Predictive Control of Nonlinear Hybrid Systems Using Generalized Outer Approximation

Abstract

This paper presents an efficient optimization algorithm for mixed integer nonlinear programming (MINLP) problem resulting from multiple partially linearized (MPL) model based control of nonlinear hybrid dynamical system (NHDS). The algorithm uses structural information of the canonical MPL framework and derives comparatively easier quadratic programming (QP) primal problem as well as an MILP master problem for generalized outer approximation (GOA) algorithm, a decomposition based solution strategy for MINLP. Computational efficiency of the algorithm over the branch and bound strategy is demonstrated using a simulated benchmark three-spherical tank system.