Approaches to explicit Nonlinear Model Predictive Control with reduced partition complexity

Abstract

Recently, several multi-parametric Nonlinear Programming approaches to explicit solution of constrained Nonlinear Model Predictive Control (NMPC) problems have been suggested. The benefits of an explicit solution, in addition to the efficient on-line computations, include also verifiability of the implementation. However, the off-line computational complexity tends to increase rapidly with the number of states. In this paper, several approaches to reduce the off-line computational burden and the partition complexity of the explicit NMPC are proposed and illustrated with two examples.