Explicit-Model Predictive Control: A simulation based scalability study

Abstract

The main impediment in the applicability of explicit model predictive control (e-MPC) is that the number of regions in the parametric space increases dramatically with an increase in the dimension of the parameter and decision spaces as well as with an increase in the number of constraints. This work explores the scalability issues by simulation in which e-MPC is used for control of quadruple tank system. Explicit-MPC problem formulation from a standard MPC (for finite and infinite prediction horizon) using multi parametric quadratic programming (mp-QP) is presented. The results confirm that while the number of critical regions increases exponentially with the control horizon, the online calculations are computationally inexpensive.