Multi-objective optimal control of re-entry and abort scenarios

Research output: Contribution to conferenceProceeding

1 Citation (Scopus)
36 Downloads (Pure)

Abstract

This paper presents a novel approach to the solution of multi-phase multi-objective optimal control problems. The proposed solution strategy is based on the integration of the Direct Finite Elements Transcription (DFET) 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 two non-linear programming problems: a bi-level and a single level one. In the bi-level problem the outer level, handled byMACS, generates trial control vectors that are then passed to the inner level, which enforces the feasibility of the solution. Feasible control vectors are then returned to the outer level to evaluate the corresponding objective functions. A single level refinement is then run to improve local convergence to the Pareto front. The paper introduces also a novel parameterisation of the controls, using Bernstein polynomials, in the context of the DFET transcription method. The approach is first tested on a known atmospheric re-entry problem and then applied to the analysis of ascent and abort trajectories for a space plane.
Original languageEnglish
DOIs
Publication statusPublished - 8 Jan 2018
EventAIAA SciTech 2018 - Gaylord Palms, Kissimmee, United States
Duration: 8 Jan 201812 Jan 2018
https://scitech.aiaa.org/Register/

Conference

ConferenceAIAA SciTech 2018
CountryUnited States
CityKissimmee
Period8/01/1812/01/18
Internet address

Keywords

  • astronautical engineering
  • trajectory optimisation
  • space missions

Fingerprint Dive into the research topics of 'Multi-objective optimal control of re-entry and abort scenarios'. Together they form a unique fingerprint.

  • Cite this