APPLICATION OF ARCHITECTURE- BASED NEURAL NETWORKS IN MODELING AND PARAMETER OPTIMIZATION OF HYDRAULIC BUMPER  

作　　者：Yang Haiwei Zhan Yongqi Qiao Junwei Shi GuanglinSchool of Mechanical Engineering,Shanghai Jiaotong University,Shanghai 200030, China 

出　　处：《Chinese Journal of Mechanical Engineering》2003年第3期313-316,共4页中国机械工程学报（英文版）

摘　　要：The dynamic working process of 52SFZ-140-207B type of hydraulic bumper isanalyzed. The modeling method using architecture-based neural networks is introduced. Using thismodeling method, the dynamic model of the hydraulic bumper is established; Based on this model thestructural parameters of the hydraulic bumper are optimized with Genetic algorithm. The result showsthat the performance of the dynamic model is close to that of the hydraulic bumper, and the dynamicperformance of the hydraulic bumper is improved through parameter optimization.The dynamic working process of 52SFZ-140-207B type of hydraulic bumper isanalyzed. The modeling method using architecture-based neural networks is introduced. Using thismodeling method, the dynamic model of the hydraulic bumper is established; Based on this model thestructural parameters of the hydraulic bumper are optimized with Genetic algorithm. The result showsthat the performance of the dynamic model is close to that of the hydraulic bumper, and the dynamicperformance of the hydraulic bumper is improved through parameter optimization.

关 键 词：Architecture-based Neural networks MODELING Parameter optimization Hydraulic bumper 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]