Self-adaptation PID Ramp Controller in Freeway Based on Single Neuron

Abstract

An improved self-adaptation PID control method based on single neuron is proposed to regulate the number of vehicles entering a freeway entrance point. The freeway traffic flow dynamic model is first built. Then the ramp control objective is determined. According to nonlinear feedback principle, a self-adaptation PID ramp controller based on single neuron is designed, and an improved algorithm is used to obtain the weight values. Finally, the controller is simulated in MATLAB software. The result shows that the controller designed has strong robustness, fast response, and good dynamic and steady-state performance. This method has a good effect on freeway ramp control.