Simulation of Networked Control Systems Based on Single Neuron Adaptive PID with Smith Predictor

neuron control system not only has simple structure and strong robustness, but also can adapt to the systems affected by interference. At the same time, Smith predictor is characterized by predicting the dynamic characteristics of time-delay systems. Aimed at the problem of time delay in networked control systems, a kind of controller based on improved single neuron adaptive PID with new Smith predictor is presented. It utilizes the self-learning and self-adaptive ability of single neuron, and Smith predictive compensation characteristics. The network based control for a DC motor is simulated in Matlab. The simulation result shows that the control algorithm based on improved Single Neuron adaptive PID with new Smith predictor can effectively improve the robustness and adaptability of networked control systems.