Adaptive neural output-feedback control for a class of nonlower triangular nonlinear systems with unmodeled dynamics
This paper presents the development of an adaptive neural controller for a class of nonlinear
systems with unmodeled dynamics and immeasurable states. An observer is designed to …
systems with unmodeled dynamics and immeasurable states. An observer is designed to …
A new varying-parameter recurrent neural-network for online solution of time-varying Sylvester equation
Solving Sylvester equation is a common algebraic problem in mathematics and control
theory. Different from the traditional fixed-parameter recurrent neural networks, such as …
theory. Different from the traditional fixed-parameter recurrent neural networks, such as …
A robust predefined-time convergence zeroing neural network for dynamic matrix inversion
J **, J Zhu, L Zhao, L Chen, L Chen… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
As a classical and effective method for solving various time-varying problems, the zeroing
neural network (ZNN) is widely applied in the scientific and industrial realms. In plentiful …
neural network (ZNN) is widely applied in the scientific and industrial realms. In plentiful …
Robustness analysis of a power-type varying-parameter recurrent neural network for solving time-varying QM and QP problems and applications
Varying-parameter recurrent neural network, being a special kind of neural-dynamic
methodology, has revealed powerful abilities to handle various time-varying problems, such …
methodology, has revealed powerful abilities to handle various time-varying problems, such …
A global neural network learning machine: Coupled integer and fractional calculus operator with an adaptive learning scheme
Find the global optimal solution of the model is one promising research topic in
computational intelligent community. Dependent on analogies to natural processes, the …
computational intelligent community. Dependent on analogies to natural processes, the …
Neural-dynamic-method-based dual-arm CMG scheme with time-varying constraints applied to humanoid robots
We propose a dual-arm cyclic-motion-generation (DACMG) scheme by a neural-dynamic
method, which can remedy the joint-angle-drift phenomenon of a humanoid robot. In …
method, which can remedy the joint-angle-drift phenomenon of a humanoid robot. In …
Design and application of an adaptive fuzzy control strategy to zeroing neural network for solving time-variant QP problem
L Jia, L **ao, J Dai, Z Qi, Z Zhang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Zeroing neural network (ZNN), as an important class of recurrent neural network, has wide
applications in various computation and optimization fields. In this article, based on the …
applications in various computation and optimization fields. In this article, based on the …
Taylor Discretization of ZNN Models for Dynamic Equality-Constrained Quadratic Programming With Application to Manipulators
In this paper, a new Taylor-type numerical differentiation formula is first presented to
discretize the continuous-time Zhang neural network (ZNN), and obtain higher …
discretize the continuous-time Zhang neural network (ZNN), and obtain higher …
A one-layer recurrent neural network for pseudoconvex optimization problems with equality and inequality constraints
S Qin, X Yang, X Xue, J Song - IEEE transactions on …, 2016 - ieeexplore.ieee.org
Pseudoconvex optimization problem, as an important nonconvex optimization problem,
plays an important role in scientific and engineering applications. In this paper, a recurrent …
plays an important role in scientific and engineering applications. In this paper, a recurrent …
G2-type SRMPC scheme for synchronous manipulation of two redundant robot arms
In this paper, to remedy the joint-angle drift phenomenon for manipulation of two redundant
robot arms, a novel scheme for simultaneous repetitive motion planning and control …
robot arms, a novel scheme for simultaneous repetitive motion planning and control …