PERFORMANCE BASED LINEAR CONTROL SYSTEM DESIGN BY GENETIC EVOLUTION WITH SIMULATED ANNEALING

Yun Li; Kay Chen Tan; Kim Chwee Ng; David J. Murray-Smith

doi:10.1109/CDC.1995.479066

PERFORMANCE BASED LINEAR CONTROL SYSTEM DESIGN BY GENETIC EVOLUTION WITH SIMULATED ANNEALING

Yun Li
, Kay Chen Tan
, Kim Chwee Ng
, David J. Murray-Smith

Research output: Journal Publications and Reviews › RGC 22 - Publication in policy or professional journal

8 Citations (Scopus)

Abstract

This paper develops a genetic algorithm based design automation method for linear control systems. It unifies the design and avoids the need for pre-selection of control schemes. Using this method, best performance is obtained for controllers described by a transfer function. The genetic algorithm encoded in decimal numerals is fine tuned by incorporating a simulated annealing technique for a more accurate search. It is shown that the design can be applied to both linear and nonlinear plants without manual calculations and can include practical constraints imposed upon the performance requirement. This method also allows the step of linearising nonlinear plants to be bypassed.

Original language	English
Pages (from-to)	731-736
Journal	Proceedings of the IEEE Conference on Decision and Control
Volume	1
DOIs	https://doi.org/10.1109/CDC.1995.479066
Publication status	Published - 1995
Externally published	Yes
Event	34th IEEE Conference on Decision and Control, CDC 1995 - New Orleans, United States Duration: 13 Dec 1995 → 15 Dec 1995

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@article{f26839852efa42fe953579e525213855,

title = "PERFORMANCE BASED LINEAR CONTROL SYSTEM DESIGN BY GENETIC EVOLUTION WITH SIMULATED ANNEALING",

abstract = "This paper develops a genetic algorithm based design automation method for linear control systems. It unifies the design and avoids the need for pre-selection of control schemes. Using this method, best performance is obtained for controllers described by a transfer function. The genetic algorithm encoded in decimal numerals is fine tuned by incorporating a simulated annealing technique for a more accurate search. It is shown that the design can be applied to both linear and nonlinear plants without manual calculations and can include practical constraints imposed upon the performance requirement. This method also allows the step of linearising nonlinear plants to be bypassed.",

author = "Yun Li and Tan, \{Kay Chen\} and Ng, \{Kim Chwee\} and Murray-Smith, \{David J.\}",

year = "1995",

doi = "10.1109/CDC.1995.479066",

language = "English",

volume = "1",

pages = "731--736",

journal = "Proceedings of the IEEE Conference on Decision and Control",

issn = "0191-2216",

publisher = "IEEE",

note = "34th IEEE Conference on Decision and Control, CDC 1995, CDC 1995 ; Conference date: 13-12-1995 Through 15-12-1995",

}

TY - JOUR

T1 - PERFORMANCE BASED LINEAR CONTROL SYSTEM DESIGN BY GENETIC EVOLUTION WITH SIMULATED ANNEALING

AU - Li, Yun

AU - Tan, Kay Chen

AU - Ng, Kim Chwee

AU - Murray-Smith, David J.

PY - 1995

Y1 - 1995

N2 - This paper develops a genetic algorithm based design automation method for linear control systems. It unifies the design and avoids the need for pre-selection of control schemes. Using this method, best performance is obtained for controllers described by a transfer function. The genetic algorithm encoded in decimal numerals is fine tuned by incorporating a simulated annealing technique for a more accurate search. It is shown that the design can be applied to both linear and nonlinear plants without manual calculations and can include practical constraints imposed upon the performance requirement. This method also allows the step of linearising nonlinear plants to be bypassed.

AB - This paper develops a genetic algorithm based design automation method for linear control systems. It unifies the design and avoids the need for pre-selection of control schemes. Using this method, best performance is obtained for controllers described by a transfer function. The genetic algorithm encoded in decimal numerals is fine tuned by incorporating a simulated annealing technique for a more accurate search. It is shown that the design can be applied to both linear and nonlinear plants without manual calculations and can include practical constraints imposed upon the performance requirement. This method also allows the step of linearising nonlinear plants to be bypassed.

UR - https://www.scopus.com/pages/publications/0029532587

UR - https://www.scopus.com/pages/publications/0029532587#tab=impact

U2 - 10.1109/CDC.1995.479066

DO - 10.1109/CDC.1995.479066

M3 - RGC 22 - Publication in policy or professional journal

SN - 0191-2216

VL - 1

SP - 731

EP - 736

JO - Proceedings of the IEEE Conference on Decision and Control

JF - Proceedings of the IEEE Conference on Decision and Control

T2 - 34th IEEE Conference on Decision and Control, CDC 1995

Y2 - 13 December 1995 through 15 December 1995

ER -

PERFORMANCE BASED LINEAR CONTROL SYSTEM DESIGN BY GENETIC EVOLUTION WITH SIMULATED ANNEALING

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