Design of Explicit Model Predictive Controllers Based on Orthogonal Partition of the Parameter Space: Methods and A Software Tool

Abstract

This paper reviews the approaches to explicit approximate Nonlinear Model Predictive Control (NMPC), based on orthogonal partition of the parameter space. They are classified with respect to the type of control problem, the type of model describing the nonlinear system, the presence of uncertainty, the type of control input, and the type of the approximating control function. A software tool for design of explicit NMPC by applying the described approaches is presented. It is used to design an explicit NMPC controller for a continuous stirred tank reactor.