2018 International Conference on Control, Automation and Information Sciences (ICCAIS)最新文献_第4页

SMC-PHD Target State Extraction Based on CFSFDP Clustering Algorithm 基于CFSFDP聚类算法的SMC-PHD目标状态提取

2018 International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2018-10-01 DOI: 10.1109/ICCAIS.2018.8570672

Feng Yang, Miaozang Zhang, P. Zhang

{"title":"SMC-PHD Target State Extraction Based on CFSFDP Clustering Algorithm","authors":"Feng Yang, Miaozang Zhang, P. Zhang","doi":"10.1109/ICCAIS.2018.8570672","DOIUrl":"https://doi.org/10.1109/ICCAIS.2018.8570672","url":null,"abstract":"The Sequential Monte Carlo PHD (SMC-PHD) filter which can solve the target tracking problems in nonlinear and non-Gaussian systems is an effective PHD implementation. The target state at each moment is characterized by a large number of weighted particles in the filtering algorithm. Therefore, extracting the target state effectively is the key to implementing SMC-PHD filtering. In the SMC-PHD filtering algorithm, the traditional K-means state extraction method commonly used is seriously affected by the initial clustering center which is prone to state estimation errors. To solve the above problems, a multi-target state extraction method based on Clustering Fast Search and Find of Density Peaks (CFSFDP) clustering algorithm is proposed. Based on numbers of weighted particles output by the SMC-PHD filter, the clustering centers and categories are clustered using the spatial distribution information of the particles, namely local density, distance, and weight information of the particles. Then, multiple target estimated states are extracted from each cluster. The simulation results show that the algorithm proposed in this paper significantly improves the accuracy of the algorithm compared with the classical K-means clustering method and the method Ristic proposed.","PeriodicalId":223618,"journal":{"name":"2018 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121822026","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

Rapid Control Prototyping Based Design of Buck Converter Using RTW/ MATLAB 基于RTW/ MATLAB的Buck变换器快速控制原型设计

2018 International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2018-10-01 DOI: 10.1109/ICCAIS.2018.8570700

Ali Mutahir, Zhaohui Gao, Husan Ali, H. Zaman, A. Ashraf, Boyan Sun

{"title":"Rapid Control Prototyping Based Design of Buck Converter Using RTW/ MATLAB","authors":"Ali Mutahir, Zhaohui Gao, Husan Ali, H. Zaman, A. Ashraf, Boyan Sun","doi":"10.1109/ICCAIS.2018.8570700","DOIUrl":"https://doi.org/10.1109/ICCAIS.2018.8570700","url":null,"abstract":"In this paper, rapid control prototyping (RCP) design of buck converter using Real-Time workshop (RTW/MATLAB) has been presented. The small signal model of buck converter is deduced using voltage mode control technique. Using frequency response method the gain and phase margins are obtained for open-loop frequency response, then proportional-integral-derivative controller with first order derivative filter (PIDF) is employed to design the feedback controller for closed-loop system of buck converter. Discrete simulation is carried out in MATLAB/SIMULINK software. The digital PIDF controller is then implemented through RCP design technique for buck converter. The advantage of RCP is that, it uses professional tools of Simulink model based on the ADC-PWM block sets and discrete PID controller block which can be converted into C-language program using RTW/MATLAB toolbox. Finally the overall program is then downloaded into the destination processor of DSP kit TMS320F2812 which is linked to the main circuit of buck converter composed of actual/experimental setup for closed loop implementation. The simulation and experimental results are compared, which indicate that the RTW-based feedback controller designed by RCP technique can effectively control the buck converter in the presence of input line voltage and output load current variations.","PeriodicalId":223618,"journal":{"name":"2018 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128844136","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

Analysis on Non-Strictly Identical Input of Safety Computer System Based on Fuzzy Theory 基于模糊理论的安全计算机系统非严格相同输入分析

2018 International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2018-10-01 DOI: 10.1109/ICCAIS.2018.8570664

Yuan Cao, Hongkang Lu, Tao Wen

引用次数: 0

Intelligent Compensation for Machining Error in the Batch Production Based on Automatic Line 基于自动线的批量生产加工误差的智能补偿

2018 International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2018-10-01 DOI: 10.1109/ICCAIS.2018.8570335

Nanyan Shen, GengSheng Zhu, Jing Li, Xing Wu, Kai Zhu

引用次数: 1

Centralized Multiple-View Information Fusion for Multi-Object Tracking Using Labeled Multi-Bernoulli Filters 基于标记多伯努利滤波器的多视图集中信息融合多目标跟踪

