An optimization paradigm for arrival trajectories usingtrajectory segmentation and state parameterization

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 distributionwithin 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.