Forward Kinematics Analysis of High-Precision Optoelectronic Packaging Platform

被引:0
作者
Wang, Ziyang [1 ,2 ]
Zhou, Haibo [1 ,2 ]
Xiao, Linjiao [1 ,2 ]
Duan, Lian [1 ,2 ]
机构
[1] Cent South Univ, Coll Mech & Elect Engn, Changsha 410000, Hunan, Peoples R China
[2] Cent South Univ, State Key Lab Precis Mfg Extreme Serv Performance, Changsha 410000, Hunan, Peoples R China
基金
中国国家自然科学基金;
关键词
optoelectronic packaging; forward kinematics problem; improved particle swarm optimization; uniform design; a random learning strategy; space reduction techniques; PARTICLE SWARM OPTIMIZATION; BP NEURAL-NETWORK; PARALLEL MANIPULATOR; ALGORITHM; DESIGN;
D O I
10.1115/1.4064704
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
To meet the requirements of high-precision motion control for optoelectronic packaging platforms, we propose an improved particle swarm optimization (PSO) and backpropagation (IPSO-BP) neural network for solving the forward kinematics problem (FKP) of platforms. The focus of this paper is the 6-pss flexible parallel platform commonly used in optoelectronic packaging. First, a platform inverse kinematics problem (IKP) based on a flexibility matrix is solved using geometric and vector analysis. The conventional PSO-BP network is then optimized utilizing uniform design (UD), a random learning strategy, and space reduction techniques in FKP. Finally, simulations and experiments demonstrate that the proposed IPSO-BP network for solving the FKP on high-precision optoelectronic packaging platforms is feasible. Compared to BP and PSO-BP, this network has a higher resolution, faster convergence speed, and error control at the submicron level, which satisfies the motion control requirements of the platform at the micron level. This study lays a solid foundation for the production of high-quality devices in optoelectronic packaging.
引用
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页数:10
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