Using interpolation to improve efficiency of multiparametric predictive control

Multi-parameteric quadratic programming (MPQP) gives a full offline solution to a time-varying quadratic programming (QP) problem arising during constrained predictive control. However, coding and implementation of this solution may be more burdensome than simply solving the original QP. This paper shows how interpolation can be used in conjunction with MPQP to achieve a large decrease in both the online computation and data storage requirements with negligible deterioration of performance. Extensive simulation results are given to back this claim and contrast the TWO proposed interpolation schemes.