Sutrisno, Imam and Abu Jami’in, Mohammad and Hu, Jinglu (2013) Implementation of Lyapunov Learning Algorithm for Fuzzy Switching Adaptive Controller Modeled Under Quasi-ARX Neural Network. 2nd International Conference on Measurement, Information and Control. ISSN 978-1-4799-1390-9
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Abstract
This paper presents a fuzzy adaptive controller applied to a non linear system modeled under a Quasi-linear ARX Neural Network, with stability proof by using the Lyapunov approach. This work exploits the new idea to use Lyapunov function to train multi-input multi-output neural network on the core-part sub-model. The proposed controller is designed between a linear controller and non linear controller based on the characteristic of fuzzy switching algorithm. The improving performances of the Lyapunov learning algorithm are stable in the learning process, fast convergence of error, and able to increase the accuracy of the controller. Index Terms—Lyapunov Learning Algorithm, Fuzzy Switching Adaptive Controller, Quasi-ARX Neural Network.
Item Type: | Article |
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Subjects: | T Technology > T Technology (General) T Technology > TL Motor vehicles. Aeronautics. Astronautics |
Divisions: | Jurusan Teknik Kelistrikan Kapal > D3 Teknik Kelistrikan Kapal |
Depositing User: | Unnamed user with email repository@ppns.ac.id |
Date Deposited: | 22 Jan 2019 06:51 |
Last Modified: | 28 Jan 2019 03:00 |
URI: | http://repository.ppns.ac.id/id/eprint/1401 |
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