Robust adaptive trajectory tracking control of underactuated autonomous underwater vehicles with prescribed performance

Li, Jian; Du, Jialu; Sun, Yuqing; Lewis, Frank L.

doi:10.1002/rnc.4659

Cited by 94 publications

(53 citation statements)

References 43 publications

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“…wheref 1 (ē 1 ,ē 2 ) = −k 1ē1 −k 2ē ι1 1 andf 2 (ē 1 ,ē 2 ) = −k 4ē1 − k 5ēῑ 1 1 +ē f . Noting that ι 2 > 1,ῑ 2 = 2ι 2 − 1, one can see that the following system (65) is homogeneous with degree l ∞ = 1 with respect to (d 1 , d 2 ), where…”

Section: Proof the Theoremmentioning

confidence: 99%

“…Autonomous underwater vehicles (AUVs) have played important roles in various underwater applications, e.g., ocean sampling, oceanographic survey and inspection, seafloor mapping and modeling, submarine mine neutralization, offshore oil and gas exploration [1,9,10,26,28]. To improve efficiency and to extend task capacity, many tasks in these applications involve collaboration of multiple AUVs in a certain formation [2,3,4,5,6,7,11,19].…”

Section: Introductionmentioning

confidence: 99%

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Fixed-time Leader-Following Formation Control of AUVs Without Velocity Measurements

Zhang

Guo

2021

Preprint

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This paper is concerned with formation control of autonomous underwater vehicles (AUVs), focusing on improving system convergence speed and overcoming velocity measurement limitation. By employing the fixed-time control theory and command filtering technique, a full state feedback formation algorithm is proposed, which makes the follower AUV track the leader in a given time with all signals in the system globally practically stabilized in fixed time. To avoid degraded control performance due to inaccurate velocity measurement, a fixed-time convergent observer is designed to estimate the velocity of AUVs. We then give an observer-based fixed-time control method, with which acceptable formation tracking performance can be achieved in fixed time without velocity measurement. The effectiveness and performance of the proposed method is demonstrated by numerical simulations.

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Section: Proof the Theoremmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fixed-time Leader-Following Formation Control of AUVs Without Velocity Measurements

Zhang

Guo

2021

Preprint

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“…However, their method is not adaptive to parameter uncertainties. The author of [ 24 ] proposed a novel robust adaptive trajectory tracking control scheme with prescribed performance for underactuated autonomous underwater vehicles (AUVs) subject to unknown dynamic parameters and disturbances. However, measurement noises are not considered in the simulation.…”

Section: Introductionmentioning

confidence: 99%

Antidisturbance Control for AUV Trajectory Tracking Based on Fuzzy Adaptive Extended State Observer

Kang

Rong

Chou

2020

Sensors

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In this paper, an output-feedback fuzzy adaptive dynamic surface controller (FADSC) based on fuzzy adaptive extended state observer (FAESO) is proposed for autonomous underwater vehicle (AUV) systems in the presence of external disturbances, parameter uncertainties, measurement noises and actuator faults. The fuzzy logic system is incorporated into both the observers and controllers to improve the adaptability of the entire system. The dynamics of the AUV system is established first, considering the external disturbances and parameter uncertainties. Based on the dynamic models, the ESO, combined with a fuzzy logic system tuning the observer bandwidth, is developed to not only adaptively estimate both system states and the lumped disturbances for the controller, but also reduce the impact of measurement noises. Then, the DSC, together with fuzzy logic system tuning the time constant of the low-pass filter, is designed using estimations from the FAESO for the AUV system. The asymptotic stability of the entire system is analyzed through Lyapunov’s direct method in the time domain. Comparative simulations are implemented to verify the effectiveness and advantages of the proposed method compared with other observers and controllers considering external disturbances, parameter uncertainties and measurement noises and even the actuator faults that are not considered in the design process. The results show that the proposed method outperforms others in terms of tracking accuracy, robustness and energy consumption.

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“…However, the stochastic noises always exist in the measurement signals. The restrain of stochastic disturbance signals are necessary for the trajectory tracking in several kinds of systems, such as the underwater vehicle systems 14,15 and missile interception systems 16 . Kalman filters is often applied to reduce the noises effects in the output feedback tracking systems, but the limitations are the requirement of system models information.…”

Section: Introductionmentioning

confidence: 99%

Sliding mode tracking control using finite‐time differentiator in high‐orders nonlinear systems with output stochastic signals

Yan

2020

Intl J Robust & Nonlinear

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This article presents sliding mode tracking control using finite-time nonlinear differentiator (FND) to the high-orders nonlinear systems that states are unknown and the output measurement signals involves stochastic disturbances. The FND using singular perturbation technique is applied to estimate the unknown states in the tracking system, and not rely on the model information under the condition of output stochastic signals. The stochastic noises involved in the output measurement signals are restrained sufficiently by the FNDs. The design of sliding mode tracking controller using FND reduces the chattering phenomenon efficiently. The analysis of systems stability and differentiator robustness is demonstrated. The comparative simulation results show that the sliding mode controller using FND track the desired trajectory in high accuracy with tracking errors fast convergence.

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Robust adaptive trajectory tracking control of underactuated autonomous underwater vehicles with prescribed performance

Cited by 94 publications

References 43 publications

Fixed-time Leader-Following Formation Control of AUVs Without Velocity Measurements

Fixed-time Leader-Following Formation Control of AUVs Without Velocity Measurements

Antidisturbance Control for AUV Trajectory Tracking Based on Fuzzy Adaptive Extended State Observer

Sliding mode tracking control using finite‐time differentiator in high‐orders nonlinear systems with output stochastic signals

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