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An Optimization Paradigm for Arrival Trajectories using Trajectory Segmentation and State Parameterization

机译:使用轨迹分割和状态参数化的到达轨迹优化范例

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This work demonstrates an optimization paradigm that generates noise abatement trajectories for an aircraft arriving at the designated airport. The fight mechanics and acoustic performance of a Boeing 747-400 aircraft are presented to calculate the noise levels at observation points on the ground. A method that estimates the probability of awakenings and the population distribution within the vicinities of the airport are used to calculate the total number of awakened residents as a reflection of the noise nuisance generated by the arriving aircraft. The infinite-dimensional optimal control problem is converted into a finite-dimensional parameter optimization problem using trajectory segmentation and state parameterization. Genetic algorithms are adopted to solve the converted parameter optimization problem. In the end, a numerical simulation is carried out and the results show that the conversion reduces the complexity of the optimization problem and genetic algorithms are capable of providing optimal trajectories. The results also show that it is possible that the searching does not converge at the globally optimal solution when it is terminated by pre-defined stopping criteria.
机译:这项工作演示了一种优化范例,该范例可以为到达指定机场的飞机生成消减噪声的轨迹。介绍了波音747-400飞机的战斗力和声学性能,以计算地面观察点的噪声水平。用于估计苏醒概率和机场附近人口分布的方法可用于计算苏醒居民总数,以反映到达飞机所产生的噪声扰民。使用轨迹分割和状态参数化将无限维最优控制问题转换为有限维参数优化问题。采用遗传算法解决了参数转换优化问题。最后,进行了数值模拟,结果表明该转换降低了优化问题的复杂性,遗传算法能够提供最优轨迹。结果还表明,当搜索被预定义的停止标准终止时,搜索可能不会收敛于全局最优解。

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