2019 International Conference on Control, Automation and Diagnosis (ICCAD)最新文献

Diagnosis of nonlinear systems using reduced kernel principal component analysis 非线性系统的简化核主成分分析诊断

2019 International Conference on Control, Automation and Diagnosis (ICCAD) Pub Date : 2019-07-01 DOI: 10.1109/ICCAD46983.2019.9037905

R. Fezai, K. Abodayeh, M. Mansouri, H. Nounou, M. Nounou

引用次数: 0

[Copyright notice] (版权)

2019 International Conference on Control, Automation and Diagnosis (ICCAD) Pub Date : 2019-07-01 DOI: 10.1109/iccad46983.2019.9037955

引用次数: 0

Grey Forecasting Model and Particle Swarm based Control of a Phosphorite Sinter Process 基于灰色预测模型和粒子群的磷矿烧结过程控制

2019 International Conference on Control, Automation and Diagnosis (ICCAD) Pub Date : 2019-07-01 DOI: 10.1109/ICCAD46983.2019.9037944

Nigina Toktassynova, H. Fourati, B. Suleimenov

{"title":"Grey Forecasting Model and Particle Swarm based Control of a Phosphorite Sinter Process","authors":"Nigina Toktassynova, H. Fourati, B. Suleimenov","doi":"10.1109/ICCAD46983.2019.9037944","DOIUrl":"https://doi.org/10.1109/ICCAD46983.2019.9037944","url":null,"abstract":"The sintering process of phosphorite ore occurs with a large amount of return caused by untimely process control. The control task of the phosphorite ore sintering is to regulate parameters of the process to obtain a high quality sinter. The parameter clearly responsible on the sinter quality is the temperature in the wind box (called also burn through point (BTP)). Therefore, in order to solve the real time control task, it is necessary to predict the BTP. In this paper, the theory of grey systems is used as a predictive approach, which makes it possible to obtain an adequate model that has the character of generalized energy system and uses a small initial samples. Based on the developed optimal grey model GMC(1,n), which is constructed in real time by using real data at the beginning of the process, the temperature is well predicted at the end of the sintering process. When the temperature does not match the set value or to find out an optimal regulation, a control synthesis is carried out through an optimization of the prediction according to the particle swarm algorithm.","PeriodicalId":294791,"journal":{"name":"2019 International Conference on Control, Automation and Diagnosis (ICCAD)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126793706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Studying Multifractality in C.elegans sequences based on multi order FCGR Images 基于多级FCGR图像的秀丽隐杆线虫序列多重分形研究

2019 International Conference on Control, Automation and Diagnosis (ICCAD) Pub Date : 2019-07-01 DOI: 10.1109/ICCAD46983.2019.9037888

Zeineb Chebbi Babchia, A. Oueslati

引用次数: 3

Audio-Visual Fusion for Aggression Detection Using Deep Neural Networks 基于深度神经网络的视听融合攻击检测

2019 International Conference on Control, Automation and Diagnosis (ICCAD) Pub Date : 2019-07-01 DOI: 10.1109/ICCAD46983.2019.9037911

Noussaiba Jaafar, Z. Lachiri

引用次数: 5

Fuzzy Logic Controller for Autonomous Mobile Robot Navigation 自主移动机器人导航的模糊逻辑控制器

2019 International Conference on Control, Automation and Diagnosis (ICCAD) Pub Date : 2019-07-01 DOI: 10.1109/ICCAD46983.2019.9037922

Habiba Batti, Chiraz Ben Jabeur, H. Seddik

引用次数: 3

Robust control of hydraulic system with delay input 具有时滞输入的液压系统鲁棒控制

2019 International Conference on Control, Automation and Diagnosis (ICCAD) Pub Date : 2019-07-01 DOI: 10.1109/ICCAD46983.2019.9037893

B. Anouar, Benajiba Chakib, H. Messaoud

引用次数: 0

Training Function Stability in Anomaly Intrusion Detection based Deep Learning 基于深度学习的异常入侵检测训练函数稳定性

2019 International Conference on Control, Automation and Diagnosis (ICCAD) Pub Date : 2019-07-01 DOI: 10.1109/ICCAD46983.2019.9037956

K. Bennaceur, Zakaria Sahraoui, A. Labed, M. Ahmed-Nacer

{"title":"Training Function Stability in Anomaly Intrusion Detection based Deep Learning","authors":"K. Bennaceur, Zakaria Sahraoui, A. Labed, M. Ahmed-Nacer","doi":"10.1109/ICCAD46983.2019.9037956","DOIUrl":"https://doi.org/10.1109/ICCAD46983.2019.9037956","url":null,"abstract":"Deep Learning is a promising model used in both supervised and unsupervised classification as well as in feature extraction. It is applied to solve various research problems. In the present paper, the problem of Anomaly Network Intrusion Detection is studied. A supervised classifier based on deep learning with a conventional architecture of neural networks (CNN) is adopted to classify normal and abnormal network users behavior in order to detect attacks. Unlike usual metrics, such as the correct classification rate, used to select appropriate classifiers, the stability of the learning algorithm is used to choose an appropriate Deep Learning model for this application. Since the synaptic weights and consequently the performance of a deep learning classifier depend crucially on the optimization algorithm (gradient descent, conjugate gradient, etc), the choice of an algorithm that lead to stable performance independently of its initialization is of a great importance. A set of experiments based on the NSL-KDD dataset is achieved to compare different learning techniques in terms of accuracy and stability.","PeriodicalId":294791,"journal":{"name":"2019 International Conference on Control, Automation and Diagnosis (ICCAD)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133195650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

LQ Optimal Multi-Loop Control of Goods Distribution Systems with Multi-Modal Transportation Solutions 多式联运货物配送系统的LQ最优多环控制

2019 International Conference on Control, Automation and Diagnosis (ICCAD) Pub Date : 2019-07-01 DOI: 10.1109/ICCAD46983.2019.9037924

P. Ignaciuk

{"title":"LQ Optimal Multi-Loop Control of Goods Distribution Systems with Multi-Modal Transportation Solutions","authors":"P. Ignaciuk","doi":"10.1109/ICCAD46983.2019.9037924","DOIUrl":"https://doi.org/10.1109/ICCAD46983.2019.9037924","url":null,"abstract":"The paper investigates application of linear-quadratic $(LQ)$ optimal control in the distribution systems with multiple transportation options. In the considered class, the distribution center governs the stock replenishment process of subordinate depots whose stock is depleted according to the market demand. The supply channels have different characteristics with respect to delay and reliability, e.g., train vs. truck delivery. The received goods are inspected for quality defects and rejected as appropriate. Thus, the system faces two major uncertainties: one related to unpredictable demand variations, and another concerning imperfect input channels. A multi-variable LQ optimal control law is synthesized in a closed form and subjected to detailed analytical and numerical treatment. It is formally shown that despite uncertainties the controller establishes a non-negative and upper-bounded replenishment signal and the stock level does not cross the reference value. Conditions for warehouse capacity selection and obtaining full demand satisfaction at the depots are specified and demonstrated analytically.","PeriodicalId":294791,"journal":{"name":"2019 International Conference on Control, Automation and Diagnosis (ICCAD)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132501327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

ICCAD 2019 Papers, Sessions and Sessions Chairs ICCAD 2019论文，会议和会议主席

2019 International Conference on Control, Automation and Diagnosis (ICCAD) Pub Date : 2019-07-01 DOI: 10.1109/iccad46983.2019.9037957

引用次数: 0