Robust neural dynamics method for redundant robot manipulator control with physical constraints
Redundant robot manipulators play a significant role in modern industry. In this article, we
propose a solution scheme to the trajectory tracking problem of the redundant robot …
propose a solution scheme to the trajectory tracking problem of the redundant robot …
An efficient and robust varying-parameter projection neural network for sparse signal reconstruction
Q Hu, B Zheng - Neurocomputing, 2024 - Elsevier
Sparse signal reconstruction plays an important role in many practical applications, and
therefore, many scholars strive to study its various effective (approximate) solution …
therefore, many scholars strive to study its various effective (approximate) solution …
From Gauss–Newton method solving nonlinear least squares problem of static overdetermined system to multi-instant neurodynamic algorithms handling future time …
D Wu, Y Zhang - Nonlinear Dynamics, 2024 - Springer
Gauss–Newton method is mainly designed and exploited to solve the nonlinear least
squares problems of static overdetermined systems with order-2 precision. When the system …
squares problems of static overdetermined systems with order-2 precision. When the system …
A zeroing neural network for solving discrete time-varying minimization with different adjustable parameter
H He - Seventh International Conference on Mechatronics and …, 2023 - spiedigitallibrary.org
It is popular approach to employ Zeroing Neural Networks (ZNN) to handle time-varying
problems. However, most of the existing methods have limited flexibility in the discretization …
problems. However, most of the existing methods have limited flexibility in the discretization …