The paper presents the study on the ascent trajectory optimization problem accomplished during a research activity on Multidisciplinary Design Optimization (MDO) for launch vehicles, undertaken by Universität Bremen and Politecnico di Milano within ESA’s PRESTIGE PhD program. The trajectory optimization problem represents just a part of the overall MDO process when the control variables are treated on the same level of the design variables in a black-box optimization approach. However, given an efficient problem formulation and optimization strategy, it can be inserted as a nested optimization loop in the overall process of design optimization of the entire launch vehicle. In order to tackle Mixed Integer Non Linear Programming problems required by a MDO framework, several optimization strategies have been integrated: from global and stochastic to local and deterministic, from single to multiobjective. The description of the optimization strategies is followed by an overview of the ascent trajectory model, constituted of 3-DoF simulation, a phase structure including standard guidance laws for the generation of first guess pitch and yaw profiles, variable thrust, coast phases, and definition of path and final orbit constraints. Results are presented for several test cases (Ariane 5 and VEGA to GTO and LEO orbits), with a comparative analysis of those obtained with global and local optimization approaches, and with different formulations of the problem. Finally, lessons learned on particular modeling aspects that allow improving the problem’s smoothness for more efficient and robust local optimization are discussed.
Global and Local Optimization Approaches for Launch Vehicles Ascent Trajectory Design
CASTELLINI, FRANCESCO;LAVAGNA, MICHÈLE
2011-01-01
Abstract
The paper presents the study on the ascent trajectory optimization problem accomplished during a research activity on Multidisciplinary Design Optimization (MDO) for launch vehicles, undertaken by Universität Bremen and Politecnico di Milano within ESA’s PRESTIGE PhD program. The trajectory optimization problem represents just a part of the overall MDO process when the control variables are treated on the same level of the design variables in a black-box optimization approach. However, given an efficient problem formulation and optimization strategy, it can be inserted as a nested optimization loop in the overall process of design optimization of the entire launch vehicle. In order to tackle Mixed Integer Non Linear Programming problems required by a MDO framework, several optimization strategies have been integrated: from global and stochastic to local and deterministic, from single to multiobjective. The description of the optimization strategies is followed by an overview of the ascent trajectory model, constituted of 3-DoF simulation, a phase structure including standard guidance laws for the generation of first guess pitch and yaw profiles, variable thrust, coast phases, and definition of path and final orbit constraints. Results are presented for several test cases (Ariane 5 and VEGA to GTO and LEO orbits), with a comparative analysis of those obtained with global and local optimization approaches, and with different formulations of the problem. Finally, lessons learned on particular modeling aspects that allow improving the problem’s smoothness for more efficient and robust local optimization are discussed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.