Optimal Low-Thrust Orbital Maneuvers via Indirect Swarming Method

Mauro Pontani, Bruce Conway

Research output: Contribution to journalArticlepeer-review


In the last decades, heuristic techniques have become established as suitable approaches for solving optimal control problems. Unlike deterministic methods, they do not suffer from locality of the results and do not require any starting guess to yield an optimal solution. The main disadvantages of heuristic algorithms are the lack of any convergence proof and the capability of yielding only a near optimal solution, if a particular representation for control variables is adopted. This paper describes the indirect swarming method, based on the joint use of the analytical necessary conditions for optimality, together with a simple heuristic technique, namely the particle swarm algorithm. This methodology circumvents the previously mentioned disadvantages of using heuristic approaches, while retaining their advantageous feature of not requiring any starting guess to generate an optimal solution. The particle swarm algorithm is chosen among the different available heuristic techniques, due to its apparent simplicity and the recent promising results reported in the scientific literature. Two different orbital maneuvering problems are considered and solved with great numerical accuracy, and this testifies to the effectiveness of the indirect swarming algorithm in solving low-thrust trajectory optimization problems.

Original languageEnglish (US)
Pages (from-to)272-292
Number of pages21
JournalJournal of Optimization Theory and Applications
Issue number1
StatePublished - Jul 2014


  • Heuristic indirect method
  • Optimal space trajectories
  • Orbital transfers and rendezvous
  • Particle swarm optimization

ASJC Scopus subject areas

  • Control and Optimization
  • Management Science and Operations Research
  • Applied Mathematics

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