Study on Self-Adaptive Control System - View of Internal Adaptation
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
www.ijsr.net | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064

M.Tech / M.E / PhD Thesis | Control Systems Engineering | Sudan | Volume 5 Issue 2, February 2016

Study on Self-Adaptive Control System - View of Internal Adaptation

Hussam Mohammed-ElHassan Ibrahim Dafaalla, Dalia Mahmoud

In world's manufacturing industry rapid development, using of the control system has become vital issue and more in demand for many reasons such like to keep up with market rising demand of goods and competition of its' quality. However, with the complicating of the production system, the traditional control system has not been able to meet the needs of the current industry. Bringing the genetic algorithm of the neural network into the control system can effectively solve this problem. In this paper we discuss the neural network, genetic algorithm principle, operation procedures and the characteristics, then, analyzes the principle and lack of conventional PID controller, finally, effectively combines genetic algorithm and controller together, forming a closed loop, strengthening the control of parameters, and giving a code description of the genetic algorithm. This paper plays a certain positive role for industrial engineers and programmers.

Keywords: Neural Network, Genetic Algorithm, Self-Adaptive Control

Edition: Volume 5 Issue 2, February 2016

Pages: 719 - 722

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How to Cite this Article?

Hussam Mohammed-ElHassan Ibrahim Dafaalla, Dalia Mahmoud, "Study on Self-Adaptive Control System - View of Internal Adaptation", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=NOV152335, Volume 5 Issue 2, February 2016, 719 - 722

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M.Tech / M.E / PhD Thesis, Control Systems Engineering, Sudan, Volume 5 Issue 2, February 2016

Pages: 719 - 722

Study on Self-Adaptive Control System - View of Internal Adaptation

Hussam Mohammed-ElHassan Ibrahim Dafaalla, Dalia Mahmoud

Share this Article
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