Linear and nonlinear model predictive control using a general purpose optimal control problem solver RIOTS 95

Abstract

In this paper, we introduce the general purpose optimal control problem solver RIOTS_95, Matlab toolbox, as a solver for general linear and nonlinear model predictive control (MPC) problems. This optimization toolbox is designed to solve a wide variety of optimal control problems and therefore constitutes a good candidate as a optimization solver in the MPC framework. The illustrative example of a DC motor is introduced to demonstrate the feasibility of model predictive control using RIOTS_95. Nonlinearities are added to the model to exemplify that RIOTS_95 is also suitable for nonlinear model predictive control (NMPC). The effectiveness and advantages of our RIOTS_95 based MPC are exemplified by comparing its results with those obtained by two readily available MPC tools.