Genetic Algorithm with Two Iterative Searching Stages for Fuzzy Controller Design  

Oleh:

Juang, Chia Feng

Jenis: Article from Article
Dalam koleksi: Final Program and Book of Abstracts: The 4th Asian Control Conference, September 25-27, 2002 (Sep. 2002), page 353-357.
Topik: Genetic Algorithm; Two Iterative; Fuzzy Controller Design; TSGA-F
Fulltext: AC021233.PDF (231.58KB)

Isi artikel

This paper proposes a Two??Stage Genetic Algorithm for Feedforward fuzzy controller design
TSGA??F The objective of the proposed TSGA-F is to increase the fuzzy controller design eectiveness and eficiency TSGA-F operates in two distant stages The rst stage the local??mapping search stage searches through the well??performed local rules In this stage each in dividual represents only a fuzzy rule One popular tion is created for searching spatial fuzzy rules To avoid population convergence on a single rule a pop ulation renewal technique is applied The other stage is a global??mapping search stage Each individual in this stage represents a fuzzy network as opposed to a single rule The objective is to determine which local rules designed in the local??mapping search stage should be combined together to achieve a good fuzzy network that best covers the whole working region To demon strate the performance of TSGA-F TSGA-F is applied to cart??pole balancing control problem

Opini Anda

Klik untuk menuliskan opini Anda tentang koleksi ini!

Kembali