通信学报2024，Vol.45Issue(9)：55-67,13.DOI:10.11959/j.issn.1000-436x.2024166
用于有界噪声时变矩阵计算的终端零化神经网络
Terminal zeroing neural network for time-varying matrix computing under bounded noise
摘要
Abstract
To improve the convergence performance of zeroing neural network(ZNN)for time-varying matrix computa-tion problems solving,a terminal zeroing neural network(TZNN)with noise resistance and its logarithmically acceler-ated form(LA-TZNN)were proposed.The terminal attraction of the error dynamic equation were analyzed,and the re-sults showed that the neural state of the proposed networks can converge to the theoretical solution within a fixed time when subjected to bounded noises.In addition,the LA-TZNN could achieve logarithmical settling-time stability,and its convergence speed was faster than the TZNN.Considering that the initial error was bounded in actual situations,an up-per bound of the settling-time in a semi-global sense was given,and an adjustable parameter was set to enable the net-work to converge within a predefined time.The two proposed models were applied to solve the time-varying matrix in-version and trajectory planning of redundant manipulators PUMA560.The simulation results further verified that com-pared with the conventional ZNN design,the proposed methods have shorter settling-time,higher convergence accuracy,and can effectively suppress bounded noise interference.关键词
时变矩阵计算/零化神经网络/固定/预定义时间收敛/重复运动规划Key words
time-varying matrix computation/ZNN/fixed/predefined-time convergence/repetitive motion planning分类
信息技术与安全科学引用本文复制引用
仲国民,唐逸飞,孙明轩..用于有界噪声时变矩阵计算的终端零化神经网络[J].通信学报,2024,45(9):55-67,13.基金项目
国家自然科学基金资助项目(No.62073291,No.62222315) （No.62073291,No.62222315）
浙江省自然科学基金资助项目(No.LZ22F030007)The National Natural Science Foundation of China(No.62073291,No.62222315),Zhejiang Provincial Natural Science Foundation of China(No.LZ22F030007) （No.LZ22F030007）
