MIN-MAX MODEL PREDICTIVE CONTROL AS A QUADRATIC PROGRAM

By David Muñoz de la Peña, Teodoro Alamo, D. Ramírez, Eduardo Fernández Camacho. 2005

51 citations recorded by the source corpus.

Abstract This paper deals with the implementation of min-max model predictive control for constrained linear systems with bounded additive uncertainties and quadratic cost functions. This type of controller has been shown to be a continuous piecewise affine function of the state vector by geometrical methods. However, no algorithm for computing the explicit solution has been given. In this paper, we show that the min-max optimization problem can be expressed as a multi-parametric quadratic program, and so, the explicit form of the controller may be determined by standard multi-parametric techniques.

Subfields: Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/9acbe603c349aa6f910976beb1deaf3a1e17cb88

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In Control and Systems Engineering

1. Alessandro Alessio
2. Alberto Bemporad
3. Francesco Borrelli
4. Manfred Morari
5. Eric C. Kerrigan

Citations in the corpus

• A survey on explicit model predictive control (2009, methodology): “In [56] the problem was reformulated as a single mpQP.”