Fuel optimal manoeuvres for multiple spacecraft formation reconfiguration using multi-agent optimization

Guang Yang, Qingsong Yang, Vikram Kapila, Daniel Palmer, Ravi Vaidyanathan

Research output: Contribution to journalArticle

Abstract

The Air Force Research Laboratory has identified multiple spacecraft formation flying as an enabling technology for several future space missions. A key benefit of formation flying is the ability to reconfigure the spacecraft formation to achieve different mission objectives. In this paper, generation of fuel optimal manoeuvres for spacecraft formation reconfiguration is modelled and analysed as a multi-agent optimal control problem. Multi-agent optimal control is quite different from the traditional optimal control for single agent. Specifically, in addition to fuel optimization for a single agent, multi-agent optimal control necessitates consideration of task assignment among agents for terminal targets in the optimization process. In this paper, we develop an efficient hybrid optimization algorithm to address such a problem. The proposed multi-agent optimal control methodology uses calculus of variation, task assignment, and parameter optimization at different stages of the optimization process. This optimization algorithm employs a distributed computational architecture. In addition, the task assignment algorithm, which guarantees the global optimal assignment of agents, is constructed using the celebrated principle of optimality from dynamic programming. A communication protocol is developed to facilitate decentralized decision making among agents. Simulation results are included to illustrate the efficacy of the proposed multi-agent optimal control algorithm for fuel optimal spacecraft formation reconfiguration.

Original languageEnglish (US)
Pages (from-to)243-283
Number of pages41
JournalInternational Journal of Robust and Nonlinear Control
Volume12
Issue number2-3
DOIs
StatePublished - Feb 2002

Fingerprint

Reconfiguration
Spacecraft
Optimal Control
Task Assignment
Optimization
Formation Flying
Process Optimization
Optimization Algorithm
Space Missions
Hybrid Optimization
Parameter Optimization
Communication Protocol
Calculus of variations
Hybrid Algorithm
Optimal Algorithm
Decentralized
Control Algorithm
Dynamic Programming
Optimal Control Problem
Efficacy

Keywords

  • Calculus of variation
  • Dynamic programming
  • Genetic algorithm
  • Hybrid optimization
  • Spacecraft formation reconfiguration

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Applied Mathematics

Cite this

Fuel optimal manoeuvres for multiple spacecraft formation reconfiguration using multi-agent optimization. / Yang, Guang; Yang, Qingsong; Kapila, Vikram; Palmer, Daniel; Vaidyanathan, Ravi.

In: International Journal of Robust and Nonlinear Control, Vol. 12, No. 2-3, 02.2002, p. 243-283.

Research output: Contribution to journalArticle

@article{6aabb15fd6fd40c094fe1fddcfa0a075,
title = "Fuel optimal manoeuvres for multiple spacecraft formation reconfiguration using multi-agent optimization",
abstract = "The Air Force Research Laboratory has identified multiple spacecraft formation flying as an enabling technology for several future space missions. A key benefit of formation flying is the ability to reconfigure the spacecraft formation to achieve different mission objectives. In this paper, generation of fuel optimal manoeuvres for spacecraft formation reconfiguration is modelled and analysed as a multi-agent optimal control problem. Multi-agent optimal control is quite different from the traditional optimal control for single agent. Specifically, in addition to fuel optimization for a single agent, multi-agent optimal control necessitates consideration of task assignment among agents for terminal targets in the optimization process. In this paper, we develop an efficient hybrid optimization algorithm to address such a problem. The proposed multi-agent optimal control methodology uses calculus of variation, task assignment, and parameter optimization at different stages of the optimization process. This optimization algorithm employs a distributed computational architecture. In addition, the task assignment algorithm, which guarantees the global optimal assignment of agents, is constructed using the celebrated principle of optimality from dynamic programming. A communication protocol is developed to facilitate decentralized decision making among agents. Simulation results are included to illustrate the efficacy of the proposed multi-agent optimal control algorithm for fuel optimal spacecraft formation reconfiguration.",
keywords = "Calculus of variation, Dynamic programming, Genetic algorithm, Hybrid optimization, Spacecraft formation reconfiguration",
author = "Guang Yang and Qingsong Yang and Vikram Kapila and Daniel Palmer and Ravi Vaidyanathan",
year = "2002",
month = "2",
doi = "10.1002/rnc.684",
language = "English (US)",
volume = "12",
pages = "243--283",
journal = "International Journal of Robust and Nonlinear Control",
issn = "1049-8923",
publisher = "John Wiley and Sons Ltd",
number = "2-3",

