2016 American Control Conference (ACC)最新文献_第8页

Kalman filter robustness for fatigue usage monitoring of flexible frame structures 基于卡尔曼滤波鲁棒性的柔性框架结构疲劳监测

2016 American Control Conference (ACC) Pub Date : 2016-07-06 DOI: 10.1109/ACC.2016.7526729

Nestor R. Polanco, E. Hernandez

引用次数: 0

Specialized algorithm for identification of stable linear systems using Lagrangian relaxation 利用拉格朗日松弛辨识稳定线性系统的专门算法

2016 American Control Conference (ACC) Pub Date : 2016-07-06 DOI: 10.1109/ACC.2016.7525034

Jack Umenberger, I. Manchester

引用次数: 4

Infrastructure cyberphysical systems and their users 基础设施网络物理系统及其用户

2016 American Control Conference (ACC) Pub Date : 2016-07-06 DOI: 10.1109/ACC.2016.7525317

T. Samad

引用次数: 1

Control of an uncertain Euler-Lagrange system with known time-varying input delay: A pde-based approach 具有已知时变输入延迟的不确定欧拉-拉格朗日系统的控制

2016 American Control Conference (ACC) Pub Date : 2016-07-06 DOI: 10.1109/ACC.2016.7525605

Indrasis Chakraborty, Serhat Obuz, Ryan A. Licitra, W. Dixon

引用次数: 5

Balancing control with neuro-fuzzy approach for electrical cart-seesaw system 电动跷跷板系统神经模糊平衡控制

2016 American Control Conference (ACC) Pub Date : 2016-07-06 DOI: 10.1109/ACC.2016.7525531

Jonqlan Lin, H. Lai, Julian Chang

引用次数: 0

Passivation and performance optimization using an extremum seeking co-simulation framework with application to Adaptive Cruise Control systems 基于极值求联合仿真框架的钝化与性能优化及其在自适应巡航控制系统中的应用

2016 American Control Conference (ACC) Pub Date : 2016-07-06 DOI: 10.1109/ACC.2016.7526629

Arash Rahnama, M. Xia, Shige Wang, P. Antsaklis

引用次数: 7

Faulty variable selection based fault reconstruction for industrial processes 基于故障变量选择的工业过程故障重构

2016 American Control Conference (ACC) Pub Date : 2016-07-06 DOI: 10.1109/ACC.2016.7526750

Chunhui Zhao, Wei Wang

{"title":"Faulty variable selection based fault reconstruction for industrial processes","authors":"Chunhui Zhao, Wei Wang","doi":"10.1109/ACC.2016.7526750","DOIUrl":"https://doi.org/10.1109/ACC.2016.7526750","url":null,"abstract":"Fault reconstruction has been widely applied for fault diagnosis recently, which, however, treats the fault data as a single subject without analyzing the specific effects of different variables. To address this problem, a faulty variable selection method is proposed which can extract more meaningful discriminant directions and probe into the specific faulty variables. By pairwise performing nested-loop Fisher discriminant analysis (NeLFDA) algorithm on normal and fault process data, some projection directions that are useful for classification between normal and fault cases are extracted. Then along these directions, an iterative faulty variable selection procedure is designed by evaluating ratio of variable contribution to the fault variations so that process variables that are significantly fault-relevant are identified and distinguished from those general variables. Based on variable selection results, fault reconstruction model is developed for faulty variables, which is used for fault diagnosis. Online fault diagnosis is then performed by dually checking the characteristics of fault samples for faulty variables and general variables. Its performance is illustrated with the industrial process data from the cut-made process of cigarette.","PeriodicalId":137983,"journal":{"name":"2016 American Control Conference (ACC)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129235099","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

Real-time combustion state identification via image processing: A dynamic data-driven approach 通过图像处理的实时燃烧状态识别:一种动态数据驱动的方法

2016 American Control Conference (ACC) Pub Date : 2016-07-06 DOI: 10.1109/ACC.2016.7525429

Michael Hauser, Yue Li, Jihang Li, A. Ray

{"title":"Real-time combustion state identification via image processing: A dynamic data-driven approach","authors":"Michael Hauser, Yue Li, Jihang Li, A. Ray","doi":"10.1109/ACC.2016.7525429","DOIUrl":"https://doi.org/10.1109/ACC.2016.7525429","url":null,"abstract":"This paper proposes a framework for analyzing video of physical processes as a paradigm of dynamic data-driven application systems (DDDAS). The algorithms were tested on a combustion system under fuel lean and ultra-lean conditions. The main challenge here is to develop feature extraction and information compression algorithms with low computational complexity such that they can be applied to real-time analysis of video captured by a high-speed camera. In the proposed method, image frames of the video is compressed into a sequence of image features. Then, these image features are mapped to a sequence of symbols by partitioning of the feature space. Finally, a special class of probabilistic finite state automata (PFSA), called D-Markov machines, are constructed from the symbol strings to extract pertinent features representing the embedded dynamic characteristics of the physical process. This paper compares the performance and efficiency of three image feature extraction algorithms: Histogram of Oriented Gradients, Gabor Wavelets, and Fractal Dimension. The k-means clustering algorithm has been used for feature space partitioning. The proposed algorithm has been validated on experimental data in a laboratory environment combustor with a single fuel-injector.","PeriodicalId":137983,"journal":{"name":"2016 American Control Conference (ACC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130613560","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: 14

Control on a molecular scale: A perspective 分子尺度上的控制:一个视角

2016 American Control Conference (ACC) Pub Date : 2016-07-06 DOI: 10.1109/ACC.2016.7525387

R. Findeisen, M. Grover, C. Wagner, Michael Maiworm, R. Temirov, F. Tautz, M. Salapaka, S. Salapaka, R. Braatz, S. Moheimani

{"title":"Control on a molecular scale: A perspective","authors":"R. Findeisen, M. Grover, C. Wagner, Michael Maiworm, R. Temirov, F. Tautz, M. Salapaka, S. Salapaka, R. Braatz, S. Moheimani","doi":"10.1109/ACC.2016.7525387","DOIUrl":"https://doi.org/10.1109/ACC.2016.7525387","url":null,"abstract":"Imaging and manipulating objects down to the molecular level plays a crucial role in many disciplines. It allows to unravel molecular phenomena, to form materials with new chemical and physical properties, or to build objects on an atomic scale. Science on the nanoscale is inherently interdisciplinary. It requires knowledge and insight into many fields, spanning from modeling, measuring, imaging, actuation to control. Often feedback control facilitates operation with molecular precision, despite the fact that many physical phenomena at the molecular level are still not well understood, and that stochastic and nonlinear effects are inherently present. This work provides an insight into some of the current control related research activities on a molecular scale. This is done considering examples from different fields: control related to scanning probe microscopy such as atomic force microscopy, controlled self assembly on a molecular scale, control aspects of molecular transport, and the use of control for manipulation of single molecules using macroscopic probe tips. The hope is that control related researchers, who are not experts in these fields, become aware of the opportunities present, which could also drive new theoretical developments.","PeriodicalId":137983,"journal":{"name":"2016 American Control Conference (ACC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124015632","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: 6

Observer-based event-triggered control: A discrete-time approach 基于观测器的事件触发控制:一种离散时间方法

2016 American Control Conference (ACC) Pub Date : 2016-07-06 DOI: 10.1109/ACC.2016.7525589

L. B. Groff, L. Moreira, J. G. D. Silva, D. Sbarbaro-Hofer

引用次数: 15