Published Paper Details:

This paper describes the design and implementation of overload protection for DC motor speed control application based on Artificial Intelligence (AI). A replica of DC motor hardware was modeled for simulation. Two neural network models were designed under no load and rated torque conditions to predict the output voltage to be applied for the given DC motor to achieve desired setpoint speed. From the output of a Proportional Integral (PI) controller the Neural network model will predict the voltage to be applied and a comparator will determine whether the voltage that has to be applied for the current load exceeds than that for the rated torque of the DC motor. The outcome from the comparison is the safety for the equipment by not exceeding rated current value and thereby reduce the thermal degradation of motor windings. A PI controller with delimiter can limit the output of the PI controller and thereby protect the motor windings from higher voltages, still, the windings get degraded when the motor run under overload conditions with lower setpoint speed for longer period. Simulation and real-time experiments along with the results are presented to demonstrate the reliability of the proposed control method over the traditional PI controller in DC motor speed control applications.