Post by Felipe Chegury Viana on Jan 6, 2009 9:31:06 GMT -5
Dear all,
Here it is a reference on the application of optimization methods in identification problems:
F. A. C. Viana, B .C. O. Maciel, N. S. B. Neto, M. F. Oliveira, V. Steffen Jr, and L. C. S. Goés, "AIRCRAFT LONGITUDINAL STABILITY AND CONTROL DERIVATIVES IDENTIFICATION BY USING LIFE CYCLE AND LEVENBERG-MARQUARDT OPTIMIZATION ALGORITHMS," Inverse Problems in Science and Engineering, Volume 17, Issue 1, pp. 17-34, 2009 (DOI:10.1080/17415970802082773).
In this work, two optimization algorithms are investigated to accomplish the parameter identification of the longitudinal motion of a real aircraft by using the output error method. The first algorithm is the nature-inspired algorithm named the life cycle model, which is a composed strategy based on other heuristics such as genetic algorithms and particle swarm optimization. The second one is the gradient-based technique named Levenberg-Marquardt algorithm, which is a variant of the Gauss-Newton method. Flight test data, performed with a training jet aircraft (Xavante AT-26), were used to feed the output error method. In this context, both optimization algorithms were tested, in solo performance and in a cascade-type approach. Results are reported, aiming to illustrate the success of using the proposed methodology.
You can find more about it on:
fchegury.googlepages.com
All the best,
Felipe Viana
Here it is a reference on the application of optimization methods in identification problems:
F. A. C. Viana, B .C. O. Maciel, N. S. B. Neto, M. F. Oliveira, V. Steffen Jr, and L. C. S. Goés, "AIRCRAFT LONGITUDINAL STABILITY AND CONTROL DERIVATIVES IDENTIFICATION BY USING LIFE CYCLE AND LEVENBERG-MARQUARDT OPTIMIZATION ALGORITHMS," Inverse Problems in Science and Engineering, Volume 17, Issue 1, pp. 17-34, 2009 (DOI:10.1080/17415970802082773).
In this work, two optimization algorithms are investigated to accomplish the parameter identification of the longitudinal motion of a real aircraft by using the output error method. The first algorithm is the nature-inspired algorithm named the life cycle model, which is a composed strategy based on other heuristics such as genetic algorithms and particle swarm optimization. The second one is the gradient-based technique named Levenberg-Marquardt algorithm, which is a variant of the Gauss-Newton method. Flight test data, performed with a training jet aircraft (Xavante AT-26), were used to feed the output error method. In this context, both optimization algorithms were tested, in solo performance and in a cascade-type approach. Results are reported, aiming to illustrate the success of using the proposed methodology.
You can find more about it on:
fchegury.googlepages.com
All the best,
Felipe Viana