2018 International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2018-10-01 DOI: 10.1109/ICCAIS.2018.8570431

A. Gostar, T. Rathnayake, A. Bab-Hadiashar, G. Battistelli, L. Chisci, R. Hoseinnezhad

引用次数: 6

Vehicle Integrated Chassis Control via Multi-Input Multi-Output Sliding Mode Control 基于多输入多输出滑模控制的汽车底盘集成控制

2018 International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2018-10-01 DOI: 10.1109/ICCAIS.2018.8570490

Chunyun Fu, R. Hoseinnezhad, Kuining Li, Minghui Hu, Feihua Huang, Feiya Li

{"title":"Vehicle Integrated Chassis Control via Multi-Input Multi-Output Sliding Mode Control","authors":"Chunyun Fu, R. Hoseinnezhad, Kuining Li, Minghui Hu, Feihua Huang, Feiya Li","doi":"10.1109/ICCAIS.2018.8570490","DOIUrl":"https://doi.org/10.1109/ICCAIS.2018.8570490","url":null,"abstract":"Integrated chassis control (ICC) systems are designed to coordinate the control actions of individual chassis control systems, in order to achieve superior overall control performance. Many existing ICC systems employ an implicit mechanism to allocate/distribute the global target control action between the subsystems, which may lead to contradictory or suboptimal individual control actions. To deal with this shortcoming, this paper proposes an ICC solution based on multi-input multi-output sliding mode control. The coupled dynamics between the vehicle states to be controlled are explicitly incorporated in the proposed control design, and the control actions of active rear steer (ARS) and direct yaw-moment control (DYC) are jointly determined by the controller rather than allocated or distributed from a global target control action. Simulink-CarSim co-simulation results show that the ARS and DYC subsystems are well coordinated by the proposed controller to achieve favorable vehicle responses, including side slip angle, yaw rate and vehicle path. under a challenging driving condition.","PeriodicalId":223618,"journal":{"name":"2018 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127002875","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

A Rotating Machinery Fault Diagnosis Method for High-Speed Trains Based on Improved Deep Learning Network 基于改进深度学习网络的高速列车旋转机械故障诊断方法

2018 International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2018-10-01 DOI: 10.1109/ICCAIS.2018.8570502

J. Yang, Guo Xie, Yanxi Yang, Xin Li

引用次数: 1

Filtering-Based Layer-Wise Parameter Update Method for Training a Neural Network 基于过滤的神经网络分层参数更新方法

2018 International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2018-10-01 DOI: 10.1109/ICCAIS.2018.8570573

Siyu Ji, Kaikai Zhai, Chenglin Wen

引用次数: 0

The Challenges and Potential of Risk Assessment for Active Safety of Unmanned Tram 无人有轨电车主动安全风险评估的挑战与潜力

2018 International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2018-10-01 DOI: 10.1109/ICCAIS.2018.8570696

Kun Li

引用次数: 5

Multivariable Composite Prediction Based on Kalman Filtering and Charging and Discharging Scheduling Strategy of Energy Storage System 基于卡尔曼滤波的多变量复合预测与储能系统充放电调度策略

2018 International Conference on Control, Automation and Information Sciences (ICCAIS) Pub Date : 2018-10-01 DOI: 10.1109/ICCAIS.2018.8570330

Mingming Pan, Xiaohui Sun, Chenglin Wen

{"title":"Multivariable Composite Prediction Based on Kalman Filtering and Charging and Discharging Scheduling Strategy of Energy Storage System","authors":"Mingming Pan, Xiaohui Sun, Chenglin Wen","doi":"10.1109/ICCAIS.2018.8570330","DOIUrl":"https://doi.org/10.1109/ICCAIS.2018.8570330","url":null,"abstract":"By estimating and predicting state variables of the distributed generation system and that of electric load in real time, the real-time state of energy storage system can be obtained, which will provide an important basis for the dispatching department of the power system to formulate the power generation plan and the transmission plan. In distributed PV generation and multi-load systems, both the power supply system and the power consumption system are multi-source and non-stationary. Firstly, based on the polynomial neural network framework, the model of state variables changing with time series is constructed. Further non-stationary of the model above is taken into consideration and is transformed into Kalman filter frame. Secondly, the block state model and prediction model of the related variables are established, which contributes to real-time block estimation and prediction of composite variables and is expected to overcome the shortcomings of existing methods. Finally, the performance of the new method is tested and verified by simulation.","PeriodicalId":223618,"journal":{"name":"2018 International Conference on Control, Automation and Information Sciences (ICCAIS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114390192","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