Tracking Control of a Nonholonomic Mobile Robot Using Neural Network
in: Handbook of Research on Advancements in Robotics and Mechatronics, Habib Maki K., Editor, IGI Global, Cairo, pp.631-661, 2015
- Publication Type: Book Chapter / Chapter Research Book
- Publication Date: 2015
- Publisher: IGI Global
- City: Cairo
- Page Numbers: pp.631-661
- Editors: Habib Maki K., Editor
- Erciyes University Affiliated: Yes
Abstract
The
goal of this chapter is to enable a nonholonomic mobile robot to track a
specified trajectory with minimum tracking error. Towards that end, an
adaptive P controller is designed whose gain parameters are tuned by
using two feed-forward neural networks. Back-propagation algorithm is
chosen for online learning process and posture-tracking errors are
considered as error values for adjusting weights of neural networks. The
tracking performance of the controller is illustrated for different
trajectories with computer simulation using Matlab/Simulink. In
addition, open-loop response of an experimental mobile robot is
investigated for these different trajectories. Finally, the performance
of the proposed controller is compared to a standard PID controller. The
simulation results show that “adaptive P controller using neural
networks” has superior tracking performance at adapting large
disturbances for the mobile robot.