Cooperative Orbital Control of Multiple Satellites via Consensus

Zhang, Hao; Gurfil, Pini

doi:10.1109/taes.2018.2808118

Cited by 44 publications

(14 citation statements)

References 36 publications

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“…Properties of the RNNFL-FTFTCC for the uncertain formation controlled system are addressed as follows. Theorem 1: Consider the dynamics of ( 7) and (8). The lumped uncertainties of ( 22), which are approximated by the RNNs in (15) and their weight matrices are learned by the adaptive law of ( 23)- (30).…”

Section: Stability Analysismentioning

confidence: 99%

Recurrent Neural Network With Fractional Learning-Based Fixed-Time Formation Tracking Constrained Control for a Group of Quadrotors

et al. 2021

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In this paper, each agent is modeled by the mechanical motion dynamics with the velocity transformation between quadrotor and world coordinates such that trajectory planning and obstacle avoidance are easily accomplished. It is assumed that at least one follower tracks the leader with a specific position, and the other followers maintain the relative position among each other or the leader. If obstacles hinder the motion of the original formation, a piecewise straight-line formation is employed to avoid these obstacles. To fulfill these tasks under the uncertain dynamics, the recurrent neural network with fractional learning-based fixed-time formation tracking constrained control (RNNFL-FTFTCC) is designed by nonlinear filtering error with dynamic fraction order, time-varying switching gain, and recurrent neural network learning compensation of dynamic lumped uncertainties in each quadrotor. The simulations with the initial formation error, the formation change in a narrow space, and the target point approach validate the effectiveness and robustness of the proposed formation control. Moreover, the comparisons among nonadaptive, RNN, and multilayer perceptron network (MLPN) compensations confirm the effectiveness and efficiency of fractional learning.

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Section: Stability Analysismentioning

confidence: 99%

Recurrent Neural Network With Fractional Learning-Based Fixed-Time Formation Tracking Constrained Control for a Group of Quadrotors

et al. 2021

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“…where means the Laplacian matrix of graph , and . According to (6), the updating law (4) can be rewritten as…”

Section: Problem Descriptionmentioning

confidence: 99%

“…In recent decades, the distributed coordination control has attracted a considerable interest in research of multi-agent systems, which has broad applications in social, industrial and national defense fields [1], such as unmanned air vehicles formation control [2,3], distributed sensor network [4], robot coordination control [5,6], attitude alignment of clusters of satellite [7,8], traffic congestion control [9,10], and so on. In multi-agent systems, the consensus control is an important problem to realize distributed coordination control.…”

Section: Introductionmentioning

confidence: 99%

Open-loop and closed-loop Dα-type iterative learning control for fractional-order linear multi-agent systems with state-delays

Lan

Zhao

et al. 2021

J. of Syst. Eng. Electron.

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This study focuses on implementing consensus tracking using both open-loop and closed-loop-type iterative learning control (ILC) schemes, for fractional-order multi-agent systems (FOMASs) with state-delays. The desired trajectory is constructed by introducing a virtual leader, and the fixed communication topology is considered and only a subset of followers can access the desired trajectory. For each control scheme, one controller is designed for one agent individually. According to the tracking error between the agent and the virtual leader, and the tracking errors between the agent and neighboring agents during the last iteration (for open-loop scheme) or the current running (for closed-loop scheme), each controller continuously corrects the last control law by a combination of communication weights in the topology to obtain the ideal control law. Through the rigorous analysis, sufficient conditions for both control schemes are established to ensure that all agents can achieve the asymptotically consistent output along the iteration axis within a finite-time interval. Sufficient numerical simulation results demonstrate the effectiveness of the control schemes, and provide some meaningful comparison results.

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“…the external disturbances. By combining (2) and 3, one can obtain that the Lagrangian expression with respect to MRPs as:…”

Section: B Model Descriptionmentioning

confidence: 99%

Robust Satellite Formation Flying Controller Design Subject to Communication Delays

2020

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A robust control method is proposed to address the satellite formation flying problem subject to communication delays. Each satellite dynamics involves nonlinear dynamics, parametric uncertainties, and external disturbances. Communications between neighboring satellites are affected by time delays. For each satellite, the resulted controller includes a translational controller to maintain the desired formation pattern, and a rotational controller to align the attitude. Theoretical analysis and simulation results are provided to verify the advantages of the proposed formation flying controller.

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Cooperative Orbital Control of Multiple Satellites via Consensus

Cited by 44 publications

References 36 publications

Recurrent Neural Network With Fractional Learning-Based Fixed-Time Formation Tracking Constrained Control for a Group of Quadrotors

Recurrent Neural Network With Fractional Learning-Based Fixed-Time Formation Tracking Constrained Control for a Group of Quadrotors

Open-loop and closed-loop Dα-type iterative learning control for fractional-order linear multi-agent systems with state-delays

Robust Satellite Formation Flying Controller Design Subject to Communication Delays

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