%0 Journal Article %1 YaowenWYang:2005:IJNME %A Yang, Yaowen W. %A Wang, Chao %A Soh, Chee Kiong %D 2005 %J International Journal for Numerical Methods in Engineering %K algorithms, dynamic excitation force force, genetic identification programming, response, system, %N 9 %P 1288--1312 %R doi:10.1002/nme.1323 %T Force identification of dynamic systems using genetic programming %V 63 %X One obvious limitation of the traditional force identification techniques is that they are unable to obtain the explicit expression of the force. Moreover, some techniques need both the displacement and velocity data of all freedoms, and some need the Markov parameters from numerical calculation or experimental test before the force identification can be carried out. This paper presents a genetic programming (GP) based method for excitation force identification of dynamic systems to overcome these traditional methods' disadvantages. GP is employed as a search and optimisation method to obtain the optimal, if not the best, force expression from the known dynamic response. One obvious merit of the proposed method is that it can obtain the explicit expression of the unknown force. Another advantage is that it only needs the dynamic response data at one point, i.e. displacement or velocity or acceleration of one freedom. Illustrative examples demonstrate that the GP based method is able to identify the excitation force of a single-degree, a three-degree dynamic systems and a frame structure, depicting its potential for force forecast problems.

@article{YaowenWYang:2005:IJNME, abstract = {One obvious limitation of the traditional force identification techniques is that they are unable to obtain the explicit expression of the force. Moreover, some techniques need both the displacement and velocity data of all freedoms, and some need the Markov parameters from numerical calculation or experimental test before the force identification can be carried out. This paper presents a genetic programming (GP) based method for excitation force identification of dynamic systems to overcome these traditional methods' disadvantages. GP is employed as a search and optimisation method to obtain the optimal, if not the best, force expression from the known dynamic response. One obvious merit of the proposed method is that it can obtain the explicit expression of the unknown force. Another advantage is that it only needs the dynamic response data at one point, i.e. displacement or velocity or acceleration of one freedom. Illustrative examples demonstrate that the GP based method is able to identify the excitation force of a single-degree, a three-degree dynamic systems and a frame structure, depicting its potential for force forecast problems.}, added-at = {2008-06-19T17:35:00.000+0200}, author = {Yang, Yaowen W. and Wang, Chao and Soh, Chee Kiong}, biburl = {https://www.bibsonomy.org/bibtex/256803632585d2ed7da11010c769aa45c/brazovayeye}, doi = {doi:10.1002/nme.1323}, interhash = {5978ad9d1e6b65852cd489a2b48099ad}, intrahash = {56803632585d2ed7da11010c769aa45c}, journal = {International Journal for Numerical Methods in Engineering}, keywords = {algorithms, dynamic excitation force force, genetic identification programming, response, system,}, notes = {http://www3.interscience.wiley.com/cgi-bin/abstract/110432712/ABSTRACT Division of Structures and Mechanics, School of Civil and Environmental Engineering, Nanyang Technological University, Nanyang Avenue, Singapore 639798, Singapore}, number = 9, pages = {1288--1312}, timestamp = {2008-06-19T17:54:48.000+0200}, title = {Force identification of dynamic systems using genetic programming}, volume = 63, year = 2005 }