Model reference adaptive control for constrained linear systems

Pham Anh Tu; Kenko Uchida

doi:10.2316/P.2011.718-084

Model reference adaptive control for constrained linear systems

Pham Anh Tu, Kenko Uchida

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The presence of state and control constraints in physi cal systems may lead to performance deterioration and instability if not adequately accounted for in controller design processes. Therefore, a procedure of state and control constraint fulfillment for uncertain linear systems, which firstly require an adaptive controller, is proposed. Model Reference Adaptive Control (MRAC) Method is selected to design the controller, and Lyapunov stability theory is used to obtained adaptive laws. To solve the constraint fulfillment problem, a concept of maximal output admissible set [8], [11] is utilized to predict safe operation of the plant. Constraint fulfill ment procedure is described as polynomial optimization problems, and a numerical design example is carried out to support the arguments.

Original language	English
Title of host publication	Proceedings of the IASTED International Conference on Modelling, Identification and Control
Pages	294-299
Number of pages	6
DOIs	https://doi.org/10.2316/P.2011.718-084
Publication status	Published - 2011
Externally published	Yes
Event	31st IASTED International Conference on Modelling, Identification, and Control, MIC 2011 - Innsbruck Duration: 2011 Feb 14 → 2011 Feb 16

Other

Other	31st IASTED International Conference on Modelling, Identification, and Control, MIC 2011
City	Innsbruck
Period	11/2/14 → 11/2/16

Keywords

Lyapunov stabilty
Maximal output admissible set
Model reference adaptive control
State and control constraints

ASJC Scopus subject areas

Computer Science Applications
Software
Modelling and Simulation

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10.2316/P.2011.718-084

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title = "Model reference adaptive control for constrained linear systems",

abstract = "The presence of state and control constraints in physi cal systems may lead to performance deterioration and instability if not adequately accounted for in controller design processes. Therefore, a procedure of state and control constraint fulfillment for uncertain linear systems, which firstly require an adaptive controller, is proposed. Model Reference Adaptive Control (MRAC) Method is selected to design the controller, and Lyapunov stability theory is used to obtained adaptive laws. To solve the constraint fulfillment problem, a concept of maximal output admissible set [8], [11] is utilized to predict safe operation of the plant. Constraint fulfill ment procedure is described as polynomial optimization problems, and a numerical design example is carried out to support the arguments.",

keywords = "Lyapunov stabilty, Maximal output admissible set, Model reference adaptive control, State and control constraints",

author = "Tu, {Pham Anh} and Kenko Uchida",

year = "2011",

doi = "10.2316/P.2011.718-084",

language = "English",

isbn = "9780889868632",

pages = "294--299",

booktitle = "Proceedings of the IASTED International Conference on Modelling, Identification and Control",

note = "31st IASTED International Conference on Modelling, Identification, and Control, MIC 2011 ; Conference date: 14-02-2011 Through 16-02-2011",

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AU - Tu, Pham Anh

AU - Uchida, Kenko

PY - 2011

Y1 - 2011

N2 - The presence of state and control constraints in physi cal systems may lead to performance deterioration and instability if not adequately accounted for in controller design processes. Therefore, a procedure of state and control constraint fulfillment for uncertain linear systems, which firstly require an adaptive controller, is proposed. Model Reference Adaptive Control (MRAC) Method is selected to design the controller, and Lyapunov stability theory is used to obtained adaptive laws. To solve the constraint fulfillment problem, a concept of maximal output admissible set [8], [11] is utilized to predict safe operation of the plant. Constraint fulfill ment procedure is described as polynomial optimization problems, and a numerical design example is carried out to support the arguments.

AB - The presence of state and control constraints in physi cal systems may lead to performance deterioration and instability if not adequately accounted for in controller design processes. Therefore, a procedure of state and control constraint fulfillment for uncertain linear systems, which firstly require an adaptive controller, is proposed. Model Reference Adaptive Control (MRAC) Method is selected to design the controller, and Lyapunov stability theory is used to obtained adaptive laws. To solve the constraint fulfillment problem, a concept of maximal output admissible set [8], [11] is utilized to predict safe operation of the plant. Constraint fulfill ment procedure is described as polynomial optimization problems, and a numerical design example is carried out to support the arguments.

KW - Lyapunov stabilty

KW - Maximal output admissible set

KW - Model reference adaptive control

KW - State and control constraints

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DO - 10.2316/P.2011.718-084

M3 - Conference contribution

AN - SCOPUS:79958170843

SN - 9780889868632

SP - 294

EP - 299

BT - Proceedings of the IASTED International Conference on Modelling, Identification and Control

T2 - 31st IASTED International Conference on Modelling, Identification, and Control, MIC 2011

Y2 - 14 February 2011 through 16 February 2011

ER -

Model reference adaptive control for constrained linear systems

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Keywords

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