Learning control via neuro-tabu-fuzzy controller

  • Authors:

  • Sarawut Sujitjorn;Sudarat Khwan-on

  • Affiliations:

  • School of Electrical Engineering, Suranaree University of Technology, Nakhon Ratchasima, Thailand;School of Electrical Engineering, Suranaree University of Technology, Nakhon Ratchasima, Thailand

  • Venue:
  • KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
  • Year:
  • 2006

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Abstract

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.