On the terminal region of model predictive control for non-linear system with input/state constraints: International Journal of Adaptive Control and Signal Processing

W.-H. Chen; J. O'Reilly; D.J. Ballance

doi:10.1002/acs.731

On the terminal region of model predictive control for non-linear system with input/state constraints: International Journal of Adaptive Control and Signal Processing

W.-H. Chen, J. O'Reilly, D.J. Ballance

Biological Sciences

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56 Scopus citations

Abstract

This paper addresses the terminal region of model-based predictive control (MFC) for non-linear systems with control input and state constraints. Based on a stability condition of non-linear MFC, a method to determine the terminal weighting term in the performance index and the terminal stabilizing control law to enlarge the terminal region and thus the domain of attraction of the non-linear MFC is proposed. An LMI based optimization approach is developed to choose the terminal weighting item and fictitious terminal stabilizing control law so as to enlarge the terminal region of the non-linear MFC method. The proposed method is illustrated by a numerical example and compares favourably with existing results.

Original language	British English
Pages (from-to)	195-207
Number of pages	13
Journal	Int J Adapt Control Signal Process
Volume	17
Issue number	3
DOIs	https://doi.org/10.1002/acs.731
State	Published - 2003

Keywords

LMI's
Model-based predictive control
Non-linear systems
Optimization
Stability
Constraint theory
Mathematical models
Matrix algebra
Predictive control systems
System stability
Linear matrix inequalities
State constraints
Nonlinear control systems

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10.1002/acs.731

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Cite this

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title = "On the terminal region of model predictive control for non-linear system with input/state constraints: International Journal of Adaptive Control and Signal Processing",

abstract = "This paper addresses the terminal region of model-based predictive control (MFC) for non-linear systems with control input and state constraints. Based on a stability condition of non-linear MFC, a method to determine the terminal weighting term in the performance index and the terminal stabilizing control law to enlarge the terminal region and thus the domain of attraction of the non-linear MFC is proposed. An LMI based optimization approach is developed to choose the terminal weighting item and fictitious terminal stabilizing control law so as to enlarge the terminal region of the non-linear MFC method. The proposed method is illustrated by a numerical example and compares favourably with existing results.",

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T2 - International Journal of Adaptive Control and Signal Processing

AU - Chen, W.-H.

AU - O'Reilly, J.

AU - Ballance, D.J.

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PY - 2003

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AB - This paper addresses the terminal region of model-based predictive control (MFC) for non-linear systems with control input and state constraints. Based on a stability condition of non-linear MFC, a method to determine the terminal weighting term in the performance index and the terminal stabilizing control law to enlarge the terminal region and thus the domain of attraction of the non-linear MFC is proposed. An LMI based optimization approach is developed to choose the terminal weighting item and fictitious terminal stabilizing control law so as to enlarge the terminal region of the non-linear MFC method. The proposed method is illustrated by a numerical example and compares favourably with existing results.

KW - LMI's

KW - Model-based predictive control

KW - Non-linear systems

KW - Optimization

KW - Stability

KW - Constraint theory

KW - Mathematical models

KW - Matrix algebra

KW - Predictive control systems

KW - System stability

KW - Linear matrix inequalities

KW - State constraints

KW - Nonlinear control systems

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DO - 10.1002/acs.731

M3 - Article

SN - 0890-6327

VL - 17

SP - 195

EP - 207

JO - Int J Adapt Control Signal Process

JF - Int J Adapt Control Signal Process

IS - 3

ER -

On the terminal region of model predictive control for non-linear system with input/state constraints: International Journal of Adaptive Control and Signal Processing

Abstract

Keywords

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