Up to date, the existing methods for nonlinear optimization with time-dependent parameters
can be classified into two types: 1) static methods are capable of handling inequality …

In recent years, dynamic overdetermined systems have sprung up and been broadly
employed for handling different problems in real time. This article makes improvements in …

In this article, the existing approaches, including numerical algorithms as well as neural
networks to solve dynamic linear matrix equations, have been presented and reviewed …

For dealing with the temporally variant optimization with nonlinear equation constraints
(TVONECs), a novel Zhang neural net (ZNN) model is proposed in this work. Two …

Zeroing neural dynamics (ZND) model is a powerful tool for solving dynamic problems. This
study presents an accelerated neural dynamics (AND) model by solving a dynamic …

Recurrent neural networks (RNNs) are excellent solvers for time-variant linear matrix–vector
inequality (TVLMVI). However, it is difficult for traditional RNNs to track the theoretical …

Nowadays, redundant manipulators have received a lot of attention from industry and
academia because of their ability to adapt to complex tasks. Specifically, the motion control …

In this paper, the development of discrete-time recurrent neural network (RNN) algorithm is
different from previous studies that require the derivation processes in the continuous-time …

This work investigates the problem of future linear equation system under various noises.
Firstly, a continuous advanced zeroing neurodynamic (CAZN) model under noise is …

It is common knowledge that the future quadratic programming (FQP) problem is a
challenging and widely applicable topic in mathematical science and many engineering …