Abstract
This paper investigates the station-keeping control of autonomous and remotely-operated vehicles (ARVs) for free-floating manipulation under model uncertainties and external disturbances. A modified adaptive generalized super-twisting algorithm (AGSTA) enhanced by adaptive tracking differentiator (ATD) and reduced-order extended state observer (RESO) is proposed. The ATD is used to obtain the smooth reference signal and its derivative. The RESO is used to estimate and compensate for the model uncertainties and external disturbances in real-time, which enhances the robustness of the controller. The modified AGSTA ensures the fast convergence of the system states and maintains them in a predefined neighborhood of origin without overestimating control gains. Besides, the proposed new variable gain strategy completely avoids the control gains vibrating near the set minimum value. Thanks to the RESO, the proposed controller is model-free and can be easily implemented in practice. The stability of the closed-loop system is analyzed based on Lyapunov’s direct method in the time domain. Finally, the proposed control scheme is applied to the station-keeping control of Haidou-1 ARV, and the simulation results confirm the superiority of the proposed control scheme over the original AGSTA.
Highlights
Accepted: 18 November 2021In recent years, unmanned underwater vehicles (UUVs) have been widely utilized in various areas such as marine science, marine rescue, and offshore industry [1]
The results show that the total disturbance can be effectively estimated and compensated by the reduced-order extended state observer (RESO)
One can see that the estimated total disturbance has a slight phase lag compared to the simulated value because the bandwidth of RESO is restricted to the measurement noise
Summary
In recent years, unmanned underwater vehicles (UUVs) have been widely utilized in various areas such as marine science, marine rescue, and offshore industry [1]. The coupling force caused by manipulator movement is considered as a disturbance to be compensated by the vehicle controller. In recent years, this approach has been investigated by several researchers. The major drawback of the SMC is the chattering issue, which degrades the control performance, reduces the life of the actuator, and may excite high-frequency unmodeled dynamics For these reasons, substantial methods on chattering reduction have been developed in recent years, such as the boundary layer method [20,21,22], adaptive control [23,24], fuzzy logic control [25,26], high-order SMC (HOSMC) [27,28,29].
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