}

TY - JOUR

T1 - Fuel optimal manoeuvres for multiple spacecraft formation reconfiguration using multi-agent optimization

AU - Yang, Guang

AU - Yang, Qingsong

AU - Kapila, Vikram

AU - Palmer, Daniel

AU - Vaidyanathan, Ravi

PY - 2002/2

Y1 - 2002/2

N2 - The Air Force Research Laboratory has identified multiple spacecraft formation flying as an enabling technology for several future space missions. A key benefit of formation flying is the ability to reconfigure the spacecraft formation to achieve different mission objectives. In this paper, generation of fuel optimal manoeuvres for spacecraft formation reconfiguration is modelled and analysed as a multi-agent optimal control problem. Multi-agent optimal control is quite different from the traditional optimal control for single agent. Specifically, in addition to fuel optimization for a single agent, multi-agent optimal control necessitates consideration of task assignment among agents for terminal targets in the optimization process. In this paper, we develop an efficient hybrid optimization algorithm to address such a problem. The proposed multi-agent optimal control methodology uses calculus of variation, task assignment, and parameter optimization at different stages of the optimization process. This optimization algorithm employs a distributed computational architecture. In addition, the task assignment algorithm, which guarantees the global optimal assignment of agents, is constructed using the celebrated principle of optimality from dynamic programming. A communication protocol is developed to facilitate decentralized decision making among agents. Simulation results are included to illustrate the efficacy of the proposed multi-agent optimal control algorithm for fuel optimal spacecraft formation reconfiguration.

AB - The Air Force Research Laboratory has identified multiple spacecraft formation flying as an enabling technology for several future space missions. A key benefit of formation flying is the ability to reconfigure the spacecraft formation to achieve different mission objectives. In this paper, generation of fuel optimal manoeuvres for spacecraft formation reconfiguration is modelled and analysed as a multi-agent optimal control problem. Multi-agent optimal control is quite different from the traditional optimal control for single agent. Specifically, in addition to fuel optimization for a single agent, multi-agent optimal control necessitates consideration of task assignment among agents for terminal targets in the optimization process. In this paper, we develop an efficient hybrid optimization algorithm to address such a problem. The proposed multi-agent optimal control methodology uses calculus of variation, task assignment, and parameter optimization at different stages of the optimization process. This optimization algorithm employs a distributed computational architecture. In addition, the task assignment algorithm, which guarantees the global optimal assignment of agents, is constructed using the celebrated principle of optimality from dynamic programming. A communication protocol is developed to facilitate decentralized decision making among agents. Simulation results are included to illustrate the efficacy of the proposed multi-agent optimal control algorithm for fuel optimal spacecraft formation reconfiguration.

KW - Calculus of variation

KW - Dynamic programming

KW - Genetic algorithm

KW - Hybrid optimization

KW - Spacecraft formation reconfiguration

UR - http://www.scopus.com/inward/record.url?scp=0036465996&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0036465996&partnerID=8YFLogxK

U2 - 10.1002/rnc.684

DO - 10.1002/rnc.684

M3 - Article

VL - 12

SP - 243

EP - 283

JO - International Journal of Robust and Nonlinear Control

JF - International Journal of Robust and Nonlinear Control

SN - 1049-8923

IS - 2-3

ER -