Combined Gradient and Newton Projection Quadratic Programming Solver for MPC

Abstract

AbstractThe objective of this paper is to present an effective on-line solver for simple constrained quadratic programming (QP) which arises in linear model predictive control (MPC) framework. In MPC, the QP is solved at each sampling time, thus a fast solver must be used for short sampling times in real-time applications. The multi-parametric quadratic programming (mp-QP) approach (explicit solution) is impossible to use for larger systems due to the memory limitation. On the other hand, the presented approach is well suitable even for medium scale systems with short sampling time, since it is based on combination of gradient and Newton projection algorithm which is very close to optimum in a very few iterations and the computation of the Newton step is not involved at each iteration.