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Adaptive Neural Feedback Linearizing Control of Type (m,s) Mobile Manipulators with a Guaranteed Prescribed Performance

Published online by Cambridge University Press:  10 April 2019

Khoshnam Shojaei Open the ORCID record for Khoshnam Shojaei [Opens in a new window]  and
Ali Kazemy
Khoshnam Shojaei*
Affiliation:
Department of Electrical Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran Digital Processing and Machine Vision Research Center, Najafabad Branch, Islamic Azad University, Najafabad, Iran
Ali Kazemy
Affiliation:
Department of Electrical Engineering, Tafresh University, Tafresh 39518-79611, Iran. E-mail: kazemy@tafreshu.ac.ir
*
*Corresponding author. E-mail: khoshnam.shojaee@gmail.com
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Summary

In this paper, a neural network (NN)-based tracking controller is proposed for a general class of type (m,s) wheeled mobile manipulators (WMMs) subjected to model uncertainties with prescribed transient and steady-state performance specifications. First, an input–output model of WMMs is derived by introducing proper output equations. Then, the prescribed performance technique is employed to propose a proportional integral derivative trajectory tracking controller for WMMs to ensure that the tracking errors converge to a smaller, arbitrary ultimate bound with a predefined maximum overshoot/undershoot and convergence speed. The learning capabilities of multilayer NNs are incorporated into the controller to approximate the uncertain nonlinear dynamics of the robot. An adaptive saturation-type controller is utilized to compensate NN estimation errors and external disturbances. A Lyapunov-based stability analysis is used to demonstrate that the tracking errors are uniformly ultimately bounded and converge to a small neighborhood of zero with a guaranteed prescribed performance. Numerical computer simulations are presented to show the effectiveness of the proposed controller.

Keywords

Adaptive robust controlModel uncertaintyMultilayer neural networksPrescribed performance functionTrajectory trackingWheeled mobile manipulators
Type
Articles
Information
Robotica , Volume 37 , Issue 11 , November 2019 , pp. 1937 - 1955
Copyright
© Cambridge University Press 2019 

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