Speed control of DC machine using adaptive neural IMC controller based on recurrent neural network
Autor: | Z. Benmabrouk, Aycha Abid, M. Ben Hamed, L. Sbita |
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Rok vydání: | 2016 |
Předmět: |
Electronic speed control
Artificial neural network Time delay neural network Computer science 020209 energy Internal model Open-loop controller Control engineering 02 engineering and technology Recurrent neural network Control theory Robustness (computer science) 0202 electrical engineering electronic engineering information engineering Algorithm design |
Zdroj: | 2016 5th International Conference on Systems and Control (ICSC). |
DOI: | 10.1109/icosc.2016.7507069 |
Popis: | This paper is a comparative study of classic IMC controller and a new adaptive IMC recurrent neural controller. The two controllers are implemented to control the DC machine speed. The IMC neural controller is based on two neural networks, the first is a recurrent neural network that replaces the DC machine model and the second is a neural network that replaces the internal model controller. The recurrent neural algorithm is developed and applied to estimate and control the DC machine speed under various types of disturbances in order to approve the controller robustness. Simulation results are provided to show the effectiveness of the proposed controller. |
Databáze: | OpenAIRE |
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