A GA-optimized fuzzy PD+I controller for nonlinear systems

K. S. Tang; Kim F. Man; Guanrong Chen; Sam Kwong

doi:10.1109/IECON.2001.976703

A GA-optimized fuzzy PD+I controller for nonlinear systems

K. S. Tang, Kim F. Man, Guanrong Chen, Sam Kwong

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

14 Citations (Scopus)

Abstract

This paper presents a design and simulation study of a fuzzy PD+I controller optimized via the Multi-Objective Genetic Algorithm (MOGA). The fuzzy PD+I controller preserves the linear structure of the conventional one, but has self-tuned gains. The proportional, integral, and derivative gains are nonlinear functions of their input signals, which have certain adaptive capability in set-point tracking performance. The proposed design is then optimized by using the MOGA. It is tested with a couple of simulated nonlinear systems, which demonstrated that these optimized gains make the fuzzy PD+I controller robust with faster response time and less overshoot than its conventional and non-optimized counterparts. © 2001 IEEE

Original language	English
Title of host publication	IECON'01
Subtitle of host publication	The 27th Annual Conference of the IEEE Industrial Electronics Society
Publisher	IEEE
Pages	718-723
Volume	3
ISBN (Print)	0-7803-7108-9
DOIs	https://doi.org/10.1109/IECON.2001.976703
Publication status	Published - Nov 2001
Event	27th Annual Conference of the IEEE Industrial Electronics Society IECON'2001 - Denver, CO, United States Duration: 29 Nov 2001 → 2 Dec 2001

Conference

Conference	27th Annual Conference of the IEEE Industrial Electronics Society IECON'2001
Place	United States
City	Denver, CO
Period	29/11/01 → 2/12/01

Research Keywords

Fuzzy control
Genetic algorithm
Optimization
PID controller

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title = "A GA-optimized fuzzy PD+I controller for nonlinear systems",

abstract = "This paper presents a design and simulation study of a fuzzy PD+I controller optimized via the Multi-Objective Genetic Algorithm (MOGA). The fuzzy PD+I controller preserves the linear structure of the conventional one, but has self-tuned gains. The proportional, integral, and derivative gains are nonlinear functions of their input signals, which have certain adaptive capability in set-point tracking performance. The proposed design is then optimized by using the MOGA. It is tested with a couple of simulated nonlinear systems, which demonstrated that these optimized gains make the fuzzy PD+I controller robust with faster response time and less overshoot than its conventional and non-optimized counterparts. {\textcopyright} 2001 IEEE",

keywords = "Fuzzy control, Genetic algorithm, Optimization, PID controller",

author = "Tang, {K. S.} and Man, {Kim F.} and Guanrong Chen and Sam Kwong",

year = "2001",

month = nov,

doi = "10.1109/IECON.2001.976703",

language = "English",

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volume = "3",

pages = "718--723",

booktitle = "IECON'01",

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note = "27th Annual Conference of the IEEE Industrial Electronics Society IECON'2001 ; Conference date: 29-11-2001 Through 02-12-2001",

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Tang, KS , Man, KF , Chen, G & Kwong, S 2001, A GA-optimized fuzzy PD+I controller for nonlinear systems. in IECON'01: The 27th Annual Conference of the IEEE Industrial Electronics Society. vol. 3, IEEE, pp. 718-723, 27th Annual Conference of the IEEE Industrial Electronics Society IECON'2001, Denver, CO, United States, 29/11/01. https://doi.org/10.1109/IECON.2001.976703

A GA-optimized fuzzy PD+I controller for nonlinear systems. / Tang, K. S.; Man, Kim F.; Chen, Guanrong et al.
IECON'01: The 27th Annual Conference of the IEEE Industrial Electronics Society. Vol. 3 IEEE, 2001. p. 718-723.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - A GA-optimized fuzzy PD+I controller for nonlinear systems

AU - Tang, K. S.

AU - Man, Kim F.

AU - Chen, Guanrong

AU - Kwong, Sam

PY - 2001/11

Y1 - 2001/11

N2 - This paper presents a design and simulation study of a fuzzy PD+I controller optimized via the Multi-Objective Genetic Algorithm (MOGA). The fuzzy PD+I controller preserves the linear structure of the conventional one, but has self-tuned gains. The proportional, integral, and derivative gains are nonlinear functions of their input signals, which have certain adaptive capability in set-point tracking performance. The proposed design is then optimized by using the MOGA. It is tested with a couple of simulated nonlinear systems, which demonstrated that these optimized gains make the fuzzy PD+I controller robust with faster response time and less overshoot than its conventional and non-optimized counterparts. © 2001 IEEE

AB - This paper presents a design and simulation study of a fuzzy PD+I controller optimized via the Multi-Objective Genetic Algorithm (MOGA). The fuzzy PD+I controller preserves the linear structure of the conventional one, but has self-tuned gains. The proportional, integral, and derivative gains are nonlinear functions of their input signals, which have certain adaptive capability in set-point tracking performance. The proposed design is then optimized by using the MOGA. It is tested with a couple of simulated nonlinear systems, which demonstrated that these optimized gains make the fuzzy PD+I controller robust with faster response time and less overshoot than its conventional and non-optimized counterparts. © 2001 IEEE

KW - Fuzzy control

KW - Genetic algorithm

KW - Optimization

KW - PID controller

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DO - 10.1109/IECON.2001.976703

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 0-7803-7108-9

VL - 3

SP - 718

EP - 723

BT - IECON'01

PB - IEEE

T2 - 27th Annual Conference of the IEEE Industrial Electronics Society IECON'2001

Y2 - 29 November 2001 through 2 December 2001

ER -

A GA-optimized fuzzy PD+I controller for nonlinear systems

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