Abstract
This paper deals with the discrete-time position control problem for an autonomous underwater vehicle (AUV) under noisy conditions. Due to underwater noise, the velocity measurements returned by the AUV’s on-board sensors afford low accuracy, downgrading its control quality. Additionally, most of the hydrodynamic parameters of the AUV model are uncertain, further degrading the AUV control accuracy. Based on these findings, a discrete-time control law that improves the position control for the AUV trajectory tracking is presented to reduce the impact of these two factors. The proposed control law extends the Ensemble Kalman Filter and solves the problem of the traditional Ensemble Kalman Filter that underperforms when the hydrodynamic parameters of the AUV model are uncertain. The effectiveness of the proposed discrete-time controller is tested on various simulated scenarios and the results demonstrate that the proposed controller has appealing precision for AUV position tracking under noisy conditions and hydrodynamic parameter uncertainty. The proposed controller outperforms the conventional time-delay controller in root-mean-square error by a percentage range of approximately 72.1–97.4% and requires at least 89.5% less average calculation time than the conventional model predictive control.
Highlights
Autonomous underwater vehicles (AUVs) can perform a variety of deep-sea tasks [1].These tasks broadly involve marine engineering, military, and marine science fields [2,3].tasks such as the inspection of underwater pipelines, enemy target tracking, and marine environmental data collection can be performed by controlling autonomous underwater vehicle (AUV) [4,5].the acquired data quality is highly dependent on the AUV position accuracy [6].improving the positional precision of an AUV has recently become a hot research topic
The enhanced TDC is computationally simple and robust to unmodeled dynamics and disturbances. These time-delay controllers (TDCs) are designed by employing the time-delay estimator (TDE) that is capable of estimating uncertain hydrodynamic parameters, using time-delayed state derivatives and control inputs [19,20]
It is worth noting that the proposed controller is tested only against opensource controllers, namely the conventional linear controller, TDC, and model predictive control (MPC) controller, because re-implementing current controllers might lead to a non-optimized solution that inevitably would underestimate the capabilities of the original method
Summary
Autonomous underwater vehicles (AUVs) can perform a variety of deep-sea tasks [1]. These tasks broadly involve marine engineering, military, and marine science fields [2,3]. Compared with adaptive control techniques, robust control techniques require fewer computing resources This type of control demands the knowledge of some of the hydrodynamic parameters, which are usually uncertain. The enhanced TDC is computationally simple and robust to unmodeled dynamics and disturbances These time-delay controllers (TDCs) are designed by employing the time-delay estimator (TDE) that is capable of estimating uncertain hydrodynamic parameters, using time-delayed state derivatives and control inputs [19,20]. Several Matlab/Simulink simulations are performed and the result demonstrates that the proposed discrete-time control law attains better position control precision, compared to the existing control laws, for trajectory tracking. The scenarios include various noise conditions, where the precision of the proposed control law in trajectory tracking is verified and the presented technique is tested on several sampling times or ensembles.
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