![](images/graphics/blank.gif)
Radial basis functions
-
Part 1 of ebook "Construction of global lyapunov functions using radial basis functions" provides readers with contents including: introduction; lyapunov functions and radial basis functions; lyapunov functions; introduction to dynamical systems; local lyapunov functions; global lyapunov functions;...
66p
mothoiphong
28-06-2024
1
1
Download
-
Part 2 of ebook "Construction of global lyapunov functions using radial basis functions" provides readers with contents including: radial basis functions; construction of lyapunov functions; global determination of the basin of attraction; application of the method examples; distributions and fourier transformation;...
108p
mothoiphong
28-06-2024
1
1
Download
-
This research focuses on the integration of a radial basis function neural network (RBFNN) for uncertainty approximation in pneumatic artificial muscle (PAM) systems within the framework of power rate exponential reaching law sliding mode control (PRERL-SMC). Configured in an antagonistic manner, PAMs provide a range of benefits for developing actuators with human-like characteristics.
9p
vimichaelfaraday
14-12-2023
9
4
Download
-
Bài viết này đề xuất phương pháp điều khiển bền vững tích hợp thuật toán điều khiển DSC (Dynamic Surface Control) kết hợp thuật toán bù thích nghi sử dụng mạng nơ-ron RBF (Radial Basis Function) làm cho lực căng và vận tốc của các quả lô xấp xỉ giá trị đặt, giúp hệ thống ổn định với các tham số thay đổi.
10p
vijeff
30-11-2023
14
9
Download
-
Estimation of Construction Price Index (CPI) is important for a market economy and it is a measure to manage construction investment costs. This is a tool to help organizations and individuals to reduce the effort and management of expenses for construction projects by reducing time of procedures for calculating and adjusting the total investment for the estimation and evaluation of contract price.
11p
visharma
20-10-2023
7
4
Download
-
Ebook "Neural networks - A comprehensive foundation" includes content: Introduction, learning processes; single layer perceptrons; multilayer perceptrons; radial basis function networks; support vector machines; committee machines; principal components analysis; self organizing maps; information theoretic models; stochastic machines and their approximates rooted in statistical mechanics; neurodynamic programming; temporal processing using feedforward networks; neurodynamics; dynamically driven recurrent networks.
823p
haojiubujain07
20-09-2023
6
2
Download
-
Kernel regression models developed with Visual C# .NET for data analysis in construction engineering
This research work relies on kernel regression methods for constructing nonlinear regression models. These models can be used to solve function approximation tasks in construction engineering. The newly developed software program was developed with the Visual C# .NET. The program has been tested with the task of estimating the punching shear strength of steel fibre reinforced concrete slab.
7p
nhanchienthien
25-07-2023
6
4
Download
-
Ebook "An introduction to Neural network methods for differential equations" introduces a variety of neural network methods for solving differential equations arising in science and engineering. The emphasis is placed on a deep understanding of the neural network techniques, which has been presented in a mostly heuristic and intuitive manner. This approach will enable the reader to understand the working, efficiency and shortcomings of each neural network technique for solving differential equations.
124p
dieptieuung
19-07-2023
281
274
Download
-
In this paper, Wavelet transforms for the recognition and localization of short circuits faults on the power transmission lines. In that, the voltage waves and current waves on the lines are simulated by Simulink - Matlab.
5p
vidoctorstrange
06-05-2023
5
3
Download
-
This paper confirms the practical effect of applying Artificial Neural Networks (ANNs) using Radial basis function (RBF) bases on Sliding mode control (SMC) to control nonlinear systems. The proposed algorithm is put into comparison with the super twisting 2-SMC, which was designed to reduce chattering and increase the performance of conventional SMC.
7p
vidoctorstrange
06-05-2023
9
5
Download
-
In this paper, we consider the adaptive sliding mode control with radial basis function neural networks for the Omni-directional mobile robot. This is a holonomic robot that can operate easily in small and narrow spaces, due to the ability of flexible rotational and translational moving, simultaneously and independently.
8p
vidoctorstrange
06-05-2023
12
6
Download
-
Bài viết Điều khiển trượt hệ nâng vật trong từ trường dùng mạng nơ ron hàm cơ sở xuyên tâm được nghiên cứu nhằm mục tiêu áp dụng bộ điều khiển trượt dùng mạng nơ-ron hàm cơ sở xuyên tâm, gọi tắt là mạng nơron RBF (Radial Basis Function Neural Networks) cho hệ nâng vật trong từ trường.
5p
visaleen
30-10-2022
13
4
Download
-
Ebook "Neural network and deep learning: A textbook" provide readers with content about: an introduction to neural networks; machine learning with shallow neural networks; training deep neural networks; teaching deep learners to generalize; radial basis function networks;...
512p
tieuduongchi
07-10-2022
13
6
Download
-
This present study proposes a design and the analysis of the novel adaptive robust neural networks (ARNNs) based on the backstepping control method for industrial robot manipulators (IRMs). In this research, the ARNNs controller has combined the advantages of Radial Basis Function neural network (RBFNN), the robust term, and adaptive backstepping control technique without the requirement of prior knowledge.
7p
vigeneralmotors
13-07-2022
471
10
Download
-
The paper has developed an adaptive algorithm using neural network for controlling dual-arm robotic system in stable holding a rectangle object and moving it to track the desired trajectories. Firstly, an overall dynamic of the system including the dual-arm robot and the object is derived based on Euler-Lagrangian principle.
7p
visherylsandber
04-07-2022
8
2
Download
-
This paper presents a novel adaptive controller for two-wheeled selfbalancing mobile robots combining sliding mode control and hierarchical sliding control techniques. In addition, the radial basis function neural networks (RBFNN) are also applied to approximate the uncertain components in the system.
9p
viericschmid
12-01-2022
23
3
Download
-
The paper has developed an adaptive control using neural network for controlling a dual-arm robotic system in moving a rectangle object to the desired trajectories. Firstly, the overall dynamics of the manipulators and the object have been derived based on Euler-Lagrangian principle. And then based on the dynamics, a controller has been proposed to achieve the desired trajectories of the grasping object
9p
spiritedaway36
28-11-2021
35
5
Download
-
Identification of acute or recent hepatitis C virus (HCV) infections is important for detecting outbreaks and devising timely public health interventions for interruption of transmission. Epidemiological investigations and chemistry-based laboratory tests are 2 main approaches that are available for identification of acute HCV infection. However, owing to complexity, both approaches are not efficient.
10p
vilarryellison
29-10-2021
9
0
Download
-
In this paper, a robust hierarchical method for trajectory tracking control of a quadrotor unmanned aerial vehicle (UAV) subjected to parameter uncertainties and external disturbances is presented. A robust control scheme based on a fast nonsingular terminal sliding mode strategy is designed to achieve fast response and excellent tracking accuracy. Moreover, a radial basis function artificial neural network with online adaptive schemes to estimate unknown aerodynamic parameters and external disturbances is developed to improve the control performance and reduce the chattering phenomenon.
6p
cothumenhmong11
05-05-2021
14
3
Download
-
The search for optimum design variables is conducted by using a recent heuristic method, namely Grey Wolf Optimizer. During the heuristic search, direct heat conduction problem has to be solved several times. The set of heat transfer parameters that lead to smallest error rate between computed temperature field and reference one is the optimum output of the inverse problem. In order to accelerate the process, the model order reduction technique Proper-Orthogonal-Decomposition (POD) is used.
14p
nguaconbaynhay11
07-04-2021
14
3
Download
CHỦ ĐỀ BẠN MUỐN TÌM
![](images/graphics/blank.gif)