resorting to on-line parameter estimation for this kind of processes is presented. The RBF-ARX model is composed of the RBF networks and a rather general form of ARX model, which is identified off-line, and whose local linearization may be easily obtained. A quickly-convergent estimation method is applied to optimize the RBF-ARX model parameters. The modeling validity and the MPC performance is illustrated by an application to Nitrogen Oxide (NOx) decomposition process in thermal power plants.