Tracking control of a nonholonomic mobile robot using compound cosine function neural networks

2013 ◽  
Vol 6 (4) ◽  
pp. 191-198 ◽  
Author(s):  
Jun Ye
Keyword(s):  
Neural Networks ◽  
Mobile Robot ◽  
Tracking Control ◽  
Cosine Function ◽  
Nonholonomic Mobile Robot

Tracking Control of a Nonholonomic Mobile Robot Using Neural Network

2015 ◽  
pp. 631-661 ◽  
Author(s):  
Şahin Yildirim ◽  
Sertaç Savaş
Keyword(s):  
Neural Networks ◽  
Mobile Robot ◽  
Tracking Error ◽  
Back Propagation ◽  
Open Loop ◽  
Tracking Performance ◽  
Back Propagation Algorithm ◽  
Tracking Errors ◽  
Nonholonomic Mobile Robot ◽  
Feed Forward Neural Networks

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.

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