The Fixed-Time Observer-Based Adaptive Tracking Control for Aerial Flexible-Joint Robot with Input Saturation and Output Constraint

Abstract

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, is proposed (FTOAC). 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.

A Novel Active Anti-Disturbance Control Strategy for Unmanned Aerial Manipulator Based on Variable Coupling Disturbance Compensation

“…In the existing research, the compensation and suppression of coupling disturbance and lumped disturbances were achieved through the force and torque produced by the propellers of the UAV, based on the instructions of the control algorithm. For this purpose, various controllers have proven to be useful, see for instance [6,7,24] and references therein. However, as proposed in this paper, the term B τ cd can be utilized as a control input signal to offset and mitigate lumped disturbances, thereby reducing both the disturbance that necessitates compensation by the control algorithm and the energy consumption of the UAV.…”

“…An UAM is subjected to various lumped disturbances in the actual aerial work environment, arising from factors including wind gusts, unmodeled dynamics, and other external factors [20]. To provide UAMs with robustness against these disturbances, existing methods basically rely on various advanced controllers combined with various online disturbance-estimation-based approaches to estimate and compensate for the lumped disturbances [6,[21][22][23][24]. For example, an adaptive sliding-mode disturbance observer-based finite-time control scheme [6], compliant control strategy with FIR-based disturbance observer [21], and an adaptive NN backstepping control method [9] were proposed to estimate and compensate for this effect.…”

Commonality Evaluation and Prediction Study of Light and Small Multi-Rotor UAVs

“…Zhang et al [26] developed the LASSA-RRT algorithm to enhance the global search advantage in UAV trajectory planning. Li [27] suggested an adaptive control scheme based on a fixed-time observer (FTOAC) for UAV tracking control. Additionally, there are numerous UAV design optimization studies utilizing intelligent algorithms [28,29].…”