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Title: | Optimal super-twisting sliding mode control design of robot manipulator: Design and comparison study |
Keywords: | Robotic manipulator Super-twisting SMC Social spider optimization Particle swarm optimization Manipulador robótico Otimização por enxame de partículas Inteligência artificial |
Issue Date: | Dec-2020 |
Publisher: | SAGE Publications Ltd. |
Citation: | AL-DUJAILI, A. Q. et al. Optimal super-twisting sliding mode control design of robot manipulator: Design and comparison study. International Journal of Advanced Robotic Systems, [S. I.], p. 1-17, Nov./Dec. 2020. DOI: 10.1177/1729881420981524. |
Abstract: | This article presents a tracking control design for two-link robot manipulators. To achieve robust tracking control performance, a super-twisting sliding mode control (STSMC) is derived. The stability of the system based on the proposed approach is proved based on the Lyapunov theorem. However, one problem with the designed STSMC is to properly set its parameters during the design. Therefore, it is proposed a social spider optimization (SSO) to tune these design parameters to improve the dynamic performance of the robot manipulator controlled considering STSMC. The performance of the STSMC approach based on SSO is compared to that based on particle swarming optimization (PSO) in terms of dynamic performance and robustness characteristics. The effectiveness of the proposed optimal controllers is verified by simulations within the MATLAB software. It is verified that the performance given by SSO-based STSMC outperforms that resulting from PSO-based STSMC. The experimental results are conducted based on LabVIEW 2019 software to validate the numerical simulation. |
URI: | http://repositorio.ufla.br/jspui/handle/1/46562 |
Appears in Collections: | DAT - Artigos publicados em periódicos DEG - Artigos publicados em periódicos |
Files in This Item:
File | Description | Size | Format | |
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ARTIGO_Optimal super-twisting sliding mode control design of robot manipulator Design and comparison study.pdf | 2,12 MB | Adobe PDF | View/Open |
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