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 ProceedingsConference paper (refereed)Researchpeer-review

14 Citations (Scopus)


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 languageEnglish
Title of host publicationIECON Proceedings (Industrial Electronics Conference)
Publication statusPublished - 2001
Externally publishedYes


  • Fuzzy control
  • Genetic algorithm
  • Optimization
  • PID controller


Dive into the research topics of 'A GA-optimized fuzzy PD+I controller for nonlinear systems'. Together they form a unique fingerprint.

Cite this