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

K. S. TANG; Kim F. MAN; Guanrong CHEN; Sam KWONG

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 Proceedings (Industrial Electronics Conference)
Pages	718-723
Publication status	Published - 2001
Externally published	Yes

Keywords

Fuzzy control
Genetic algorithm
Optimization
PID controller

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",

language = "English",

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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 - http://www.scopus.com/inward/record.url?scp=0035690107&partnerID=8YFLogxK

M3 - Conference paper (refereed)

SP - 718

EP - 723

BT - IECON Proceedings (Industrial Electronics Conference)

ER -

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

Abstract

Keywords

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