Abstract
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.
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