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The aerial flexible-joint robot (AFJR) manipulation system has been widely used in recent years. To handle uncertainty, the input saturation and the output constraint existing in the system, a fixed-time observer-based adaptive control scheme (FTOAC) is proposed. First, to estimate the input saturation and disturbances from the internal force between the robot and the flight platform, a fixed-time observer is designed. Second, a tangent-barrier Lyapunov function is introduced to implement the output constraint. Third, adaptive neural networks are introduced for the online identification of nonlinear unknown dynamics in the system. In addition, a fixed-time compensator is designed in this paper to eliminate the adverse effects caused by filtering errors. The stability analysis shows that all the signals of the closed-loop system are bounded, and the system satisfies the condition of fixed-time convergence. Finally, the simulation results prove the superiority of the proposed control strategy by comparing it with the previous schemes.
Li et al. (Fri,) studied this question.