Learning Control Via Neuro-Tabu-Fuzzy Controller

The paper presents a novel search algorithm named adaptive tabu search (ATS). The algorithm has been applied to enhance the learning process of neural networks. The paper presents a new neuro-tabu-fuzzy (NTF) control structure to demonstrate the capability of the ATS algorithm. The algorithm is gene...

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Bibliographic Details
Published inKnowledge-Based Intelligent Information and Engineering Systems Vol. 4251; pp. 833 - 840
Main Authors Sujitjorn, Sarawut, Khwan-on, Sudarat
Format Book Chapter Conference Proceeding
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2006
Springer
SeriesLecture Notes in Computer Science
Subjects
Applied sciences
Artificial intelligence
Computer science; control theory; systems
Exact sciences and technology
Fuzzy Controller
Information systems. Data bases
Inverted Pendulum
Learn Control
Memory organisation. Data processing
Software
Stabilization Limit
Stabilization Time
Knowledge engineering
Fuzzy logic
Inversed pendulum
Fuzzy control
Adaptive algorithm
Tabu search
Learning (artificial intelligence)
Neural network
Artificial intelligence
Search algorithm
Intelligent control
Mathematical programming
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Summary:The paper presents a novel search algorithm named adaptive tabu search (ATS). The algorithm has been applied to enhance the learning process of neural networks. The paper presents a new neuro-tabu-fuzzy (NTF) control structure to demonstrate the capability of the ATS algorithm. The algorithm is general and can be applied to various problems including machine learning, optimization, etc. Our proposed algorithm and controller nicely stabilize the single- and double-inverted pendulum systems.
ISBN:3540465359
9783540465355
ISSN:0302-9743
1611-3349
DOI:10.1007/11892960_100