Abstract

Cable-driven parallel robots (CDPRs) usually suffer from kinematic and dynamic uncertainties, which makes it difficult for traditional trajectory tracking control algorithms to achieve high precision, fast response time, and robustness. In this study, we present a novel fast finite-time tracking control (FFTTC) algorithm which solves this problem to a large extent. Specifically, we firstly used a function of exponential errors with fractional power combined with API technique, to deal with the key difficulty of the convergence rate degradation which exists in traditional finite-time tracking control (TFTTC) when system states are far from the equilibrium point. Simultaneously, the API technique was used to avoid the problem of the explosion of complexity. To facilitate algorithm evaluation, the finite-time stability of the close system consisting of the proposed FFTTC algorithm and the CDPRs was proved mathematically and the settling time was estimated correspondingly. The trajectory tracking experiments were performed on a 3-DOF CDPR driven by 4 cables. Simulation and experimental results show that the proposed FFTTC algorithm can cope with external disturbances, variable load, and inaccurate model parameters. The comparison experiment indicates that the proposed FFTTC algorithm is superior to the model predictive control and TFTTC algorithms in precision, response speed and robustness.

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