Abstract
This paper addresses the solution of optimal control problems with multiple and possibly conflicting objective functions. The solution strategy is based on the integration of Direct Finite Elements in Time (DFET) transcription into the Multi Agent Collaborative Search (MACS) framework. Multi Agent Collaborative Search is a memetic algorithm in which a population of agents performs a set of individual and social actions looking for the Pareto front. Direct Finite Elements in Time transcribe an optimal control problem into a constrained Non-linear Programming Problem (NLP) by collocating states and controls on spectral bases. MACS operates directly on the NLP problem and generates nearly-feasible trial solutions which are then submitted to a NLP solver. If the NLP solver converges to a feasible solution, an updated solution for the control parameters is returned to MACS, along with the corresponding value of the objective functions. Both the updated guess and the objective function values will be used by MACS to generate new trial solutions and converge, as uniformly as possible, to the Pareto front. To demonstrate the applicability of this strategy, the paper presents the solution of the multi-objective extensions of two well-known space related optimal control problems: the Goddard Rocket problem, and the maximum energy orbit rise problem.
Original language | English |
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Title of host publication | 2016 IEEE Congress on Evolutionary Computation, (CEC) |
Place of Publication | Piscataway |
Publisher | IEEE |
Pages | 869-876 |
Number of pages | 8 |
ISBN (Print) | 9781509006236 |
DOIs | |
Publication status | Published - 21 Nov 2016 |
Event | 2016 IEEE Congress on Evolutionary Computation, CEC 2016 - Vancouver, Vancouver, Canada Duration: 24 Jul 2016 → 29 Jul 2016 http://www.wcci2016.org/ |
Conference
Conference | 2016 IEEE Congress on Evolutionary Computation, CEC 2016 |
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Abbreviated title | IEEE CEC 2016 |
Country/Territory | Canada |
City | Vancouver |
Period | 24/07/16 → 29/07/16 |
Internet address |
Keywords
- optimal control
- optimisation
- aerospace engineering
- space access
- launch vehicle
- finite elements in time (FET)
- collaboration
- programming
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Christie Maddock, PhD, FHEA, MRAeS
- Mechanical And Aerospace Engineering - Senior Lecturer
- Ocean, Air and Space
Person: Academic