A chaos search immune algorithm with its application to neuro-fuzzy controller design
X.Q. Zuo and
Y.S. Fan
Chaos, Solitons & Fractals, 2006, vol. 30, issue 1, 94-109
Abstract:
In this paper, a chaos search immune algorithm (CSIA) is proposed by integrating the chaos optimization algorithm and the clonal selection algorithm. First, optimization variables are expressed by chaotic variables through solution space transformation. Then, taking advantages of the ergodic and stochastic properties of chaotic variables, a chaos search is performed in the neighbourhoods of high affinity antibodies to exploit local solution space, and the motion of the chaotic variables in their ergodic space is used to explore the whole solution space. Furthermore, a generalized radial basis function neuro-fuzzy controller (GRBFNFC) is constructed and designed automatically by the proposed CSIA. Application of the CSIA-designed GRBFNFC to real-time control of an inverted pendulum system is discussed. Experimental results demonstrate that the designed GRBFNFC has very satisfactory performance.
Date: 2006
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960077905007733
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:30:y:2006:i:1:p:94-109
DOI: 10.1016/j.chaos.2005.08.126
Access Statistics for this article
Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros
More articles in Chaos, Solitons & Fractals from Elsevier
Bibliographic data for series maintained by Thayer, Thomas R. ().