Landing gear identification using heuristic methods

[fche...@gmail.com]

Dear all,

Here it is a reference on the application of heuristic optimization
methods to the identification of a landing gear model:

F. A. C. Viana, V. Steffen Jr., M. A. X. Zanini, S. A. Magalhães and
L. C. S. Góes, "IDENTIFICATION OF A NON-LINEAR LANDING GEAR MODEL
USING NATURE-INSPIRED OPTIMIZATION," Shock and Vibration, Volume 15,
Number 3-4, pp. 205-479, 2008, (ISSN: 1070-9622 and 1875-9203 for
printed and online versions, respectively).

This work deals with the application of a nature-inspired optimization
technique to solve an inverse problem represented by the
identification of an aircraft landing gear model. The model is
described in terms of the landing gear geometry, internal volumes and
areas, shock absorber travel, tire type, and gas and oil
characteristics of the shock absorber. The solution to this inverse
problem can be obtained by using classical gradient-based optimization
methods. However, this is a difficult task due to the existence of
local minima in the design space and the requirement of an initial
guess. These aspects have motivated the authors to explore a nature-
inspired approach using a method known as LifeCycle Model. In the
present formulation two nature-based methods, namely the Genetic
Algorithms and the Particle Swarm Optimization were used. An
optimization problem is formulated in which the objective function
represents the difference between the measured characteristics of the
system and its model counterpart. The polytropic coefficient of the
gas and the damping parameter of the shock absorber are assumed as
being unknown: they are considered as design variables. As an
illustration, experimental drop test data, obtained under zero
horizontal speed, were used in the non-linear landing gear model
updating of a small aircraft.

You can find more about it on:
http://fchegury.110mb.com/publications.html


All the best,
Felipe