Online self-evolving fuzzy controller with global learning capabilities

被引：12

作者：

Cara A.B. ^{[1
]}

Pomares H. ^{[1
]}

Rojas I. ^{[1
]}

Lendek Z. ^{[2
]}

Babuška R. ^{[2
]}

机构：

[1] Department of Computer Architecture and Computer Technology, University of Granada, 18071 Granada, C/Periodista Saucedo Aranda s/n

[2] Delft Center for Systems and Control, Delft University of Technology, 2628 CD Delft

来源：

Evolving Systems | 2010年 / 1卷 / 04期

关键词：

Adaptive control; Adaptive fuzzy control; Evolutionary methodology; Evolving fuzzy system;

D O I：

10.1007/s12530-010-9016-8

中图分类号：

学科分类号：

摘要：

This paper presents an online self-evolving fuzzy controller with global learning capabilities. Starting from very simple or even empty configurations, the controller learns from its own actions while controlling the plant. It applies learning techniques based on the input/ output data collected during normal operation to modify online the fuzzy controller's structure and parameters. The controller does not need any information about the differential equations that govern the plant, nor any offline training. It consists of two main blocks: a parameter learning block that learns proper values for the rule consequents applying a local and a global strategy, and a selfevolving block that modifies the controller's structure online. The modification of the topology is based on the analysis of the error surface and the determination of the input variables which are most responsible for the error. Simulation and experimental results are presented to show the controller's capabilities. © Springer-Verlag 2010.

引用

页码：225 / 239

页数：14

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