Neural network based predictive control of DC motor position by Newton - Raphson method

DC motor operation with accurate position control marks a positive impact for the functioning of the motor driven system in the electric sector. Rotor position control aspect favours the necessity of precise movement of the connected load. In this paper, model predictive control algorithm drives the positioning control of DC motor and neural network using Newton-Raphson method trains the data in an orderly fashion to achieve desired output. Model predictive control tests the functioning of required position enabling DC motor operation through MATLAB program codings. The test results pose the necessity of position control in the system when compared to its absence. Plant model is designed using MATLAB/Simulink and the necessary training and testing is carried out using codings. Results picturize the need of stated algorithms for the accurate positioning of rotor and precise application of motor in an electric circuit.