Noniterative Positive Constrained Control of Cable-Driven Parallel Robots

In cable-driven parallel robots (CDPRs), the controller should generate positive output forces, as cables only support tensile forces. In fully constrained CDPRs, positive tension distribution in cables is guaranteed using optimization-based techniques, which have unpredictable worst case computatio...

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Bibliographic Details
Published in:IEEE transactions on industrial informatics 2024-02, Vol.20 (2), p.2007-2016
Main Authors: Ameri, Adel, Fazeli, Seyed Mahdi, Molaei, Amir, Khosravi, Mohammad A., Hassani, Masoud
Format: Article
Language:English
Subjects:
Actuators
Asymptotic methods
Cable-driven parallel robots (CDPRs)
Cables
Closed loops
Computing time
constrained control
Control systems design
Controllers
Dynamic models
End effectors
Feedback control
Informatics
Jacobian matrices
Liapunov direct method
Linear matrix inequalities
Mathematical models
Optimization
Power cables
Redundancy
redundancy resolution
Robot control
Robust control
Sliding mode control
Stability analysis
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Summary:In cable-driven parallel robots (CDPRs), the controller should generate positive output forces, as cables only support tensile forces. In fully constrained CDPRs, positive tension distribution in cables is guaranteed using optimization-based techniques, which have unpredictable worst case computation time. Furthermore, the optimization-based methods fail to handle situations where the initial pose of the end-effector is beyond the wrench-feasible workspace (WFW). To address the existing problems, we introduce a new representation of the dynamic model of CDPRs by including cable tension positiveness as an inherent part of the dynamic, using an absolute function. This leads to a nonaffine dynamic model, which is then converted to the affine form, for which a robust super-twisting sliding-mode controller is designed. The stability of the closed-loop system is guaranteed via the Lyapunov direct method, where H_{\infty } asymptotic stability is proved with parameters derived by solving a linear matrix inequality. The superiority of the proposed method is validated in both simulation and experiment. The analytical nature of the method also allows dramatic improvement in the computation time of the control compared to the optimization-based methods in the literature. In addition, it shows suitable performance at the boundary of the WFW, while conventional methods fail to operate.
ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2023.3285038