Abstract
An adaptive sliding mode controller based on fuzzy logic is proposed to control a manipulator robot over unknown surface trajectory using force-vision tracking, considering uncertainties of the kinematic, dynamic, and camera models. In this work we show that the robot can track the desired trajectories overcoming the model’s uncertainties, the use of the sliding mode to reject the disturbances and converge much faster, a nonlinear sliding surface proposed to regulate the convergence speed in order to illuminate the overshoot of the system response, thanks to the online fuzzy logic adaption, used to generate the equivalent control. The system’s stability has been validated using Lyapunov criteria. So as to show the performance of the proposed control law, we performed simulations consisting of a series of tests in various conditions. The obtained results allowed us to validate the robustness of the controller towards the payload variations and the model’s uncertainties.
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ACKNOWLEDGMENTS
The authors would like to thank the editor in chief and the anonymous reviewers for their valuable comments and suggestions that helped improve the quality of this work.
Funding
This work was supported by the CNEPRU project (Systems achieved for personal assistance) under contract no. J 0200220140007 funded by the Ministry of Higher Education and scientific research.
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Djelal, N., Saadia, N. & Ramdane-Cherif, A. Adaptive Force-Vision Control of Robot Manipulator Using Sliding Mode and Fuzzy Logic. Aut. Control Comp. Sci. 53, 203–213 (2019). https://doi.org/10.3103/S0146411619030027
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DOI: https://doi.org/10.3103/S0146411619030027