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: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › 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.

Original language	English
Title of host publication	IECON’01: The 27th Annual Conference of the IEEE Industrial Electronics Society
Publisher	IEEE
Pages	718-723
Number of pages	6
Volume	1
ISBN (Print)	0780371089
DOIs	https://doi.org/10.1109/IECON.2001.976703
Publication status	Published - 2001
Externally published	Yes
Event	27th Annual Conference of the IEEE Industrial Electronics Society, 2001 - Hyatt Regency Tech Center, Denver, United States Duration: 29 Nov 2001 → 2 Dec 2001

Conference

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

Keywords

Fuzzy control
Genetic algorithm
Optimization
PID controller

Access to Document

10.1109/IECON.2001.976703

Cite this

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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.",

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

author = "TANG, \{K. S.\} and MAN, \{Kim F.\} and Guanrong CHEN and Sam KWONG",

year = "2001",

doi = "10.1109/IECON.2001.976703",

language = "English",

isbn = "0780371089",

volume = "1",

pages = "718--723",

booktitle = "IECON{\textquoteright}01: The 27th Annual Conference of the IEEE Industrial Electronics Society",

publisher = "IEEE",

note = "27th Annual Conference of the IEEE Industrial Electronics Society, 2001, IECON'01 ; Conference date: 29-11-2001 Through 02-12-2001",

}

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. 1, IEEE, pp. 718-723, 27th Annual Conference of the IEEE Industrial Electronics Society, 2001, Denver, Colorado, United States, 29/11/01. https://doi.org/10.1109/IECON.2001.976703

TY - GEN

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AU - TANG, K. S.

AU - MAN, Kim F.

AU - CHEN, Guanrong

AU - KWONG, Sam

PY - 2001

Y1 - 2001

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.

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.

KW - Fuzzy control

KW - Genetic algorithm

KW - Optimization

KW - PID controller

UR - https://www.scopus.com/pages/publications/0035690107

U2 - 10.1109/IECON.2001.976703

DO - 10.1109/IECON.2001.976703

M3 - Conference paper (refereed)

SN - 0780371089

VL - 1

SP - 718

EP - 723

BT - IECON’01: The 27th Annual Conference of the IEEE Industrial Electronics Society

PB - IEEE

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

Y2 - 29 November 2001 through 2 December 2001

ER -

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

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