DocumentCode
2998974
Title
Co-evolutionary learning and hierarchical fuzzy control for the inverted pendulum
Author
Stonier, R.J. ; Young, N.
Author_Institution
Fac. of Informatics & Commun., Central Queensland Univ., Rockhampton, Qld., Australia
Volume
1
fYear
2003
fDate
8-12 Dec. 2003
Firstpage
467
Abstract
In this paper we examine the problem of learning a two layer hierarchical fuzzy controller for the control of the inverted pendulum (with nonlinear dynamics). The fuzzy rules are learned using cooperative co-evolution, whereby two distinct evolutionary populations are used: one defining the first fuzzy layer and the other defining the second fuzzy layer. We compare the results from the co-evolutionary algorithm with the results from a classical evolutionary algorithm.
Keywords
evolutionary computation; fuzzy control; learning (artificial intelligence); nonlinear dynamical systems; pendulums; co-evolutionary algorithm; co-evolutionary learning; cooperative co-evolution; evolutionary algorithm; evolutionary populations; fuzzy layer; fuzzy rules; hierarchical fuzzy control; inverted pendulum; nonlinear dynamics; Australia; Centralized control; Communication system control; Control systems; Force control; Fuzzy control; Fuzzy logic; Fuzzy systems; Informatics; Nonlinear control systems;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2003. CEC '03. The 2003 Congress on
Print_ISBN
0-7803-7804-0
Type
conf
DOI
10.1109/CEC.2003.1299612
Filename
1299612
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