Consensus Formation Tracking for Multiple AUV Systems Using Distributed Bioinspired Sliding Mode Control

Yan, Tao; Xu, Zhe; Yang, Simon X.

doi:10.1109/tiv.2022.3175647

Cited by 42 publications

(21 citation statements)

References 36 publications

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“…In this section, we validate the performance of the proposed algorithm. The dynamic model of each vehicle is described as in (9), where the parameters are selected as in Table I [16].…”

Section: Resultsmentioning

confidence: 99%

“…(60) Note that the above parameters are selected to be quite similar to the parameters used in [16] to facilite the comparison later. However, in this experiment, the disturbance term ( 60) is modeled to be more severe to include both environmental disturbances and model uncertainties.…”

Section: Resultsmentioning

confidence: 99%

“…6×6 and the Jacobian matrix J i (η 2,i ) can be found in [16]. d i (t, η i , υ i ) ∈ 6×1 denotes the lumped model uncertainty and disturbance component in the system.…”

Section: Dynamics Of Auvs and Control Objectivementioning

confidence: 99%

“…Despite the advantages of high robustness, SMC generates high chattering, which can cause significant oscillations within the operation of mechanical systems. To reduce the chattering for SMC, a distributed bio-inspired SMC has been proposed for multiple AUVs [16]. However, the conventional SMCs do not provide finite time/fixed time convergence for the systems.…”

Section: Introductionmentioning

confidence: 99%

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Distributed Fixed-Time Consensus Control for Multiple AUV Systems with Input Saturations

Van¹,

Sun²,

Mcllvanna³

et al. 2023

Preprint

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This study proposes a new distributed control method based on an adaptive fuzzy control for multiple collaborative autonomous underwater vehicles (AUVs) to track a desired formation shape within a fixed time. First, a formation control protocol based on a fixed-time backstepping sliding mode control is designed, in which the consensus cooperative tracking errors for each AUV will be formulated. Then, to compensate for the saturated control torques, an adaptive auxiliary variable is introduced. Finally, a fixed-time adaptive fuzzy logic control (FLC) is derived to approximate the unknown dynamics, in which the adaptive laws of the FLC is derived such that the adaptive signals and errors can be convergent within a fixed time. The fixed time convergence is desired in practice because it provides an exciting property that the global convergence of the whole system is independent with the initial states of the AUVs. The computer simulation results for a consensus formation control of four AUVs show that the proposed formation control can provide high tracking performance with lower and smoother control efforts.

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“…In this section, we validate the performance of the proposed algorithm. The dynamic model of each vehicle is described as in (9), where the parameters are selected as in Table I [16].…”

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

“…6×6 and the Jacobian matrix J i (η 2,i ) can be found in [16]. d i (t, η i , υ i ) ∈ 6×1 denotes the lumped model uncertainty and disturbance component in the system.…”

Section: Dynamics Of Auvs and Control Objectivementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Distributed Fixed-Time Consensus Control for Multiple AUV Systems with Input Saturations

Van¹,

Sun²,

Mcllvanna³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Towards this end, higher-order SMC techniques were proposed to attenuate the high-frequency chattering to make SMC schemes more practical, and such methods were also applied to the control problems of AUVs tracking and formation [134][135][136][137][138] . To completely eliminate the chattering while obtaining good robustness, the authors developed a distributed neuro-dynamics-based sliding mode controller for the consensus formation tracking control of a group of AUVs [139] . In addition to the static robust control schemes that are considered more conservative, there are numerous disturbance observer-based controllers used for AUVs motion and formation control, which behave more actively in addressing the disturbances and hydrodynamic coefficients [140][141][142][143][144][145] .…”

Section: Adverse Underwater Environmentsmentioning

confidence: 99%

Formation control of multiple autonomous underwater vehicles: a review

Yan¹,

Xu²,

Yang³

et al. 2023

Intell Robot

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This paper presents a comprehensive overview of recent developments in formation control of multiple autonomous underwater vehicles (AUVs). Several commonly used structures and approaches for formation coordination are listed, and the advantages and deficiencies of each method are discussed. The difficulties confronted in synthesis of a practical AUVs formation system are clarified and analyzed in terms of the characteristic of AUVs, adverse underwater environments, and communication constraints. The state-of-the-art solutions available for addressing these challenges are reviewed comprehensively. Based on that, a brief discussion is made, and a list of promising future work is pointed out, which aims to be helpful for the further promotion of AUVs formation applications.

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