Virtual leader based path tracking control for Multi-UUV considering sampled-data delays and packet losses

Yan, Zheping; Yang, Zewen; Pan, Xiaoli; Zhang, Jiajia; Wu, Di

doi:10.1016/j.oceaneng.2020.108065

Cited by 24 publications

(4 citation statements)

References 30 publications

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“…, σ nj (p)] ⊤ . Proof: According to the Cora-GP algorithm (6), it is trivial to show the j-th dimensional unknown f (•) prediction error |∆f ij (p)| := |f j (p) − μij (p)| with the property in (7) is bounded by…”

Section: B Cooperative Learning With Correlation-aware Gpsmentioning

confidence: 99%

“…Accomplishing intricate tasks in MASs often involves extensive investigations of tracking control protocols, as evident in numerous studies [4]- [7]. Many of these approaches assume a prior understanding of system dynamics and environmental disturbances, which poses a significant constraint when dealing with uncertain MASs operating in unfamiliar environments.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Distributed Learning Consensus Control for Unknown Nonlinear Multi-Agent Systems based on Gaussian Processes

Yang

Sosnowski

Liu

et al. 2021

2021 60th IEEE Conference on Decision and Control (CDC)

Self Cite

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This work presents an innovative learning-based approach to tackle the tracking control problem of Euler-Lagrange multi-agent systems with partially unknown dynamics operating under switching communication topologies. The approach leverages a correlation-aware cooperative algorithm framework built upon Gaussian process regression, which adeptly captures inter-agent correlations for uncertainty predictions. A standout feature is its exceptional efficiency in deriving the aggregation weights achieved by circumventing the computationally intensive posterior variance calculations. Through Lyapunov stability analysis, the distributed control law ensures bounded tracking errors with high probability. Simulation experiments validate the protocol's efficacy in effectively managing complex scenarios, establishing it as a promising solution for robust tracking control in multi-agent systems characterized by uncertain dynamics and dynamic communication structures.

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Section: B Cooperative Learning With Correlation-aware Gpsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Distributed Learning Consensus Control for Unknown Nonlinear Multi-Agent Systems based on Gaussian Processes

Yang

Sosnowski

Liu

et al. 2021

2021 60th IEEE Conference on Decision and Control (CDC)

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, it is difficult for a single AUV to complete complex or high-disk tasks with low cost and fewer sensors, especially in the presence of uncertainty, incomplete information, and distributed control. To make up for the inadequacy of a single AUV, the AUV group is used for many marine tasks ( Sun et al, 2020 ; Yan et al, 2020 ). AUV group faces the problem of area coverage in the process of carrying out tasks such as seafloor sonar array exploration, resource exploration, and ocean hydrographic environment exploration ( Antonelli and Antonelli, 2014 ; Wadoo and Kachroo, 2017 ; Yan et al, 2019 ; Xin et al, 2021 ; Yang et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

A Static Area Coverage Algorithm for Heterogeneous AUV Group Based on Biological Competition Mechanism

Guo

Chen

Zhao

et al. 2022

Front. Bioeng. Biotechnol.

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Static area coverage of the heterogeneous autonomous underwater vehicle (AUV) group is widely used in many fields. With the use of the centroidal Voronoi tessellation (CVT) algorithm, the coverage problem can be resolved. However, the CVT method, which is optimized with the location evaluation function, cannot consider the heterogeneity of AUVs when the group performs the static area coverage task and will cause a waste of resources. In this paper, considering different AUVs’ task requirements and detection capabilities comprehensively, we propose a coverage control optimization algorithm based on a biological competition mechanism (BCM). By using BCM, the task load of each AUV can be distributed consistently. In addition, we provide strict proof of the consistency of the algorithm based on the Lyapunov method. Simulation results demonstrate that with the proposed algorithm, the location distribution of the heterogeneous AUV group for area coverage is close to the balanced value, and the performance is better than the CVT algorithm for static area coverage.

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“…To make the research closer to the actual engineering, the continuous-time dynamics equation of AUV is required to be derived as the discrete-time formulation, and design the coordination controller in discrete time to tackle the formation control problem of multiple AUVs. 4,22,23 For the coordinated consensus control of multiple agent system in discrete-time domain, there has also been a lot of researching achievements in some aspects, such as the consensus with time delay, 24,25 the consensus under switching communication topologies, [26][27][28] etc.…”

Section: Introductionmentioning

confidence: 99%

Discrete-time event-based coordinated formation control of multiple AUVs with time-varying delay and alterable topology

Zeng

2022

Proceedings of the Institution of Mechanical Engineers, Part I:

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This article considers the issue of event-based coordinated formation control for multiple autonomous underwater vehicles subject to time-varying communication delay and alterable topology under discretized time. First, to derive the dynamics model in the discrete-time domain, the state feedback technique and the forward difference approach are employed for the continuous-time nonlinear model of autonomous underwater vehicle. For each follower, the event-triggering function and the coordinated controller are designed, using only discrete-time state information of the leader or other followers. Under this control strategy, the controller will not be updated at each discrete-time instant. Then, the coordinated control problem is turned into the asymptotic stability problem of the multi-autonomous underwater vehicle system. According to the stability analysis, sufficient conditions are presented for successfully completing the formation assignment without and with time-varying delay, respectively. Finally, by performing some numerical simulation experiments, the efficacity of our proposed event-based controller and the correctness of the main theoretical results are demonstrated. The impact of different communication conditions on the control system is revealed by the comparison of several scenarios.

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Virtual leader based path tracking control for Multi-UUV considering sampled-data delays and packet losses

Cited by 24 publications

References 30 publications

Distributed Learning Consensus Control for Unknown Nonlinear Multi-Agent Systems based on Gaussian Processes

Distributed Learning Consensus Control for Unknown Nonlinear Multi-Agent Systems based on Gaussian Processes

A Static Area Coverage Algorithm for Heterogeneous AUV Group Based on Biological Competition Mechanism

Discrete-time event-based coordinated formation control of multiple AUVs with time-varying delay and alterable topology

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