检索结果-内蒙古大学图书馆

International Conference on Control, Automation and Diagnosis (ICCAD)

作者： Benamor Anouar Ben Njima Chakib Messaoud Hassani Laboratory of Automatic Signal and Image Processing National School of Engineers of Monastir University of Monastir Tunisia

ISBN: (数字)9781728122922

ISBN: (纸本)9781728122939

In this paper we propose a new robust sliding mode control for the uncertain systems with delay on the input.. The Control law is function of the estimated upper bound and is based on a choice of Lyapunov function. This new approach is carried out in two steps; the first consists on the determination of a state predictor in discrete time for the uncertain systems. The second is the synthesis of a first order sliding mode control. Simulation results prove the efficiency of the proposed resulting methodology.

关键词： Sliding mode control Delays Adaptive systems Uncertain systems Delay effects Automation

来源：评论

学校读者我要写书评

暂无评论

Exoskeleton Dynamic Modeling and Identification with Load and Temperature-Dependent Friction Model

Exoskeleton Dynamic Modeling and Identification with Load an...

引用

signal, Control and Communication (SCC), International Conference on

作者： Mouna Dali Hassen Imen Laamiri Hassani Messaoud Laboratory of Automatic Signal and Image Processing National School of Engineers of Monastir University of Monastir Tunisia

ISBN: (纸本)9781665402712

Frictional losses within the transmission components of robotic manipulators are often modeled as a constant Coulomb friction force or/and a viscous friction force proportional to the sliding velocity. However, the variation in contact forces of lubricated surfaces of the mechanical transmission system influences the friction force. The joint temperature also has an effect on the variation of the latter. Hence, the importance of considering the parameters mentioned in the dynamic model of the robotic manipulator. This paper presents a new load and temperature-dependent model that will be subsequently identified from experimental measurements carried out on two-link robotic manipulator with different loads.

关键词： Temperature measurement Temperature dependence Friction Force Exoskeletons Dynamics Propagation losses

来源：评论

学校读者我要写书评

暂无评论

A hybrid method based on conjugate gradient trained neural network and differential evolution for non linear systems identification

A hybrid method based on conjugate gradient trained neural n...

引用

International Conference on Electrical Engineering and Software Applications (ICEESA)

作者： Chiha Ibtissem Liouane Nouredine Laboratory of Automatic Image and Signal Processing (ATSI) National School of Engineers of Monastir Monastir Tunisia

ISBN: (纸本)9781467363020

A hybrid method based on Differential Evolution and Neural Network training algorithms is presented in this paper for improving the performance of neural network in the non linear system identification. For this purpose, the local optimization algorithm of conjugate gradients (CG) is combined with the differential evolution algorithm (DE), which is a population-based stochastic global search method, to yield a computationally efficient algorithm for training multilayer perceptron networks for nonlinear system identification. After, a series of simulation studies of our method on the different nonlinear systems it has been confirmed that the proposed CG+DE algorithm has yielded better identification results in terms of time of convergence and less identification error.

关键词： Vectors Algorithm design and analysis signal processing algorithms Nonlinear systems Sociology Statistics Neural networks

来源：评论

学校读者我要写书评

暂无评论

Intelligent ID System for the Industrial Internet of Things Using Machine Learning Algorithms

Intelligent ID System for the Industrial Internet of Things ...

引用

International Conference on Advanced Systems and Electric Technologies (IC_ASET)

作者： BACHA Sawssen LIOUANE Noureeddine Laboratory of Automatic Signal and Image Processing National Engineering School of Monastir University of Monastir Tunisia

ISBN: (数字)9798350384895

ISBN: (纸本)9798350384901

The Industrial Internet of Things offers modern industrial firms numerous opportunities for significant growth. The Internet of Things technology utilized in the sector has developed into a large-scale network as a result of the increasing amount of data and devices. Industrial IoT networks are by nature susceptible to hacking and intrusions. Thus, in order to ensure the security of IIoT networks, intrusion detection system IDS development is essential. This study proposes an IDS to defeat a variety of cyberattacks in industrial Internet of things environments. The suggested approach reduces the dimension of the data characteristics and enhances the performance of anomaly identification by using the kernel principal component analysis technique. For binary classification, we use the kernel extreme learning machine to identify if the traffic flow is benign or attack. We use it to multiclass classification in order to classify the set of attacks based on the specific type of attack. The performance results are assessed and analyzed using the X-IloTDS dataset in order to prove the effectiveness of the suggested anomaly detection approach. The evaluation's findings show that the suggested anomaly detection strategy may greatly raise detection performance outcomes in terms of specificity, accuracy, sensitivity, and F1-score while also successfully increasing detection efficiency.

