A study of Experience Mapping based Prediction Controller for position control of DC motors with inertial and friction load changes

The paper studies the performance of a new controller utilized for the position control of DC motors. The new controller is inspired by the human voluntary body action control (dubbed motor control) mechanism. The controller is called Experience Mapping based Prediction Controller (EMPC). EMPC is designed with the concepts of the human motor action prediction-control mechanism as part of its core. The controller has auto-learning features without the need for a plant model which is inspired by the experiential learning ability of humans. The ability to adapt to environmental changes has also been developed as part of EMPC. The simulation results for position control of DC motors for inertial and friction load changes are presented to show that accurate control is achieved using EMPC with good adaptation. The performance of EMPC is compared with MRAC based position controller. Position control of DC motors with load changes is practically implemented using EMPC and the results are presented.