Arrival Trajectory Optimization for Passenger Aircraft using Genetic Algorithms

This work concentrates on the development of an optimization technique which is capable of minimizing the noise impact of an arriving aircraft by optimizing its flight trajectory. Actions needed from pilots to gradually establish the landing configuration are considered because it is expected that the pilot workload throughout this phase should be remained or even reduced compared with the current standard arrival procedures. Therefore, the conventional point-mass equations of motion are reformulated in such a way that the variations of the aerodynamic performance of the aircraft of different configurations can be easily taken into account. A set of independent state variables are chosen to be parameterized with Bernstein polynomials in order to convert the infinite-dimensional optimal control problem into a finite-dimensional parametric optimization problem. The number of awakenings is selected as the performance index and finally written into a function of the parameters introduced by the parameterization process. Genetic algorithms are employed to optimize these parameters within a search domain in order to minimize the number of awakenings while satisfying all constraints on both state and control variables. A number of numerical examples, for a Boeing 747-400 aircraft arriving at an airport with different population distribution situations, are provided to demonstrate the feasibility and effectiveness of the proposed optimization technique. Without loss of generality, this particular technique is also able to deal with a departing aircraft since most of the models are built into replaceable modules