关键词： Training Machine learning algorithms Accuracy Sensitivity Security Computer crime Kernel

来源：评论

学校读者我要写书评

暂无评论

Supervised machine learning-based salp swarm algorithm for fault diagnosis of photovoltaic systems

引用

Journal of Engineering and Applied Science 2024年第1期71卷 12页

作者： Hichri, Amal Hajji, Mansour Mansouri, Majdi Nounou, Hazem Bouzrara, Kais Research Unit Advanced Materials and Nanotechnologies Higher Institute of Applied Sciences and Technology of Kasserine Kairouan University Kairouan Tunisia Electrical and Computer Engineering Program Texas A&M University at Qatar Doha Qatar Laboratory of Automatic Signal and Image Processing National School of Engineers of Monastir University of Monastir Monastir5019 Tunisia

The diagnosis of faults in grid-connected photovoltaic (GCPV) systems is a challenging task due to their complex nature and the high similarity between faults. To address this issue, we propose a wrapper approach called the salp swarm algorithm (SSA) for feature selection. The main objective of SSA is to extract only the most important features from the raw data and eliminate unnecessary ones to improve the classification accuracy of supervised machine learning (SML) classifiers. Subsequently, the selected features are used to train supervised machine learning (SML) techniques in distinguishing between various operating modes. To evaluate the efficiency of the technique, we used healthy and faulty data from GCPV systems that have been injected with frequent faults, 20 different types of faults were introduced, including line-to-line, line-to-ground, connectivity faults, and those affecting the operation of bay-pass diodes. These faults present diverse conditions, such as simple and multiple faults in the PV arrays and mixed faults in both arrays. The performances of the developed SSA-SML are compared with those using principal component analysis (PCA) and kernel PCA (KPCA) based SML techniques through different criteria (i.e., accuracy, recall, precision, F1 score, and computation time). The experimental findings demonstrated that the proposed diagnosis paradigm outperformed the other techniques and achieved a high diagnostic accuracy (an average accuracy greater than 99%) while significantly reducing computation time. © 2023, The Author(s).

关键词： Failure analysis

来源：评论

学校读者我要写书评

暂无评论

Design of optimal PD controller for inverted pendulum using differential evolution

Design of optimal PD controller for inverted pendulum using ...

引用

International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Chiha Ibtissem Liouane Nouredine Laboratory of Automatic Image and Signal Processing (ATSI) National School of Engineers of Monastir (ENIM) Monstir Tunisia

In this paper, we have tried to tune PD Controller inverted pendulum using Multiobjective Differential Evolution by nonlinear equations. The objective was to apply the differential evolution algorithm in the aim of tuning the optimum solution of the PD controllers K p and K d by minimizing the Multiobjective function. The results of this simulation have been mentioned in the conclusion. It seems that the results be acceptable results.

关键词： Vectors PD control Optimization signal processing algorithms Sociology Statistics Regulators

来源：评论

学校读者我要写书评

暂无评论

Control of Continuous Stirred Tank Reactor using PI corrector based on NARX model

Control of Continuous Stirred Tank Reactor using PI correcto...

引用

International Conference on Control, Automation and Diagnosis (ICCAD)

作者： Imen Ben Abdelwahed Kais Bouzrara Research Laboratory of Automatic Signal and Image Processing National School of Engineers of Monastir University of Monastir Tunisia

ISBN: (数字)9798350361025

ISBN: (纸本)9798350361032

This paper presents a study on the control of a Continuous Stirred Tank Reactor (CSTR) using a Proportional-Integral (PI) controller based on a second-order Nonlinear AutoRegressive with eXogenous inputs (NARX) model in its regression form. The objective is to achieve an optimal control of the CSTR system by leveraging the capabilities of the NARX model and the PI controller. The proposed approach is validated through simulations to demonstrate its effectiveness in regulating the CSTR reactor.

关键词： Adaptation models PI control Optimal control Predictive models Benchmark testing Stability analysis Regulation

来源：评论

学校读者我要写书评

暂无评论

Pole optimization of NARX-Laguerre model using Gradient method

Pole optimization of NARX-Laguerre model using Gradient meth...

