Robust optimization for MPC

Authors

B. Houska, M.E. Villanueva

Reference

Houska B., Villanueva M.E. (2019)
Robust Optimization for MPC. In: Raković S., Levine W. (eds)
Handbook of Model Predictive Control. Control Engineering. Birkhäuser.

Abstract

This chapter aims to give a concise overview of numerical methods and algorithms for implementing robust model predictive control (MPC). We introduce the mathematical problem formulation and discuss convex approximations of linear robust MPC as well as numerical methods for nonlinear robust MPC. In particular, we review and compare generic approaches based on min-max dynamic programming and scenario-trees as well as Tube MPC based on set-propagation methods. As this chapter has a strong focus is on numerical methods and their practical implementation, we also review a number of existing software packages for set computations, which can be used as building blocks for the implementation of robust MPC solvers.

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Robust optimization for MPC Chapter

Bibtex

@INBOOK{Houska2019,
author = {Houska, B. and Villanueva, M.E.},
chapter = {Robust optimization for MPC},
pages = {415–447},
booktitle ={Handbook of Model Predictive Control. Control Engineering.},
editors = {Rakovic, S. and Levine, W.},
publisher = {Birkh\"auser}
}