Genetic design of kinematically optimal fine tuning Stewart platform for large spherical radio telescope

被引:45
|
作者
Su, YX
Duan, BY [1 ]
Zheng, CH
机构
[1] Xidian Univ, Sch Mech & Elect Engn, Xian 710071, Peoples R China
[2] Xian Inst Petr, Dept Comp Sci, Xian 710068, Peoples R China
关键词
genetic algorithms; Stewart platform; optimal kinematics; fine tuning platform; large spherical radio telescope;
D O I
10.1016/S0957-4158(00)00041-6
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents a methodology for the design of optimal kinematical characteristics of Stewart platform using genetic algorithms (GAs). The optimal kinematics index which expressed by Jacobian matrix of Stewart platform is first deduced, and then the minimum of condition numbers of Jacobian matrix in the whole trajectory tracing workspace is used as the objective function. The constrained optimal design problem is transformed to unrestrained optimal one which is suitable to GAs by penalizing strategy, and the corresponding real-encoding scheme is used. This genetic methodology for optimal kinematical Stewart platform is illustrated by applying to design the fine tuning Stewart platform for large spherical radio telescope, and its validity is verified with the kinematic accuracy comparison of genetic-designed fine tuning platform with that of conventional Quasi-Newton optimal method. (C) 2001 Published by Elsevier Science Ltd.
引用
收藏
页码:821 / 835
页数:15
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