Co‐ordination and control of distributed spacecraft systems using convex optimization techniques

By Michael Tillerson, Gökhan Inalhan, Jonathan P. How. 2002

245 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/f6e4c02d9216e3bea6913616710511dd99b0e79b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. Xinfu Liu
2. Ping Lu
3. Binfeng Pan
4. Daniel P. Scharf
5. Fred Y. Hadaegh
6. Scott R. Ploen
7. Arthur G. Richards
8. Soon-Jo Chung

In Computer Networks and Communications

1. Ping Lu
2. Fred Y. Hadaegh
3. Scott R. Ploen
4. Binfeng Pan
5. Daniel P. Scharf
6. Arthur G. Richards
7. Xinfu Liu
8. Wei Ren

Citations in the corpus

• A survey of spacecraft formation flying guidance and control (part 1): guidance (2003, methodology): “trajectories) bidding algorithms [94], linear programming [241, [ 129 ] and dynamic programming [143] have been used.”
• A survey of spacecraft formation flying guidance and control. Part II: control (2004, methodology): “A similar MPC algorithm using linear time-varying models is developed in [44], [46], [110] and references therein.”
• Robust constrained model predictive control (2005, methodology): “The spacecraft MPC problem has been extensively studied for application to spacecraft formation flight [8] and can be posed in linear optimization using Hills equations [35] to model relative spacecraft motion.”
• Survey of convex optimization for aerospace applications (2017, methodology): “Formation reconfiguration with collision-avoidance constraints [28] and the formation control problem of multiple spacecraft [29] were all solved by convex optimization for onboard implementation.”