Identification and control of a DC motor using back-propagation neural networks

An artificial-neural-network (ANN)-based high-performance speed-control system for a DC motor is introduced. The rotor speed of the DC motor can be made to follow an arbitrarily selected trajectory. The purpose is to achieve accurate trajectory control of the speed, especially when motor and load parameters are unknown. The unknown nonlinear dynamics of the motor and the load are captured by the ANN. The trained neural-network identifier is combined with a desired reference model to achieve trajectory control of speed. The performances of the identification and control algorithms are evaluated by simulating them on a typical DC motor model. It is shown that a DC motor can be successfully controlled using an ANN