TY - JOUR
T1 - Multi-objective optimization design of a connection frame in macro-micro motion platform
AU - Zhang, Lufan
AU - Long, Zhili
AU - Cai, Jiandong
AU - Luo, Fei
AU - Fang, Jiwen
AU - Wang, Michael Yu
N1 - Funding Information:
This work was supported by the following funds: (1) supported by Guangdong Innovative Research Team Program (No. 2009010051 ); (2) the Guangdong Key Project ( 2011A080801004 ); (3) the Key Joint Project of National Natural Science Foundation of China ( U1134004 ); (4) the Innovation Fund of Harbin Industrial University ( HIT.NSRIF.2013099 ); (5) the Basic Research Plan of Shenzhen ( JC201105160586A ); (6) the Province University-industry Cooperation Project ( 2012B091100022 ); (7) the Dongguan City Project in Colleges and Universities ( 2012108102023 ).
Publisher Copyright:
© 2015 Elsevier B.V. All rights reserved.
PY - 2015/7
Y1 - 2015/7
N2 - Connection frame is an essential component to implement high acceleration and ultra-precision positioning motion in a macro-micro motion platform. The performance of the positioning system is mainly affected by two sources which include thermal-mechanical deformation and the natural frequency of connection frame. In the paper, multi-objective optimization and design for the connection frame is constructed and discussed comprehensively by the effects of thermal-mechanical deformation and the natural frequency of the system. The optimization objectives for the connection structure are the minimized displacement when thermal-mechanical deformation is occurred, the maximized natural frequency to avoid system resonance, and the light weight for the connection structure to fulfil high acceleration motion. Using response surface method (RSM) combined with finite element method (FEM), the objective function is formulated as a prediction model. Non-dominated Sorting Genetic Algorithm II (NSGAII) is used to solve the optimization model and attain the matched parameters. A cantilever beam example is tested to examine the validity of the methodology, and the results from prediction model agree well with that from theoretical model. By the above methodology, a high performance with optimal parameters for the connection structure is obtained, and its natural frequency and weight can meet our design expectation.
AB - Connection frame is an essential component to implement high acceleration and ultra-precision positioning motion in a macro-micro motion platform. The performance of the positioning system is mainly affected by two sources which include thermal-mechanical deformation and the natural frequency of connection frame. In the paper, multi-objective optimization and design for the connection frame is constructed and discussed comprehensively by the effects of thermal-mechanical deformation and the natural frequency of the system. The optimization objectives for the connection structure are the minimized displacement when thermal-mechanical deformation is occurred, the maximized natural frequency to avoid system resonance, and the light weight for the connection structure to fulfil high acceleration motion. Using response surface method (RSM) combined with finite element method (FEM), the objective function is formulated as a prediction model. Non-dominated Sorting Genetic Algorithm II (NSGAII) is used to solve the optimization model and attain the matched parameters. A cantilever beam example is tested to examine the validity of the methodology, and the results from prediction model agree well with that from theoretical model. By the above methodology, a high performance with optimal parameters for the connection structure is obtained, and its natural frequency and weight can meet our design expectation.
KW - Connection frame
KW - Multi-objective optimization
KW - Natural frequency
KW - RSM
KW - Thermal-mechanical deformation
UR - http://www.scopus.com/inward/record.url?scp=84927942746&partnerID=8YFLogxK
U2 - 10.1016/j.asoc.2015.03.044
DO - 10.1016/j.asoc.2015.03.044
M3 - Article
AN - SCOPUS:84927942746
VL - 32
SP - 369
EP - 382
JO - Applied Soft Computing
JF - Applied Soft Computing
SN - 1568-4946
ER -