2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS)最新文献_第7页

A Novel YOLOv3-tiny Network for Unmanned Airship Obstacle Detection 一种用于无人飞艇障碍物检测的新型YOLOv3-tiny网络

2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2019-05-01 DOI: 10.1109/DDCLS.2019.8908875

Shan Ding, F. Long, Huijin Fan, Lei Liu, Yongji Wang

引用次数: 8

Fault Detection of Multimodal Chemical Process Based on CLTSA 基于CLTSA的多模态化工过程故障检测

2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2019-05-01 DOI: 10.1109/DDCLS.2019.8908884

Yankun Han, Ruirui Huang, Yandong Hou, Qianshuai Cheng

{"title":"Fault Detection of Multimodal Chemical Process Based on CLTSA","authors":"Yankun Han, Ruirui Huang, Yandong Hou, Qianshuai Cheng","doi":"10.1109/DDCLS.2019.8908884","DOIUrl":"https://doi.org/10.1109/DDCLS.2019.8908884","url":null,"abstract":"For modern chemical process often has multiple operational modes and monitoring data in the process are often nonlinear and high dimensional, a new fault detection method based on improved local tangent space alignment (LTSA) is proposed in this paper. Firstly, aiming at the characteristics of multi-modality of the chemical process, an improved LTSA algorithm is proposed in the paper, called correlation tangent space arrangement (CLTSA). In CLTSA, the variable $r$ is constructed and used to describe the relationship between the multivariate variables and reconstruct the global coordinates of monitoring data. Then, the incremental learning mechanism is introduced in CLTSA. For newly collected data, only some elements of the transition matrix need to be updated. And the matrix similarity statistics is established to maintain the size of the transition matrix, which has improved the efficiency of the algorithm. Finally, nonlinear principal elements in monitoring data are extracted through CLTSA and statistics $T^{2}$ and $SPE$ are used to monitor the change of the principal elements. When the monitored amount exceeds the threshold, it is determined that a fault has occurred in the chemical process. The simulation results of TE process show that the method proposed in the paper has a high fault detection rate and provides a new way for fault detection of multi-modal nonlinear chemical processes.","PeriodicalId":6699,"journal":{"name":"2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"8 1","pages":"598-603"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83641733","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

Finite-Duration Consensus of Multi-Agent Systems Using a Generic Attracting Law 基于通用吸引律的多智能体系统的有限持续一致性

2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2019-05-01 DOI: 10.1109/DDCLS.2019.8908927

Mingxuan Sun, Xing Li

引用次数: 1

Model Analysis and Design of 3D Printing Control System Based on Cement Components 基于水泥构件的3D打印控制系统模型分析与设计

2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2019-05-01 DOI: 10.1109/DDCLS.2019.8908964

H. Lu, Renren Wang

引用次数: 0

Feedback Control of Switched Linear Systems with Event-Triggered Link 具有事件触发链路的切换线性系统的反馈控制

2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2019-05-01 DOI: 10.1109/DDCLS.2019.8908959

Xiaoqian Luo, Xinxin Wang, Tai-Fang Li

引用次数: 3

A Variable Selection Method for Fault Isolation through Bayesian Information Criterion 基于贝叶斯信息准则的故障隔离变量选择方法

2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2019-05-01 DOI: 10.1109/DDCLS.2019.8909044

Lang Liu, Weidong Yang, Hong Zhang, Huijin Fan, Bo Tao

引用次数: 0

Health Maintenance Decisions Based on Hazard Rate Function under Degradation Process 退化过程下基于危害率函数的健康维护决策

2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2019-05-01 DOI: 10.1109/DDCLS.2019.8908916

An Liu, Xiao-fei Lu, Shaolin Hu, Weihui He

{"title":"Health Maintenance Decisions Based on Hazard Rate Function under Degradation Process","authors":"An Liu, Xiao-fei Lu, Shaolin Hu, Weihui He","doi":"10.1109/DDCLS.2019.8908916","DOIUrl":"https://doi.org/10.1109/DDCLS.2019.8908916","url":null,"abstract":"The classical Hazard Rate Function (HRF) is typically used to make preventative maintenance (PM) decisions and always estimates HRF based on time to failure data. Even so, PM determination using conventional HRF is not suitable for systems with condition monitoring. The system is stopped checking and maintaining when the measured health state exceeds a predetermined threshold, which is always referred to as a soft failure. Since the application of HRF for PM decision making has great advantages, the classic HRF should be extended to combine soft and hard failure of systems with condition monitoring. In this paper, we define the HRFs of hard and soft failure for system under condition monitoring and propose a method to estimate the HRFs with data of failure time. We discuss in detail the relationship between these two HRFs and the classical HRF. With double stochastic processes (processes of degradation and measured healthy status), the properties of these HRFs are also researched. Further the optimal maintenance decisions are made for non-repairable and repairable systems upon these two types of HRFs. Eventually, the idea of this paper is verified by numerical examples.","PeriodicalId":6699,"journal":{"name":"2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"109 1","pages":"962-968"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79125215","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

Performance Assessment of Non-Gaussian Systems Based on Double Error Entropy Minimization 基于双误差熵最小化的非高斯系统性能评估

2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2019-05-01 DOI: 10.1109/DDCLS.2019.8909025

Han Zhang, Jinglin Zhou, Jing Wang

引用次数: 1

Zeroing-Type Recurrent Neural Network for Solving Time-Dependent Lyapunov Equation with Noise Rejection 具有噪声抑制的时变Lyapunov方程的归零型递归神经网络

2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2019-05-01 DOI: 10.1109/DDCLS.2019.8908866

Jingkun Yan, Long Jin, Rui Zhang, Hongxin Li, Jiliang Zhang, Huiyan Lu

{"title":"Zeroing-Type Recurrent Neural Network for Solving Time-Dependent Lyapunov Equation with Noise Rejection","authors":"Jingkun Yan, Long Jin, Rui Zhang, Hongxin Li, Jiliang Zhang, Huiyan Lu","doi":"10.1109/DDCLS.2019.8908866","DOIUrl":"https://doi.org/10.1109/DDCLS.2019.8908866","url":null,"abstract":"It is well known that many engineering communities are confronted with the problem of Lyapunov equation (LE) solving, and a mass of methods are proposed to solve the problem under the circumstance of no-noise. Whereas, noise is inevitable during actual experiments due to all kinds of factors, and models with resistance to noises are needed. To fill this lacuna, this paper proposes a zeroing-type recurrent neural network (ZTRNN) model for the task of solving the time-dependent LE. Additionally, the original zeroing neural network (OZNN) model is described for the purpose of comparison. Rigorous theoretical analyses concerning the convergence and the resistance to noises of the ZTRNN model are presented. Further, a numerical example of the time-dependent LE is solved by using the ZTRNN model and the OZNN model separately. Computer simulations are carried out perfectly and the results verify the feasibility and resistance to noises of the ZTRNN model, reflecting that the ZTRNN model outperforms the OZNN model in terms of resistance to noises.","PeriodicalId":6699,"journal":{"name":"2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"44 1","pages":"366-371"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85627084","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

An Improved Kalman Filter Based on Self-adaptive Adjustment Parameters 基于自适应参数调整的改进卡尔曼滤波

2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS) Pub Date : 2019-05-01 DOI: 10.1109/DDCLS.2019.8909000

Shenglun Yi, X. Ren, Tingli Su

引用次数: 0