Fixed-time robust control framework for saturated robotic systems: a nonsingular terminal sliding mode method via RBFNN

Le résumé fourni par la source

This paper presents an adaptive fixed-time sliding-mode control (SMC) strategy to address the trajectory tracking problem of n-link robotic manipulators subject to input saturation, parameter uncertainties, and external disturbances. Firstly, the unknown dynamic parameters and the bound vector of external disturbances are integrated into a compounded uncertainty. Then, a robust controller based on nonsingular fast terminal SMC is designed under the assumption that the upper boundary of the compounded uncertainty is precisely known. Considering that the boundary of compounded uncertainty is not readily available in practice, the adaptive radial basis function neural networks are adopted to compensate for compounded uncertainty of the manipulator. Moreover, in order to enhance the fast tracking capability and robustness of the controlled system, the nonsingular fast terminal SMC is merged into the control framework. The proposed controller in this paper can guarantee the actual trajectory track the desired reference trajectory within a fixed time while eliminating the influence of input saturation. At last, simulation results based on a two-joint manipulator confirm the excellent performance and effectiveness of the proposed approach.

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