Abstract
Morphing technologies can improve the flight performance and energy efficiency of hypersonic aircraft. However, conventional trajectory optimization methods are difficult to meet the trajectory optimization requirements with multiple constraints and multiple performance indicators, which limits the performance of hypersonic morphing aircraft. In this paper, a hybrid multiobjective evolutionary algorithm based on decomposition (h-MOEA/D) is developed to solve a multiobjective reentry trajectory optimization problem for hypersonic telescopic wing morphing aircraft. According to the different morphing states of the morphing aircraft, an aerodynamic model is first built using Missile Datcom. An optimization model for the reentry trajectory is then established. Next, based on the MOEA/D framework, the h-MOEA/D components are designed or improved. Chebyshev polynomials are used to parameterize the control variables. Normal boundary intersection (NBI) style Tchebycheff approach and niche-guided scheme are applied to guarantee the uniformity and the diversity for the solution set. The angle-based constrained dominance principle (ACDP) is improved to handle complex constraints. Finally, simulation results show the feasibility and competitiveness of the proposed method compared with other advanced algorithms.
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