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Multi-objective optimization of configuration parameter forsix dimensional microgravity simulation platform(PDF)


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Multi-objective optimization of configuration parameter forsix dimensional microgravity simulation platform
Zou Shangyuan1Liu Hairui2Jiang Yanjie3Liu Yanli<sup>23Wu Hongtao3
1. Department of Automotive Engineering; 2. Department of Electrical Engineering,Jiangsu College of Safety Technology,Xuzhou 221011,China; 3. College of MechanicalEngineering,Nanjing University of Aeronautics & Astronautics,Nanjing 210016,China
microgravity simulation platform configuration parameters multi-objective optimization NSGA-2
In order to solve the problems that the parallel mechanism has the same performance after the same proportion zoom and the performance index is related with the dimension selection,the Jacobian matrix is dealt with dimensionless by using the characteristic length method to ensure the continued optimization of the configuration parameters. By analyzing the impact of 6 design variables on the configuration parameter optimization and determining the 2 of 6 variables as the final multi-objective optimization variables,a set of optimal Pareto solutions is gotten and among them a group of optimal solution in accordance with the engineering is obtained under the premise that the workspace size can be obtained by the multi-objective NSGA-2 optimization algorithm for the 3 performance indexes of workspace inradius,global dexterity and global load capacity index. All the results show that the NSGA-2 method is more valuable for practical engineering than the traditional single objective optimization method.


[1] Merlet J P. Optimal design of robots[C]//Proceedings of Robotics:Science and Systems. Cambridge,US:IEEE,2005:8-11.
[2]Angeles J,Park F C. Performance evaluation and design criteria(Springer Handbook of Robotics)[M]. Berlin Heidelberg,Germany:Springer,2008:229-244.
[3]Gon?alves R S,Carvalho J C M,Lobato F S. Workspace analysis of a parallel manipulator using multi-objective optimization and bio-inspired methods[C]//International Symposium on Multibody Systems and Mechatronics. Florianó-Polis,Brazil:Springer,2017:107-115.
[4]Ma O,Angeles J. Optimum architecture design of platform manipulators[C]//The fifth International Conference on Advanced Robotics. Pisa,Italy:IEEE,1991:1130-1135.
[5]Kim S G,Ryu J. New dimensionally homogeneous Jacobian matrix formulation by three end-effector points for optimal design of parallel manipulators[J]. IEEE Transactions on Robotics and Automation,2003,19(4):731-737.
[6]Merlet J P. Jacobian,manipulability,condition number,and accuracy of parallel robots[J]. Journal of Mechanical Design,2006,128(1):199-206.
[7]Yoon J,Ryu J. Design,fabrication,and evaluation of a new haptic device using a parallel mechanism[J]. IEEE/ASME Transactions on Mechatronics,2001,6(3):221-233.
[8]Khan S,Andersson K,Wikander J. Jacobian matrix normalization-A comparison of different approaches in the context of multi-objective optimization of 6-DOF haptic devices[J]. Journal of Intelligent & Robotic Systems,2015,79(1):87-100.
[9]Wang H,Zhang L,Chen G,et al. Parameter optimization of heavy-load parallel manipulator by introducing stiffness distribution evaluation index[J]. Mechanism & Machine Theory,2017,108:244-259.
[10]Yang X,Wu H,Li Y,et al. Dynamic isotropic design and decentralized active control of a six-axis vibration isolator via Stewart platform[J]. Mechanism and Machine Theory,2017,117:244-252.
[11]Yang X,Wu H,Li Y,et al. Dynamic isotropic design and decentralized active control of a six-DOF micro-vibration isolator lying on two rings for space systems[C]//The 24th International Congress on Sound and Vibration.London,UK:ICSV,2017.
[12]Su Y X,Duan B Y,Zheng C H. Genetic design of kinematically optimal fine tuning Stewart platform for large spherical radio telescope[J]. Mechatronics,2001,11(7):821-835.
[13]Zheng Y,Yao Y. Kinematic optimal design of 6-UPS parallel manipulator[C]//Proceedings of the 2006 IEEE International Conference on Mechatronics and Automation. Niagara Fall,Canada:IEEE,2006:2341-2345.
[14]Lara-molina F A,Rosario J M,Dumur D. Multi-objective optimization of Stewart-Gough manipulator using global indices[C]//2011 IEEE/ASME International Conference on Advanced Intelligent Mecha-tronics(AIM). Budapest,Hungary:IEEE,2011:79-85.
[15]Lou Y,Liu G,Li Z. Randomized optimal design of parallel manipulators[J]. IEEE Transactions on Automation Science & Engineering,2008,5(2):223-233.
[16]Lou Y,Liu G,Chen N,et al. Optimal design of parallel manipulators for maximum effective regular workspace[C]//2005 IEEE/RSJ International Conference on Intelligent Robots and Systems. Edmonton,Canada:IEEE,2005:795-800.
[17]Vulliez M,Zeghloul S. Multi-objective design optimization of the delthaptic,a new 6-DOF haptic device[C]//IEEE,International Conference on Industrial Informatics. Poitiers,France:IEEE,2017:248-253.
[18]Wang R,Zhang X. Optimal design of a planar parallel 3-DOF nanopositioner with multi-objective[J]. Mechanism & Machine Theory,2017,112:61-83.
[19]Khan S. Multi-objective optimal design of a 6-DOF haptic device based on Jacobian normalization[J]. IEEE Transactions on Robotics and Automation,2012,31(4):823-834.
[20]刘国军,郑淑涛,刘小初,等. 采用进化算法的Gough-Stewart平台优化设计[J]. 哈尔滨工业大学学报,2013,45(3):36-44.
Liu Guojun,Zheng Shutao,Liu Xiaochu,et al. Optimal design of the Gough-Stewart platform using evolutionary algorithms[J]. Journal of Harbin Institute of Technology,2013,45(3):36-44.
[21]张琦,朱春生,冉红亮,等. 基于NSGA-Ⅱ的测试性指标分配方法[J]. 南京理工大学学报,2012,36(4):650-655.
Zhang Qi,Zhu Chunsheng,Ran Hong1iang,et al. Testability index distribution method based on NSGA-Ⅱ algorithm[J]. Journal of Nanjing University of Science and Technology,2012,36(4):650-655.


Last Update: 2019-04-26