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Self-organizing approximation-based control for higher order systems

Authors :
Yuanyuan Zhao
Jay A. Farrell
Source :
IEEE transactions on neural networks. 18(4)
Publication Year :
2007

Abstract

Adaptive approximation-based control typically uses approximators with a predefined set of basis functions. Recently, spatially dependent methods have defined self-organizing approximators where new locally supported basis elements were incorporated when existing basis elements were insufficiently excited. In this paper, performance-dependent self-organizing approximators will be defined. The designer specifies a positive tracking error criteria. The self-organizing approximation-based controller then monitors the tracking performance and adds basis elements only as needed to achieve the tracking specification. The method of this paper is applicable to general nth-order input-state feedback linearizable systems. This paper includes a complete stability analysis and a detailed simulation example.

Details

ISSN :
10459227
Volume :
18
Issue :
4
Database :
OpenAIRE
Journal :
IEEE transactions on neural networks
Accession number :
edsair.doi.dedup.....0e18b444b4515cf4953774d8b1c4295e