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Neural network formation control of a team of tractor–trailer systems

Published online by Cambridge University Press:  03 April 2017

Khoshnam Shojaei
Khoshnam Shojaei*
Affiliation:
Department of Electrical Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
*
*Corresponding author. E-mail: khoshnam.shojaee@gmail.com
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Summary

This paper addresses the formation tracking control of a group of tractor–trailer systems in the presence of model uncertainties. A virtual leader–follower formation technique is used to design a controller in order to force a team of tractor–trailer systems to construct a desired formation configuration. Since tractor–trailer systems have a nonlinear multi-input multi-output model with strong couplings, multi-layer neural networks are employed to overcome unknown nonlinearities and uncertain parameters by using on-line weight tuning algorithms. Neural network approximation errors and external disturbances are also compensated with adaptive robust signals. The dynamic surface control approach has been used to reduce the complexity of the proposed controller effectively. Lyapunov’s direct method proves that all signals in the closed-loop formation control system are bounded and tracking errors converge to a neighborhood of the origin whose size is adjustable. Finally, simulation results will be provided to illustrate the efficiency of the proposed controller.

Keywords

Adaptive controlDynamic surface controlFormation controlNeural networkTractor–trailerVirtual leader–follower
Type
Articles
Information
Robotica , Volume 36 , Issue 1 , January 2018 , pp. 39 - 56
Copyright
Copyright © Cambridge University Press 2017 

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