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

Ricciardi, Lorenzo A. and Maddock, Christie Alisa and Vasile, Massimiliano (2018) Multi-objective optimal control of re-entry and abort scenarios. In: AIAA SciTech 2018, 2018-01-08 - 2018-01-12, Gaylord Palms.

[thumbnail of Ricciardi-etal-AIAA-2018-Multi-objective-optimal-control-of-re-entry-and-abort-scenarios]
Text (Ricciardi-etal-AIAA-2018-Multi-objective-optimal-control-of-re-entry-and-abort-scenarios)
Accepted Author Manuscript

Download (1MB)| Preview


    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.

    ORCID iDs

    Ricciardi, Lorenzo A. ORCID logoORCID:, Maddock, Christie Alisa ORCID logoORCID: and Vasile, Massimiliano ORCID logoORCID:;