引用

International Conference on Control, Automation and Diagnosis (ICCAD)

作者： Imen Ben Abdelwahed Ameni El Anes Kais Bouzrara Research Laboratory of Automatic Signal and Image Processing National Engineering School of Monastir University of Monastir Tunisia

ISBN: (数字)9798350361025

ISBN: (纸本)9798350361032

The NARX-Laguerre model serves as a significantly simplified representation of nonlinear systems, achieved by expressing the coefficients of the NARX model through five independent Laguerre bases. This particular model is defined by five Laguerre poles, the optimal values of which ensure a noteworthy reduction in parameters. In this paper, we suggest an approach to estimate the NARX-Laguerre poles based on input/output measurements, employing the gradient method. The algorithm proposed for optimizing these poles is tested through a numerical example.

关键词： Gradient methods Automation Numerical models Nonlinear systems Optimization Testing

来源：评论

学校读者我要写书评

暂无评论

Expansion of the switched FIR model parameters on Laguerre bases

Expansion of the switched FIR model parameters on Laguerre b...

引用

signal, Control and Communication (SCC), International Conference on

作者： Ibtissem bengharat Abdelkader Mbarek Hedi Dhouibi Research Laboratory of Automatic Signal and Image Processing National School of Engineers of Monastir University of Monastir Tunisia

ISBN: (数字)9781728135960

ISBN: (纸本)9781728135977

This paper proposes a new representation of the S-FIR model by developing its coefficients using Laguerre orthonormal functions. The resulting model, entitled S-Laguerre model, ensures a significant parameter number reduction as well as simple recursive representation. However, this reduction is strongly linked to an optimal choice of the S-Laguerre poles defining the Laguerre bases. Therefore, we propose to extended the works of Tanguy et al. (2000) by proposing an optimisation algorithm to provide the optimal values for S-Laguerre poles. The Fourier coefficients of the proposed model are identified using the classical Recursive Least Square algorithm. The performances of the proposed S-Laguerre model and the proposed identification approach are illustrated on a numerical simulation.

关键词： Switching model S-FIR S-Laguerre Identification Optimization

来源：评论

学校读者我要写书评

暂无评论

Effective uncertain fault diagnosis technique for wind conversion systems using improved ensemble learning algorithm

引用

Energy Reports 2023年 10卷 3113-3124页

作者： Attouri, Khadija Dhibi, Khaled Mansouri, Majdi Hajji, Mansour Bouzrara, Kais Nounou, Mohamed Higher Institute of Applied Sciences and Technology of Kasserine Kairouan University Kasserine1200 Tunisia Electrical and Computer Engineering Program Texas A&M University at Qatar Qatar Chemical Engineering Program Texas A&M University at Qatar Qatar Laboratory of Automatic Signal and Image Processing National Engineering School of Monastir University of Monastir 5019 Tunisia

This paper introduces a pioneering fault diagnosis technique termed Interval Ensemble Learning based on Sine Cosine Optimization Algorithm (IEL- SCOA), tailored to tackle uncertainties prevalent in wind energy conversion (WEC) systems. The approach unfolds in three integral phases. Firstly, the establishment of interval centers and ranges, employing upper and lower bounds, effectively manages the inherent uncertainties arising from noise and measurement errors intrinsic to the wind system. Subsequently, the dataset undergoes processing via the Sine-Cosine Optimization Algorithm (SCOA), enabling the extraction of the most pertinent attributes. The culmination of predictive precision and classification performance is achieved through the integration of the refined dataset into an ensemble learning paradigm, harmonizing bagging, boosting techniques, and an artificial neural network classifier. The principal aim of the IEL-SCOA approach is to discern the spectrum of operational conditions within WEC systems, encompassing a healthy mode alongside six distinct faulty modes. These anomalies, encompassing short circuits, open circuits, and wear-out incidents, are deliberately induced at diverse locations and facets of the system, notably the generator and grid sides. Empirical results underscore the robustness and efficiency of the proposed methodology, showcasing an exceptional accuracy rate of 99.76 %. These outcomes definitively establish the IEL-SCOA approach as a potent and efficacious tool for precise fault diagnosis in uncertain WEC systems. © 2023

关键词： Fault detection

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：