A stable one-step-ahead predictive control of nonlinear systems
type: Item
instance of: scholarly article
title: A stable one-step-ahead predictive control of nonlinear systems
zbMATH Open document ID: 0984.93040
DOI: 10.1016/S0005-1098(99)00173-9
author: Yanyan Li
published in: Automatica
publication date: 2002-05-05T00:00:00Z
review text: A one-step control of a single-input single-output nonlinear analytic plant is considered. The control at the current step is chosen such that the squared difference between the setpoint and output at the next step is minimal. To avoid overshooting, a quadratic penalty function is added to the cost function. Also, to ensure equality between the model and the plant output, an uncertainty parameter is added to the general nonlinear model. Neural networks models, radial basis functions, NARMAX models, and other general nonlinear models can be equally used. It is shown that the unconstrained closed-loop system is asymptotically stable in the large, and asymptotically stable under the input-output constraints. The effectiveness of the proposed control architecture is demonstrated on a recognized benchmark problem and on the continuous-stirred tank reactor.
Mathematics Subject Classification ID: 93B51
Mathematics Subject Classification ID: 93D20
Mathematics Subject Classification ID: 92B20
Mathematics Subject Classification ID: 93C10
zbMATH DE Number: 1437544
zbMATH Keywords: predictive control
zbMATH Keywords: asymptotic stability
zbMATH Keywords: nonlinear plant
zbMATH Keywords: neural networks models
zbMATH Keywords: one-step control
zbMATH Keywords: overshooting
zbMATH Keywords: penalty
zbMATH Keywords: radial basis functions
zbMATH Keywords: NARMAX models
zbMATH Keywords: input-output constraints
reviewed by: Ingmar Randvee
MaRDI profile type: Publication
Wikidata QID: Q56895926
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DBLP publication ID: journals/automatica/KambhampatiMW00
description: scientific article; zbMATH DE number 1437544