Download PDFOpen PDF in browserTrade-Offs in Robust Trajectory Optimization Based on Sensitivity Minimization13 pages•Published: December 11, 2024AbstractRapid developments in aerospace technologies demand reliable procedures to plan ro- bust missions with high safety. To increase safety under uncertainties in model parameters or environmental conditions, multi-objective robust optimization methods via sensitivity minimization can be used. An acceptable trade-off between a nominal operational cost (e.g., time, energy) and robustness is searched for to plan missions that are less prone to disturbances. The presented analysis considers open-loop and closed-loop sensitivity min- imization approaches and utilizes multi-objective optimization to assess the performance and the limitations of both approaches. To solve the multi-objective optimization prob- lems, scalarization techniques are employed using weighted sums and cost bounds. By varying weights and cost bounds, multiple optima can be calculated, resulting in an ap- proximate Pareto front and giving rise to an overview of the trade-off between optimality and robustness of the solutions. The analysis is performed for robust unmanned aerial vehicle (UAV) trajectory optimization minimizing positional sensitivities.Keyphrases: multi objective optimization, robust optimal control, robust trajectory optimization, sensitivity minimization, uncertainties In: Varvara L Turova, Andrey E Kovtanyuk and Johannes Zimmer (editors). Proceedings of 3rd International Workshop on Mathematical Modeling and Scientific Computing, vol 104, pages 1-13.
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