TY - GEN
T1 - Type-2 fuzzy PD controller tuning using quantum-inspired evolutionary algorithm
AU - Cho, Seung Yoon
AU - Lee, Joon Woo
AU - Lee, Ju Jang
PY - 2011
Y1 - 2011
N2 - Fuzzy Logic Controller (FLC) is used widely since it can control non-linear system which are hard to be solved by conventional control method. The design of fuzzy logic controller (FLC), however, has some difficulties such as formation of the fuzzy rules, tuning of the scale factor and the rule explosion. The decision of fuzzy rules are not easy since the fuzzy rule is formed by the expert's experience. Finding suitable scale factor is difficult as conventional PID ones since it takes long time. As input increase, fuzzy rule increase exponentially. To overcome these problems, the information integration is used for preventing the rule explosion and fixed the fuzzy rules and scaling factor is used. we proposed Fuzzy PD Controller Tuning method by using Quantum-inspired Evolution algorithm (QEA). This proposed method also was demonstrated by control of double inverted pendulum.
AB - Fuzzy Logic Controller (FLC) is used widely since it can control non-linear system which are hard to be solved by conventional control method. The design of fuzzy logic controller (FLC), however, has some difficulties such as formation of the fuzzy rules, tuning of the scale factor and the rule explosion. The decision of fuzzy rules are not easy since the fuzzy rule is formed by the expert's experience. Finding suitable scale factor is difficult as conventional PID ones since it takes long time. As input increase, fuzzy rule increase exponentially. To overcome these problems, the information integration is used for preventing the rule explosion and fixed the fuzzy rules and scaling factor is used. we proposed Fuzzy PD Controller Tuning method by using Quantum-inspired Evolution algorithm (QEA). This proposed method also was demonstrated by control of double inverted pendulum.
KW - Information integration
KW - Quantum Inspired Evolution Algorithm (QEA)
KW - scale fator tuning
KW - Type-2 fuzzy logic controller
UR - http://www.scopus.com/inward/record.url?scp=80055062919&partnerID=8YFLogxK
U2 - 10.1109/DEST.2011.5936641
DO - 10.1109/DEST.2011.5936641
M3 - Conference contribution
AN - SCOPUS:80055062919
SN - 9781457708725
T3 - IEEE International Conference on Digital Ecosystems and Technologies
SP - 292
EP - 296
BT - Proceedings of the 5th IEEE International Conference on Digital Ecosystems and Technologies, DEST 2011
T2 - 5th IEEE International Conference on Digital Ecosystems and Technologies, DEST 2011
Y2 - 31 May 2011 through 3 June 2011
ER -