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离场航迹降噪优化设计的多目标智能方法
引用本文:王超,王飞.离场航迹降噪优化设计的多目标智能方法[J].西南交通大学学报,2013,26(1):147-153.
作者姓名:王超  王飞
作者单位:南京航空航天大学民航学院;中国民航大学空中交通管理学院
基金项目:国家科技支撑计划资助项目(2011BAH24B08);中央高校基本科研业务费专项资金资助项目(ZXB2011A002)
摘    要:为满足新一代空管系统中离场航迹优化设计时降低噪声影响和减少飞行成本的需要,进行了离场航迹的多目标优化设计方法研究.结合飞行动力学和运动学模型,建立了符合民航飞机离场飞行阶段特征的航迹分段模型,提出了应用状态矩阵和控制矩阵准确表示航迹的数学方法.基于模糊理论建立航迹噪声影响、飞行成本和空中导航约束的满意度评价函数,提出了3种启发式搜索规则和动态领域搜索方法来改进模拟退火算法.仿真结果表明,在绕飞限制空域的前提下,降噪和减少飞行成本的目标无法同时达到最优;离场航迹多目标优化后的总体满意度比仅考虑降噪时提高了4.3%. 

关 键 词:空中交通管理    离场航迹优化    降噪程序    模糊多目标优化    模拟退火
收稿时间:2012-04-09

Multi-objective Intelligent Optimization of Noise Abatement Departure Trajectory
WANG Chao,WANG Fei.Multi-objective Intelligent Optimization of Noise Abatement Departure Trajectory[J].Journal of Southwest Jiaotong University,2013,26(1):147-153.
Authors:WANG Chao  WANG Fei
Institution:1.College of Civil Aviation,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China;2.College of Air Traffic Management,Civil Aviation University of China,Tianjin 300300,China)
Abstract:For the purpose of noise abatement and reducing flight cost during departure trajectory optimal design in the next generation air traffic management system, the multi-objective optimization and design method for departure trajectory was addressed. A segmented trajectory model according with the features of departure flight phases for civil aviation aircraft was established by dynamics and kinematics, and a mathematical method for describing trajectories using state matrix and control matrix was proposed. Several satisfaction evaluation functions about noise impact, flight cost and air navigation constraints were established based on fuzzy theory, and 3 heuristic search rules and a dynamic neighborhood search method were presented to improve the simulated annealing algorithm. The simulation results show that optimal noise abatement and cost reduction cannot be achieved simultaneously on the premise of restricted airspace circumnavigation compared to the trajectory optimized with the single objective of noise abatement, the total satisfaction of the departure trajectory obtained by multi-objective optimization is improved by 4.3%. 
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