Comparison of two second-order sliding mode control algorithms for an articulated intervention AUV: Theory and experimental results

Borlaug, Ida-Louise Garmann; Pettersen, Kristin Y.; Gravdahl, Jan Tommy

doi:10.1016/j.oceaneng.2020.108480

Cited by 35 publications

(19 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Section: Discussionsupporting

confidence: 87%

“…One thing worth noting is that the results of this performance comparison between the STA with adaptive gains, the original GSTA and the PID controller are similar to those previously obtained in Reference 25. This strengthens the evidence from Reference 25 that adaptive gains are beneficial, as the results we obtain do not depend on our tuning capabilities. We also see that adding adaptive gains to the GSTA, thereby combining the theoretical advantages afforded by the GSTA and the practical advantages afforded by adaptive gains, improves the consequent tracking results and capabilities.…”

Section: Discussionsupporting

confidence: 87%

“…In References 21 and 22, we investigated the use of the STA with adaptive gains to control an AIAUV, and in References 23 and 24, we investigated the use of the original GSTA for this purpose. In Reference 25, we compared these two SMC algorithms through both simulations and experiments, and we observed that the STA with adaptive gains yielded better tracking results than the GSTA, even though the GSTA has better theoretical properties as it is proven to provide GFT stability for a larger class of systems. The incorporation of adaptive gains was thus seen to be very practical and to provide certain tuning advantages.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The generalized super‐twisting algorithm with adaptive gains

Borlaug

Pettersen

Gravdahl

2022

Intl J Robust & Nonlinear

Self Cite

View full text Add to dashboard Cite

In this paper a novel adaptive generalized supertwisting algorithm is proposed for a class of systems whose perturbations and uncertain control coefficients are time-and statedependent. The proposed approach uses dynamically adapted control gains, and it is proven that this ensures global finitetime convergence. A non-smooth strict Lyapunov function is used to obtain the conditions for the global finite-time stability. As a case study, it is also shown that the tracking errors of an articulated intervention AUV converge asymptotically to zero when the proposed adaptive generalized super-twisting algorithm is applied. A simulation study is performed that shows the effectiveness of the proposed algorithm.

show abstract

Section: Discussionsupporting

confidence: 87%

Section: Discussionsupporting

confidence: 87%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The generalized super‐twisting algorithm with adaptive gains

Borlaug

Pettersen

Gravdahl

2022

Intl J Robust & Nonlinear

Self Cite

View full text Add to dashboard Cite

show abstract

“…Autonomous navigation of AUVs has been widely explored in its different variants: waypoint navigation, path following, and trajectory tracking. For this purpose, various techniques, such as sliding mode control (SMC), high-order SMC, adaptive control, backstepping control, fuzzy control, and neural network control [14][15][16][17][18][19], have been explored. In manipulation operations, autonomous navigation is used to drive the vehicle to the object or surface on which the task will be performed.…”

Section: Introductionmentioning

confidence: 99%

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

Sensors

View full text Add to dashboard Cite

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.

show abstract

“…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]. Specifically, tasks such as the inspection of underwater pipelines, enemy target tracking, and marine environmental data collection can be performed by controlling AUVs [4,5].…”

Section: Introductionmentioning

confidence: 99%

Discrete-Time Position Control for Autonomous Underwater Vehicle under Noisy Conditions

Liu

2021

Applied Sciences

View full text Add to dashboard Cite

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.

show abstract

Comparison of two second-order sliding mode control algorithms for an articulated intervention AUV: Theory and experimental results

Cited by 35 publications

References 22 publications

The generalized super‐twisting algorithm with adaptive gains

The generalized super‐twisting algorithm with adaptive gains

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

Discrete-Time Position Control for Autonomous Underwater Vehicle under Noisy Conditions

Contact Info

Product

Resources

About