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What is Back-Propagation Algorithm

Chapter 20
Handbook of Research on Advancements in Robotics and Mechatronics
Learning algorithm for neural networks.
Published in Chapter:
Tracking Control of a Nonholonomic Mobile Robot Using Neural Network
Şahin Yildirim (Erciyes University, Turkey) and Sertaç Savaş (Erciyes University, Turkey)
Copyright: © 2015 |Pages: 31
DOI: 10.4018/978-1-4666-7387-8.ch020
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.
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Chapter 19
ANN Development with EC Tools: An Overview
Supervised learning technique used by ANNs, that iteratively modifies the weights of the connections of the network so the error given by the network after the comparison of the outputs with the desired one decreases.
Published in Chapter: ANN Development with EC Tools: An Overview; From: Encyclopedia of Artificial Intelligence
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Chapter 55
Complex-Valued Neural Networks
A supervised learning technique used for training neural networks, based on minimizing the error between the actual outputs and the desired outputs.
Published in Chapter: Complex-Valued Neural Networks; From: Encyclopedia of Artificial Intelligence
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Chapter 235
Wave Reflection at Submerged Breakwaters
Supervised learning technique used by ANNs that iteratively modifies the weights of the connections of the network so the error given by the network after the comparison of the outputs with the desired one decreases.
Published in Chapter: Wave Reflection at Submerged Breakwaters; From: Encyclopedia of Artificial Intelligence
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Chapter 94
Evolving Graphs for ANN Development and Simplification
Supervised learning technique used by ANNs, that iteratively modifies the weights of the connections of the network so the error given by the network after the comparison of the outputs with the desired one decreases
Published in Chapter: Evolving Graphs for ANN Development and Simplification; From: Encyclopedia of Artificial Intelligence
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