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A Novel Model-Based Robust Super-Twisting Sliding Mode Control of PKMs: Design and Real-Time Experiments

Hussein Saied 1 Ahmed Chemori 1 Maher El Rafei 2 Clovis Francis 2 
1 DEXTER - Robotique médicale et mécanismes parallèles
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : In this paper, a new robust model-based supertwisting algorithm is proposed as a control solution for parallel kinematic manipulators (PKMs). The conventional supertwisting algorithm for robot manipulators has the structure of a computed-torque control which can be sensitive to measurement noise. This issue may deteriorate the dynamic performance of the manipulator and reduce its robustness towards changes in the operating conditions. The proposed approach, relying on the desired trajectory, is more computationally efficient and more robust. It includes a feedforward dynamic compensator, the super-twisting feedback control, and a feedback stabilizing term. As a validation, real-time experiments have been conducted on a 5-DOF redundantly actuated PKM. Several scenarios have been tested including nominal case and the robustness towards speed variations. The relevance of the proposed control solution is proved through the improvement of the tracking performance at different dynamic operating conditions.
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Submitted on : Saturday, October 9, 2021 - 6:32:45 AM
Last modification on : Friday, August 5, 2022 - 3:03:30 PM




Hussein Saied, Ahmed Chemori, Maher El Rafei, Clovis Francis. A Novel Model-Based Robust Super-Twisting Sliding Mode Control of PKMs: Design and Real-Time Experiments. IROS 2021 - IEEE/RSJ International Conference on Intelligent Robots and Systems, Sep 2021, Prague, Czech Republic. pp.8029-8035, ⟨10.1109/IROS51168.2021.9636168⟩. ⟨lirmm-03343014v2⟩



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