PID Control of DC Servo Motor using a Single Memory Neuron

In this paper, a novel approach to determine the optimal values of a PID controller is presented. The proposed method is based on using a single memory neuron which its weights represent the PID parameters. These weights are updated by the well-known bio-inspired algorithm: the particle swarm optimization. To show the efficiency of our method, we have applied it to control a DC servo motor which is used as an actuator for an arm robot manipulator. The obtained results are compared with those a fuzzy logic controller.