JACIII Vol.15 No.7 pp. 846-853
doi: 10.20965/jaciii.2011.p0846


Neuro-PID Control for Electric Vehicle

Shigeru Omatu*, Michifumi Yoshioka**, and Toru Fujinaka***

*Osaka Institute of Technology, 5-16-1 Omiya, Asahi-ku, Osaka 535-8585, Japan

**Osaka Prefecture University, 1-1 Gakuen-cho, Naka-ku, Sakai 599-8531, Japan

***Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima 739-8524, Japan

March 3, 2011
May 9, 2011
September 20, 2011
neuro-PID, electric vehicle control, speed control, torque control

In this paper we consider the neuro-control method and its application to control problems of an electric vehicle. The neuro-control methods adopted here is based on Proportional-plus-Integral-plus-Derivative (PID) control, which has been adopted to solve process control or intelligent control problems. In Japan about eighty four percent of the process industries have used the PID control. After deriving the self-tuning PID control scheme (neuro-PID) using the learning ability of the neural network, we will show the control results by using the speed and torque control of an electric vehicle.

Cite this article as:
S. Omatu, M. Yoshioka, and T. Fujinaka, “Neuro-PID Control for Electric Vehicle,” J. Adv. Comput. Intell. Intell. Inform., Vol.15, No.7, pp. 846-853, 2011.
Data files:
  1. [1] D. E. Rumelhart, J. L. McClelland, and PDP Group, “Parallel Distributed Processing,” Explorations in the Microstructure of Cognition, Vol.1, MIT Press, Massachusetts, 1987.
  2. [2] S. Omatu, K. Maruzuki, and Y. Rubiyah, “Neuro-Control and Its Applications,” Springer, London, 1996.
  3. [3] S. Omatu, “Neuro-Control Applications in Real-World Problems,” Proc. of the 10th Yale Workshop on Adaptive and Learning Systems, pp. 92-97, Yale University, New Haven, 1998.

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Last updated on Sep. 09, 2019