Identification of a Non-Linear Landing Gear Model Using Nature-Inspired Optimization
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...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2008-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2008/246271 |
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| _version_ | 1832556445439098880 |
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| author | Felipe A.C. Viana Valder Steffen Jr. Marcelo A.X. Zanini Sandro A. Magalhães Luiz C.S. Góes |
| author_facet | Felipe A.C. Viana Valder Steffen Jr. Marcelo A.X. Zanini Sandro A. Magalhães Luiz C.S. Góes |
| author_sort | Felipe A.C. Viana |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-f979502be1df4a468914d0ed11246af5 |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2008-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-f979502be1df4a468914d0ed11246af52025-02-03T05:45:25ZengWileyShock and Vibration1070-96221875-92032008-01-01153-425727210.1155/2008/246271Identification of a Non-Linear Landing Gear Model Using Nature-Inspired OptimizationFelipe A.C. Viana0Valder Steffen Jr.1Marcelo A.X. Zanini2Sandro A. Magalhães3Luiz C.S. Góes4School of Mechanical Engineering, Federal University of Uberlândia, Av. João Naves de Ávila 2121, Campus Santa Mônica, 38400-902, Uberlândia, MG, BrazilSchool of Mechanical Engineering, Federal University of Uberlândia, Av. João Naves de Ávila 2121, Campus Santa Mônica, 38400-902, Uberlândia, MG, BrazilEmbraer – Empresa Brasileira de Aeronautica S.A., Av. Brigadeiro Faria Lima 2170, 12227-901, São José dos Campos, SP, BrazilEmbraer – Empresa Brasileira de Aeronautica S.A., Av. Brigadeiro Faria Lima 2170, 12227-901, São José dos Campos, SP, BrazilDepartment of Mechanical-Aeronautical Engineering, Instituto Tecnológico de Aeronáutica, Praça Marechal Eduardo Gomes 50, 12228-900, Sao José dos Campos, SP, BrazilThis 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.http://dx.doi.org/10.1155/2008/246271 |
| spellingShingle | Felipe A.C. Viana Valder Steffen Jr. Marcelo A.X. Zanini Sandro A. Magalhães Luiz C.S. Góes Identification of a Non-Linear Landing Gear Model Using Nature-Inspired Optimization Shock and Vibration |
| title | Identification of a Non-Linear Landing Gear Model Using Nature-Inspired Optimization |
| title_full | Identification of a Non-Linear Landing Gear Model Using Nature-Inspired Optimization |
| title_fullStr | Identification of a Non-Linear Landing Gear Model Using Nature-Inspired Optimization |
| title_full_unstemmed | Identification of a Non-Linear Landing Gear Model Using Nature-Inspired Optimization |
| title_short | Identification of a Non-Linear Landing Gear Model Using Nature-Inspired Optimization |
| title_sort | identification of a non linear landing gear model using nature inspired optimization |
| url | http://dx.doi.org/10.1155/2008/246271 |
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