Control strategies optimization of track-hunting intelligent car using advanced PID controllers

Intelligent vehicles have been major research interests recent years. A track-hunting intelligent car is presented in this paper. A fuzzy Proportional-Integral-Derivative(PID) controller is applied in the direction control of this car, which could execute self-tuning operation under different situations. And a friction based differential-forward PID controller is proposed to solve the dichotomy between fast response and stability. Differential-forward part enhance the step response, while the friction compensation makes car more stable at a low speed. Numerical simulation and real experiments are conducted to evaluate these two controllers, and results obtained demonstrate effectiveness of the controllers.