Nonlinear model-predictive control based on quasi-ARX radial-basis function-neural-network

Imam Sutrisno, Mohammad Abu Jami'In, Takayuki Furuzuki, Norman Mariun, Mohd Hamiruce Marhaban

研究成果: Conference contribution

抄録

A nonlinear model-predictive control (NMPC) is demonstrated for nonlinear systems using an improved fuzzy switching law. The proposed moving average filter fuzzy switching law (MAFFSL) is composed of a quasi-ARX radial basis function neural network (RBFNN) prediction model and a fuzzy switching law. An adaptive controller is designed based on a NMPC. a MAFFSL is constructed based on the system switching criterion function which is better than the (ON/OFF) switching law and a RBFNN is used to replace the neural network (NN) in the quasi-ARX black box model which is understood in terms of parameters and is not an absolute black box model, in comparison with NN. The proposed controller performance is verified through numerical simulations to demonstrate the effectiveness of the proposed method.

本文言語English
ホスト出版物のタイトルProceedings - Asia Modelling Symposium 2014: 8th Asia International Conference on Mathematical Modelling and Computer Simulation, AMS 2014
出版社Institute of Electrical and Electronics Engineers Inc.
ページ104-109
ページ数6
ISBN(印刷版)9781479964871
DOI
出版ステータスPublished - 2014 4 2
イベント2014 8th Asia International Conference on Mathematical Modelling and Computer Simulation - Asia Modelling Symposium, AMS 2014 - Kuala Lumpur, Malaysia
継続期間: 2014 9 232014 9 25

Other

Other2014 8th Asia International Conference on Mathematical Modelling and Computer Simulation - Asia Modelling Symposium, AMS 2014
国/地域Malaysia
CityKuala Lumpur
Period14/9/2314/9/25

ASJC Scopus subject areas

  • モデリングとシミュレーション

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