Quasi-min-max MPC algorithms for LPV systems
type: Item
instance of: scholarly article
title: Quasi-min-max MPC algorithms for LPV systems
zbMATH Open document ID: 0981.93027
DOI: 10.1016/S0005-1098(99)00176-4
author: Yaohui Lu
author: Yaman Arkun
published in: Automatica
publication date: 2002-03-10T00:00:00Z
review text: An infinite horizon ``quasi min-max'' model predictive control (MPC) algorithm is developed. The plant is given by a polytopic linear discrete-time parameter varying (LPV) model. No mismatch exists between the model and the plant. The parameters and the state are assumed to be available in real time. The on-line optimization problems are solved by semi-definite programming involving linear matrix inequalities. At each sampling instance, the optimal control is calculated by minimizing the upper bound on the ``quasi-worst-case'' value of an infinite horizon quadratic objective function subject to constraints on inputs and outputs. It is shown that a receding horizon implementation of feasible solutions guarantees closed-loop stability. Numerical examples demonstrate the decreased conservatism, improved feasibility, and superior performance of the proposed MPC-LPV algorithm.
Mathematics Subject Classification ID: 93B51
zbMATH DE Number: 1437547
zbMATH Keywords: time-varying systems
zbMATH Keywords: polytopic linear discrete-time parameter varying model
zbMATH Keywords: model predictive control
zbMATH Keywords: real time
zbMATH Keywords: on-line optimization
zbMATH Keywords: semi-definite programming
zbMATH Keywords: linear matrix inequalities
zbMATH Keywords: receding horizon
zbMATH Keywords: stability
zbMATH Keywords: feasibility
reviewed by: Ingmar Randvee
MaRDI profile type: Publication
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description: scientific article; zbMATH DE number 1437547