Research on Single Neuron Adaptive PID Controller

The paper focuses on single neuron adaptive PID controller based on unsupervised Hebb algorithm, and simulation research on the controller is carried out for a second-order pure lag process system. Simulation results show that through learning and adjusting weights of single neuron adaptive PID controller, its online self-tuning ability can make timely adjustment of PID controller parameters according to controlled object changes and external disturbances in order to ensure that the stability and robustness of the system and, ultimately, more satisfactory actual control effect is obtained. At last, the control characteristics and parameter design rules are concluded.