Self-tuning PID Parameters by using NN-GA for Cruise Control System

Jirapun Pongfai, Wudhichai Assawinchaichote


This paper considers the self-tuning PID parameters by using Neural Network (NN) together with Genetic Algorithm (GA) which is called the NN-GA. The NN-GA is the combination of Neural Network and Genetic Algorithm which is optimized the learning process of NN by using GA. From the simulation results, the NN-GA gives the better transient response i.e., the percent overshoot, the steady state error, the rise time and the settling time when compared with the pure NN, pure GA and PSO.


PID Controller; Self-Tuning; Cruise Control; Genetic Algorithm; Neural Networks; Particle and Swarm Optimization; Transient Response Analysis; Artificial Intelligence; Fitness Function Calculation

Full Text:



Khairuddin Osman, Mohd. Fuaad Rahmat and Mohd Ashraf Ahmad, "Modelling and Controller Design for a Cruise Control System", 2009 5th International Colloquium on Signal Processing & Its Application, March 2009.

Mahyar Vajedi and Nasser L. Azad, "Ecological Adaptive Cruise Controller for Plug-In Hybrid Electric Vehicles Using Nonlinear Model Predictive Control", IEEE TRANSACTION ON INTELLIGENT TRANSPORTATION SYSTEMS, vol. 17, Issue. 1, January 2016.

D. Sain, S.K. Swain and S.K. Mishra M.K. Rout, "PID Controller Design for Cruise Control System using Genetic algorithm”, International Conference on Electrical, Electronics and Optimization Techniques, November 2016.

Hua Ji and Zhiyong Li, "Design of Neural Network PID Controller Based on Brushless DC motor," IEEE, October 2009.

Xufei Dai, Zhili Long and Jianguo Zhang, “PSO based on chaotic Map and Its Application to PID Controller Self-tuning”, 2015 16th International Conference on Electronic Packaging Technology, August, 2015.



  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.