A Review on Intelligent PID Controllers in Autonomous Vehicle

Abstract

In recent times, autonomous vehicle is gaining popularity in several of applications ranging from conventional transport system to nuclear reactor. The importance of autonomous vehicle increases manifold for those applications where it is not possible or very much risky for human to reach out. Many Artificial Intelligence techniques have been successfully applied in this field. In this paper, an adequate number of recent machine learning-based techniques to design intelligent PID controllers in autonomous vehicles have been reviewed and suitably compared with some other competitive approaches. Particularly, the parameters tuning of Kp, Ki, Kd as well as the rise time characteristics by two methods, namely Ziegler–Nichols and genetic algorithm (GA), have been discussed. Also, we have compared the properties of rise time and percentage overshoot by conventional PID controllers and fuzzy-based PID controllers.