Abstract
In this paper, an intelligent controller is proposed for high-accuracy position tracking control of a 4-degree-of-freedom (4DOF) robot. The control scheme is formatted using a 2-layer neural-network template, in which the first layer is encoded by a proportional-derivative structure, and the second layer is comprised of three different functions. Three ranges of perturbation that affects to the control performance are respectively treated by an offset learning, a folding PD control and high-switching control terms. The gains of the control terms are updated using modified gradient methods. Effectiveness of the proposed control is successfully verified by comparative simulation results.
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The authors are very grateful to the referees and editors for their valuable comments, which helped to improve the paper quality. This work is funded by the Vietnam National Foundation for Science and Technology (NAFOSTED) under grant number 107.01-2020.10.
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Tai, V.T., Minh, D.N., Ba, D.X. (2021). A PD-Folding-Based Controller for a 4DOF Robot. In: Huang, YP., Wang, WJ., Quoc, H.A., Giang, L.H., Hung, NL. (eds) Computational Intelligence Methods for Green Technology and Sustainable Development. GTSD 2020. Advances in Intelligent Systems and Computing, vol 1284. Springer, Cham. https://doi.org/10.1007/978-3-030-62324-1_11
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