Browse > Article
http://dx.doi.org/10.6109/jkiice.2014.18.8.1811

Formation Control of Mobile Robots using PID Controller with Neural Networks  

Kim, Yong-Baek (Department of Electrical Engineering, Pusan National University, Automation Research Dept., Industrial Technology Institute, Hyundai Heavy Industries)
Park, Jin-Hyun (Dept. of Mechatronics Eng., Kyeognam National University of Science and Technology)
Choi, Young-Kiu (Department of Electrical Engineering, Pusan National University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.18, no.8, 2014 , pp. 1811-1817 More about this Journal
Abstract
In this paper, a PID controller with interpolated gains by use of neural networks is proposed for the formation control problem that following robots track a leading robot with constant distances and angles when there are changes in the mass of the following robot. The whole control system is composed of a kinematic controller and a dynamic controller considering the robot dynamics. The dynamic controller is the PID controller with varying gains, and the proper gains are obtained for some representative masses of the follower robot by the genetic algorithm. Neural networks is trained using the genetic algorithm with the gain data obtained in the previous step. The trained neural network determines optimal PID gains for a random mass of following robot. Simulation studies show that for arbitrary masses of the tracking robot, the PID controller with interpolated gains by the trained neural network has better tracking performance than that of the PID controller with fixed gains.
Keywords
formation control; PID control; genetic algorithm; neural network;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Y. Q. Chen and Z. Wang, "Formation control: a review and a new consideration," Proc. IEEE International Conference on Intelligent Robots and systems, pp. 3181-3186, Aug 2005.
2 Aveek K. Das et. al., "A vision-based formation control framework," IEEE Trans on Robotics and Automaton, vol. 18, no. 5, Oct 2002.
3 J. Shao, G. Xie and L. Wang, "Leader-following formation control of multiple mobile vehicles," IET Control Theory and Applications, vol. 1, no. 2, pp. 545-552, Mar 2007.   DOI   ScienceOn
4 R. Fierro and F. L. Lewis, "Control of a nonholonomic mobile robot: Backstepping kinematics into dynamics," Proc. IEEE Conference on Decision and Control, pp. 3805-3810, 1995.
5 A. M. Bloch, M. Reyhanoglu and N. H. McClamroch, "Control and stabilization of nonholonomic dynamic systems," IEEE Trans. Automatic Control, vol. 37, pp. 1746-1757, 1992.   DOI   ScienceOn
6 N. Sarkar, X. Yun and V. Kumar, "Control of mechanical system with rolling constraints: Application to dynamical control of mobile robots," Int. J. Robot. Res., vol. 13, no. 1, pp. 55-69, 1994.   DOI   ScienceOn
7 E. R. Fierro and F. L. Lewis, "Control of a nonholonomic mobile robot using neural networks," IEEE Trans on Neural Networks, vol. 9, no. 4, July 1998.
8 Y. B. Kim, J. H. Park and Y. K. Choi, "Design of PID controller with adaptive neural network compensator for formation control of mobile robots," Journal of the Korea Insttute of Information and Communication Engineering, vol. 18, no. 3, Mar 2014.   과학기술학회마을   DOI   ScienceOn