Author:
Cang Naimeng,Qiu Feng,Xue Shan,Jia Zehua,Guo Dongsheng,Zhang Zhijun,Li Weibing
Abstract
AbstractRecently, continuous- and discrete-time models of a zeroing neural network (ZNN) have been developed to provide online solutions for the time-dependent linear equation (TDLE) with boundary constraint. This paper presents a novel approach to address the bound-constrained TDLE (BCTDLE) problem by proposing a new discrete-time ZNN (DTZNN) model. The proposed DTZNN model is designed using the Taylor difference formula to discretize the previous continuous-time ZNNN (CTZNN) model. Theoretical analysis indicates the computational property of the proposed DTZNN model, and numerical results further demonstrate its validity. The applicability of the proposed DTZNN model is finally confirmed via its application to the motion planning of a PUMA560 robotic arm.
Funder
Key Technologies Research and Development Program
Shanghai Science and Technology program
Hainan Province Science and Technology Special Fund
Hainan Provincial Natural Science Foundation of China
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
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