Abstract
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.
Original language | English |
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Title of host publication | Proceedings - Asia Modelling Symposium 2014: 8th Asia International Conference on Mathematical Modelling and Computer Simulation, AMS 2014 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 104-109 |
Number of pages | 6 |
ISBN (Print) | 9781479964871 |
DOIs | |
Publication status | Published - 2014 Apr 2 |
Event | 2014 8th Asia International Conference on Mathematical Modelling and Computer Simulation - Asia Modelling Symposium, AMS 2014 - Kuala Lumpur, Malaysia Duration: 2014 Sept 23 → 2014 Sept 25 |
Other
Other | 2014 8th Asia International Conference on Mathematical Modelling and Computer Simulation - Asia Modelling Symposium, AMS 2014 |
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Country/Territory | Malaysia |
City | Kuala Lumpur |
Period | 14/9/23 → 14/9/25 |
Keywords
- moving average filter fuzzy switching law
- nonlinear model-predictive control
- quasi-ARX radial basis function neural network
ASJC Scopus subject areas
- Modelling and Simulation