Lorentz-Augmented Spacecraft Formation Reconfiguration

Sobiesiak, Ludwik A.; Damaren, Christopher J.

doi:10.2514/6.2014-4134

Cited by 7 publications

(8 citation statements)

References 10 publications

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“…This study is beyond the scope of this Note, which focuses on optimal control given a set of prescribed impulse times, and it is part of the future work. Interested readers are referred to [13], which studied the necessary and sufficient optimality conditions for thruster firing times in formation flight applications and will be used as a basis for future work on this magnetic attitude control problem.…”

Section: B Selection Of Impulse Application Times Based On Controllamentioning

confidence: 99%

“…Norm of rotation angle 1.84 × 10 0 8.83 × 10 −1 4.41 × 10 −1 rad a PD: γ 0.001 and k p k v 50; LQR: r c 3 × 10 5 and q c 10 8 ; hybrid LQR: r c 3 × 10 5 , q c 10 8 , r d 10 13 , and q d 10 10 . b N/A denotes "not applicable.…”

Section: Numerical Examplesmentioning

confidence: 99%

“…Continuous and impulsive control torques: solely magnetic (dashed) vs hybrid (solid) LQR (r c 3 × 10 5 and q c 10 8 ; for hybrid, also r d 1013 and q d10 10 ).…”

mentioning

confidence: 99%

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Optimal Combination of Magnetic Attitude Control with Impulsive Thrusting

Vatankhahghadim

Damaren

2016

Journal of Guidance, Control, and Dynamics

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Section: B Selection Of Impulse Application Times Based On Controllamentioning

confidence: 99%

Section: Numerical Examplesmentioning

confidence: 99%

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Optimal Combination of Magnetic Attitude Control with Impulsive Thrusting

Vatankhahghadim

Damaren

2016

Journal of Guidance, Control, and Dynamics

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“…Formation control of swarm systems is widely applied in surveillance and reconnaissance [1]- [3], target searching and localization [4]- [7], telecommunication relay [8], space exploration and source seeking [9], [10]. Main approaches for formation problem include leader-follower [11], behavior approach [12] and virtual structure [13].…”

Section: Introductionmentioning

confidence: 99%

Formation Control of High-Order Swarm Systems With Time-Varying Delays and Switching Interconnections

Zhang

Guo

Xiaohang³

2020

IEEE Access

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The paper investigates the formation control problem for high-order linear swarm systems with limited communications such as time-varying delays and switching interconnections. Firstly, the problem description is given including the dynamics of high-order swarm systems, formation protocol and the definitions of formation maintenance and tracking. Secondly, four formation conditions are derived: the former three are related to formation function, reference trajectory, auxiliary functions and network topology; the fourth one is equivalent to the stability of N-1 time-delay systems. In order to get lower conservative criteria, the Free-weighting Matrices(FWM) approach is employed to analyze the stabilization problem. Finally, the allowance upper bound of delays is calculated through solving the feasible linear matrix inequalities (LMIs). Numerical examples and simulation results are given to demonstrate the effectiveness and benefit on reducing conservativeness of the proposed method. INDEX TERMS Formation tracking, formation maintenance, high-order swarm systems, time-varying delays, switching interconnections.

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“…The capacity of accurate control and collision/obstacle avoidance is desperately required to guarantee the security of all the spacecraft in the SFR, but only limited solutions have been presented for this problem. ()…”

Section: Introductionmentioning

confidence: 99%

Neural network–based reconfiguration control for spacecraft formation in obstacle environments

Zhou

Chen

Xia

et al. 2018

Intl J Robust & Nonlinear

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Summary This paper proposes an adaptive formation reconfiguration control scheme based on the leader‐follower strategy for multiple spacecraft systems. By taking the predesigned desired velocities and the trajectories as reference signals, a set of coordination tracking controllers is constructed by combining the reconstructed dynamic system and the neural network–based reconfiguration algorithm together. To avoid collisions between spacecraft and obstacles during the formation configuration process, the null space–based behavioral control is integrated into the control design. Since the spacecraft dynamics contains unknown nonlinearity and disturbance, it is challenging to make the system robust to uncertainties and improve the control precision simultaneously. To solve this problem, both the adaptive neural network strategy and the finite‐time control theory are employed. Finally, 2 simulation examples are carried out to verify the proposed algorithm, showing that the formation reconfiguration task can be executed successfully while achieving high control precision.

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Lorentz-Augmented Spacecraft Formation Reconfiguration

Cited by 7 publications

References 10 publications

Optimal Combination of Magnetic Attitude Control with Impulsive Thrusting

Optimal Combination of Magnetic Attitude Control with Impulsive Thrusting

Formation Control of High-Order Swarm Systems With Time-Varying Delays and Switching Interconnections

Neural network–based reconfiguration control for spacecraft formation in obstacle environments

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