Adaptive control of uncertain nonaffine nonlinear systems with input saturation using neural networks

K Esfandiari, F Abdollahi… - IEEE transactions on …, 2014 - ieeexplore.ieee.org
This paper presents a tracking control methodology for a class of uncertain nonlinear
systems subject to input saturation constraint and external disturbances. Unlike most …

[图书][B] Fault diagnosis of nonlinear systems using a hybrid approach

E Sobhani-Tehrani, K Khorasani - 2009 - books.google.com
Theincreasingcomplexityofspacevehiclessu…, andthecostreduction measures that have
affected satellite operators are increasingly driving the need for more autonomy in satellite …

Comparative study of neural networks for dynamic nonlinear systems identification

R Kumar, S Srivastava, JRP Gupta, A Mohindru - Soft Computing, 2019 - Springer
In this paper, a comparative study is performed to test the approximation ability of different
neural network structures. It involves three neural networks multilayer feedforward neural …

Improved learning algorithm for two-layer neural networks for identification of nonlinear systems

JAR Vargas, W Pedrycz, EM Hemerly - Neurocomputing, 2019 - Elsevier
This study is concerned with the asymptotic identification of nonlinear systems based on
Lyapunov theory and two-layer neural networks. An improved identification model enhanced …

[HTML][HTML] A method for weighing broiler chickens using improved amplitude-limiting filtering algorithm and BP neural networks

W Ma, Q Li, J Li, L Ding, Q Yu - Information Processing in Agriculture, 2021 - Elsevier
Broiler chickens are traditionally weighed by steelyard or platform scale, which is time-
consuming and labor-intensive. Broiler chickens usually exhibit stress-related behavior …

Identification and control for singularly perturbed systems using multitime-scale neural networks

D Zheng, WF Xie, X Ren, J Na - IEEE Transactions on Neural …, 2016 - ieeexplore.ieee.org
Many well-established singular perturbation theories for singularly perturbed systems
require the full knowledge of system model parameters. In order to obtain an accurate and …

An adaptive modeling method for a robot belt grinding process

S Yixu, L Hongbo, Y Zehong - IEEE/ASME Transactions on …, 2011 - ieeexplore.ieee.org
A robot belt grinding system has a good prospect for releasing hand grinders from their dirty
and noisy work environment. However, as a kind of manufacturing system with a flexible …

Constrained PI tracking control for output probability distributions based on two-step neural networks

Y Yi, L Guo, H Wang - … Transactions on Circuits and Systems I …, 2008 - ieeexplore.ieee.org
In this paper, a new method for the control of the shape of the conditional output probability
density function (pdf) for general nonlinear dynamic stochastic systems is presented using …

Inverse double NARX fuzzy modeling for system identification

KK Ahn, HPH Anh - Ieee/asme transactions on mechatronics, 2009 - ieeexplore.ieee.org
In this paper, a novel inverse double nonlinear autoregressive with exogenous input (NARX)
fuzzy model is applied to simultaneously model and identify both joints of the prototype two …

[PDF][PDF] Control of power system stability-reviewed solutions based on intelligent systems

AG Abro, J Mohamad-Saleh - International Journal of Innovative …, 2012 - researchgate.net
Electric power grid is a widely distributed system, consisting of dispersed generators
interconnected through transmission lines, mounting real and reactive power compensators …