Modelling and Control of Dynamical Systems Using Neural Network – A Review
Abubakar S. Umar1, Muntaqa D. Alhassan2, Kabiru Aminu3, Salahuddeen G. Ahmad4
1Abubakar S. Umar, M.Tech. Students, Department of Electrical Engineering, Jodhpur National University, Jodhpur, Rajasthan, India.
2Muntaqa D. Alhassan, M.Tech. Students, Department of Electrical Engineering, Jodhpur National University, Jodhpur, Rajasthan, India.
3Kabiru Aminu, M.Tech. Students, Department of Electrical Engineering, Jodhpur National University, Jodhpur, Rajasthan, India.
4Salahuddeen G. Ahmad M.Tech. Students, Department of Electrical Engineering, Jodhpur National University, Jodhpur, Rajasthan, India.
Manuscript received on August 18, 2015. | Revised Manuscript received on August 28, 2015. | Manuscript published on September 05, 2015. | PP: 1-12 | Volume-5 Issue-4, September 2015 . | Retrieval Number: D2697095415 /2015©BEIESP
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©The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/
Abstract: This paper presents a brief review on how artificial neural networks can be used in modelling and control of dynamical systems. The paper is broadly categorized into two; the first part is a short overview on artificial neural networks, particularly its generalization property, as applied to systems identification. The subsequent part contains a review onsome of the typical approaches used in the control of dynamical systems using neural networks which includes model predictive control, NARMA-L2 Control and model reference control. Finally, a comparative conclusion was made to distinguish the performances of the different control methods presented in this paper.
Keywords: Neural Network Controllers; Generalization; Systems Modelling; Control Systems.