Comparative study on the application of evolutionary optimization techniques to orbit transfer maneuvers

Orbit transfer maneuvers are here considered as benchmark cases for comparing performance of different optimization techniques in the framework of direct methods. Two different classes of evolutionary algorithms, a conventional genetic algorithm and an estimation of distribution method, are compared in terms of performance indices statistically evaluated over a prescribed number of runs. At the same time, two different types of problem representations are considered, a first one based on orbit propagation and a second one based on the solution of Lambert’s problem for direct transfers. In this way it is possible to highlight how problem representation affects the capabilities of the considered numerical approaches

Multi-objective design of robust flight control systems

A multi–objective evolutionary algorithm is used in the framework of H1 control theory to find the controller gains that minimize a weighted combination of the infinite–norm of the sensitivity function (for disturbance attenuation requirements) and complementary sensitivity function (for robust stability requirements). After considering a single operating point for a level flight trim condition of a F-16 fighter aircraft model, two different approaches will then be considered to extend the domain of validity of the control law: 1) the controller is designed for different operating points and gain scheduling is adopted; 2) a single control law is designed for all the considered operating points by multiobjective minimisation. The two approaches are analyzed and compared in terms of effectiveness of the design method and resulting closed loop performance of the system

Orbit Transfer Manoeuvres as a Test Benchmark for Comparison Metrics of Evolutionary Algorithms

In the present paper some metrics for evaluating the performance of evolutionary algorithms are considered. The capabilities of two different optimisation approaches are compared on three test cases, represented by the optimisation of orbital transfer trajectories. The complexity of the problem of ranking stochastic algorithms by means of quantitative indices is analyzed by means of a large sample of runs, so as to derive statistical properties of the indices in order to evaluate their usefulness in understanding the actual algorithm capabilities and their possible intrinsic limitations in providing reliable information

Overplanning Factor in Toyota's Formula for Computing the Number of Kanban

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