Multi-objective optimal control of ascent trajectories for launch vehicles

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

2 Citations (Scopus)

Abstract

This paper presents a novel approach to the solution of multi-objective optimal control problems. The proposed solution strategy is based on the integration of the Direct Finite Elements Transcription method, to transcribe dynamics and objectives, with a memetic strategy called Multi Agent Collaborative Search (MACS). The original multi-objective optimal control problem is reformulated as a bi-level nonlinear programming problem. In the outer level, handled by MACS, trial control vectors are generated and passed to the inner level, which enforces the solution feasibility. Solutions are then returned to the outer level to evaluate the feasibility of the corresponding objective functions, adding a penalty value in the case of infeasibility. An optional single level refinement is added to improve the ability of the scheme to converge to the Pareto front. The capabilities of the proposed approach will be demonstrated on the multi-objective optimisation of ascent trajectories of launch vehicles.

LanguageEnglish
Title of host publicationAIAA/AAS Astrodynamics Specialist Conference, 2016
Place of PublicationReston, VA
Number of pages14
DOIs
Publication statusPublished - 13 Sep 2016
EventAIAA/AAS Astrodynamics Specialist Conference, 2016 - Long Beach, United States
Duration: 13 Sep 201616 Sep 2016

Publication series

NameAIAA Space Forum
PublisherAmerican Institute of Aeronautics and Astronautics

Conference

ConferenceAIAA/AAS Astrodynamics Specialist Conference, 2016
CountryUnited States
CityLong Beach
Period13/09/1616/09/16

Fingerprint

ascent trajectories
launch vehicles
Launch vehicles
optimal control
Trajectories
directional control
nonlinear programming
Nonlinear programming
Transcription
Multiobjective optimization
penalties
optimization

Keywords

  • multi-objective optimal control
  • control problems
  • solution strategies
  • direct finite elements transcription method
  • multi agent collaborative search
  • ascent trajectories
  • launch vehicles

Cite this

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title = "Multi-objective optimal control of ascent trajectories for launch vehicles",
abstract = "This paper presents a novel approach to the solution of multi-objective optimal control problems. The proposed solution strategy is based on the integration of the Direct Finite Elements Transcription method, to transcribe dynamics and objectives, with a memetic strategy called Multi Agent Collaborative Search (MACS). The original multi-objective optimal control problem is reformulated as a bi-level nonlinear programming problem. In the outer level, handled by MACS, trial control vectors are generated and passed to the inner level, which enforces the solution feasibility. Solutions are then returned to the outer level to evaluate the feasibility of the corresponding objective functions, adding a penalty value in the case of infeasibility. An optional single level refinement is added to improve the ability of the scheme to converge to the Pareto front. The capabilities of the proposed approach will be demonstrated on the multi-objective optimisation of ascent trajectories of launch vehicles.",
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author = "Ricciardi, {Lorenzo A.} and Massimiliano Vasile and Federico Toso and Maddock, {Christie Alisa}",
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Ricciardi, LA, Vasile, M, Toso, F & Maddock, CA 2016, Multi-objective optimal control of ascent trajectories for launch vehicles. in AIAA/AAS Astrodynamics Specialist Conference, 2016., 2016-5669, AIAA Space Forum, Reston, VA, AIAA/AAS Astrodynamics Specialist Conference, 2016, Long Beach, United States, 13/09/16. https://doi.org/10.2514/6.2016-5669

Multi-objective optimal control of ascent trajectories for launch vehicles. / Ricciardi, Lorenzo A.; Vasile, Massimiliano; Toso, Federico; Maddock, Christie Alisa.

AIAA/AAS Astrodynamics Specialist Conference, 2016. Reston, VA, 2016. 2016-5669 (AIAA Space Forum).

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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N2 - This paper presents a novel approach to the solution of multi-objective optimal control problems. The proposed solution strategy is based on the integration of the Direct Finite Elements Transcription method, to transcribe dynamics and objectives, with a memetic strategy called Multi Agent Collaborative Search (MACS). The original multi-objective optimal control problem is reformulated as a bi-level nonlinear programming problem. In the outer level, handled by MACS, trial control vectors are generated and passed to the inner level, which enforces the solution feasibility. Solutions are then returned to the outer level to evaluate the feasibility of the corresponding objective functions, adding a penalty value in the case of infeasibility. An optional single level refinement is added to improve the ability of the scheme to converge to the Pareto front. The capabilities of the proposed approach will be demonstrated on the multi-objective optimisation of ascent trajectories of launch vehicles.

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Ricciardi LA, Vasile M, Toso F, Maddock CA. Multi-objective optimal control of ascent trajectories for launch vehicles. In AIAA/AAS Astrodynamics Specialist Conference, 2016. Reston, VA. 2016. 2016-5669. (AIAA Space Forum). https://doi.org/10.2514/6.2016-5669