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Title: | Modified Elman Spike Neural Network for Identification and Control of Dynamic System |
Authors: | Aljamali, NAS Al-Raweshidy, HS |
Keywords: | identification;dynamic system;modified Elman spike neural network;spike neural network |
Issue Date: | 30-Mar-2020 |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Citation: | Aljamali, N.A.S. and Al-Raweshidy, H.S. (2020) 'Modified Elman Spike Neural Network for Identification and Control of Dynamic System', IEEE Access, 8, pp. 61246 - 61254. doi: 10.1109/access.2020.2984311. |
Abstract: | The utilization of conventional modeling strategies in the identification and control of a nonlinear dynamical system suffers from some weaknesses. These include absence of precise, conventional knowledge about the system, a high degree of uncertainty, strongly nonlinear and time-varying behavior. In this paper, a modified training algorithm for the identification and control of a nonlinear system using a soft-computing approach is proposed. Specifically, a modified structure of the Elman neural network with spike neural networks is proposed. This modified structure includes self-feedback, which provides a dynamic trace of the training algorithm. This self-feedback has weights, which can be trained during the training process. The simulation results show that the modified structure with the modified training algorithm is capable of the identification and control of a dynamic system in a more robust manor than when solely applying the other types of neural networks by 70% in terms of minimization of the percentage of error. |
URI: | https://bura.brunel.ac.uk/handle/2438/20601 |
DOI: | https://doi.org/10.1109/ACCESS.2020.2984311 |
Other Identifiers: | ORCiD: Nadia Adnan Shiltagh Al-Jamali https://orcid.org/0000-0002-0377-1519 ORCiD: Hamed S. Al-Raweshidy https://orcid.org/0000-0002-3702-8192 |
Appears in Collections: | Dept of Electronic and Electrical Engineering Research Papers |
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FullText.pdf | © Copyright The Authors 2020. Published by Institute of Electrical and Electronics Engineers (IEEE). This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ . | 7.96 MB | Adobe PDF | View/Open |
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