Fuzzy Sliding Mode Control of Manipulator Based on Disturbance Observer and RBF Neural Network
Author:
Publisher
Allerton Press
Subject
Signal Processing,Control and Systems Engineering,Software
Link
https://link.springer.com/content/pdf/10.3103/S0146411623020098.pdf
Reference24 articles.
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3. Sri Harsha, A. and Vikram Kumar, Ch.R., Fused deposition modeling of an aircraft wing using industrial robot with non-linear tool path generation, Int. J. Eng., 2021, vol. 34, no. 1, pp. 272–282. https://doi.org/10.5829/IJE.2021.34.01A.30
4. Xie, Zh., Sun, T., Kwan, T., and Wu, X., Motion control of a space manipulator using fuzzy sliding mode control with reinforcement learning, Acta Astronaut., 2020, vol. 176, pp. 156–172. https://doi.org/10.1016/j.actaastro.2020.06.028
5. Brahim, B., Laraki, M.H., Brahmi, A., Saad, M., and Rahman, M.H., Improvement of sliding mode controller by using a new adaptive reaching law: Theory and experiment, ISA Trans., 2020, vol. 97, pp. 261–268. https://doi.org/10.1016/j.isatra.2019.08.010
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