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

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

14 Scopus Citations
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Detail(s)

Original languageEnglish
Title of host publicationIECON Proceedings (Industrial Electronics Conference)
Pages718-723
Volume3
Publication statusPublished - 2001

Publication series

Name
Volume3

Conference

Title27th Annual Conference of the IEEE Industrial Electronics Society IECON'2001
PlaceUnited States
CityDenver, CO
Period29 November - 2 December 2001

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.

Research Area(s)

  • Fuzzy control, Genetic algorithm, Optimization, PID controller

Citation Format(s)

A GA-optimized fuzzy PD+I controller for nonlinear systems. / Tang, K. S.; Man, Kim F.; Chen, Guanrong et al.
IECON Proceedings (Industrial Electronics Conference). Vol. 3 2001. p. 718-723.

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