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Speed control of DC machine using adaptive neural IMC controller based on recurrent neural network

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.