Experimental Validation of a Model-Free High-Order Sliding Mode Controller with Finite-Time Convergence for Trajectory Tracking of Autonomous Underwater Vehicles

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The use of autonomous underwater vehicles (AUVs) has expanded in recent years to include inspection, maintenance, and repair missions. For these tasks, the vehicle must maintain its position while inspections or manipulations are performed. Some station-keeping controllers for AUVs can be found in the literature that exhibits robust performance against external disturbances. However, they are either model-based or require an observer to deal with the disturbances. Moreover, most of them have been evaluated only by numerical simulations. In this paper, the feasibility of a model-free high-order sliding mode controller for the station-keeping problem is validated. The proposed controller was evaluated through numerical simulations and experiments in a semi-Olympic swimming pool, introducing external disturbances that remained unknown to the controller. Results have shown robust performance in terms of the root mean square error (RMSE) of the vehicle position. The simulation resulted in the outstanding station-keeping of the BlueROV2 vehicle, as the tracking errors were kept to zero throughout the simulation, even in the presence of strong ocean currents. The experimental results demonstrated the robustness of the controller, which was able to maintain the RMSE in the range of 1–4 cm for the depth of the vehicle, outperforming related work, even when the disturbance was large enough to produce thruster saturation.

Section: Time Parametrization Of α Gainmentioning

confidence: 99%

Section: Experimentationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Model-Free High-Order Sliding Mode Controller for Station-Keeping of an Autonomous Underwater Vehicle in Manipulation Task: Simulations and Experimental Validation

González-García

Gómez-Espinosa

García-Valdovinos

et al. 2022

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“…Autonomous underwater vehicles (AUV) have always been an important tool to undertake Marine military tasks and complete Marine resource development, especially in polar resource exploration, and has attracted more and more attention from researchers around the world [1,2]. Due to the special geographical environment and geomagnetic characteristics in polar regions, common satellite navigation, radio navigation, and geomagnetic navigation can not work effectively in polar regions for a long time [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

A Vision Aided Initial Alignment Method of Strapdown Inertial Navigation Systems in Polar Regions

Zhang

Gao

Song

2022

The failure of the traditional initial alignment algorithm for the strapdown inertial navigation system (SINS) in high latitude is a significant challenge due to the rapid convergence of polar longitude. This paper presents a novel vision aided initial alignment method for the SINS of autonomous underwater vehicles (AUV) in polar regions. In this paper, we redesign the initial alignment model by combining inertial navigation mechanization equations in a transverse coordinate system (TCS) and visual measurement information obtained from a camera fixed on the vehicle. The observability of the proposed method is analyzed under different swing models, while the extended Kalman filter is chosen as an information fusion algorithm. Simulation results show that: the proposed method can improve the accuracy of the initial alignment for SINS in polar regions, and the deviation angle has a similar estimation accuracy in the case of uniaxial, biaxial, and triaxial swing modes, which is consistent with the results of the observable analysis.

“…In order to handle the influences of uncertainties and exterior disturbances, sliding mode control (SMC) with powerful and immutable properties can be employed effectively. In recent years, SMC has been successfully applied for a wide range of practical applications such as unmanned aerial vehicles (UAVs) [ 8 , 9 , 10 ], autonomous underwater vehicles (AUVs) [ 11 , 12 , 13 , 14 , 15 ], robotic manipulators [ 16 , 17 , 18 , 19 , 20 ], and so on. In the approach stage, SMC cannot maintain uniform characteristics due to the existence of unidentified uncertain elements.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Implementation of the Prescribed Performance Tracking Control for Magnetic Levitation Systems

Truong

Kang

2022

For magnetic levitation systems subject to dynamical uncertainty and exterior perturbations, we implement a real-time Prescribed Performance Control (PPC). A modified function of Global Fast Terminal Sliding Mode Manifold (GFTSMM) based on the transformed error of the novel PPC is introduced; hence, the error variable quickly converges to the equilibrium point with the prescribed performance, which means that maximum overshoot and steady-state of the controlled errors will be in a knowledge-defined boundary. To enhance the performance of Global Fast Terminal Sliding Mode Control (GFTSMC) and to reduce chattering in the control input, a modified third-order sliding mode observer (MTOSMO) is proposed to estimate the whole uncertainty and external disturbance. The combination of the GFTSMC, PPC, and MTOSMO generates a novel solution ensuring a finite-time stable position of the controlled ball and the possibility of performing different orbit tracking missions with an impressive performance in terms of tracking accuracy, fast convergence, stabilization, and chattering reduction. It also possesses a simple design that is suitable for real-time applications. By using the Lyapunov-based method, the stable evidence of the developed method is fully verified. We implement a simulation and an experiment on the laboratory magnetic levitation model to demonstrate the improved performance of the developed control system.