Explicit Approximate Approach to Feedback Min-Max Model Predictive Control of Constrained Nonlinear Systems

Abstract

This paper presents an approximate multi-parametric nonlinear programming (mp-NLP) approach to explicit solution of feedback min-max model predictive control problems for constrained nonlinear systems in the presence of bounded disturbances. It is based on an orthogonal search tree structure of the state space partition and consists in constructing a feasible piecewise nonlinear (PWNL) approximation to the optimal sequence of feedback control policies. The proposed approach is applied to design an explicit feedback min-max nonlinear model predictive controller for a cart moving on a plane and attached to the wall via a spring