2015 20th International Conference on Process Control (PC)最新文献_第7页

FPGA-based explicit model predictive control for closed-loop control of intravenous anesthesia 基于fpga的显式模型预测控制用于静脉麻醉闭环控制

2015 20th International Conference on Process Control (PC) Pub Date : 2015-06-09 DOI: 10.1109/PC.2015.7169936

Deepak D. Ingole, Juraj Holaza, B. Takács, M. Kvasnica

{"title":"FPGA-based explicit model predictive control for closed-loop control of intravenous anesthesia","authors":"Deepak D. Ingole, Juraj Holaza, B. Takács, M. Kvasnica","doi":"10.1109/PC.2015.7169936","DOIUrl":"https://doi.org/10.1109/PC.2015.7169936","url":null,"abstract":"Over the last decade, anesthesia research community witnessed numerous advances in controllers and their implementation platforms to control the depth of anesthesia (DoA) in a patient undergoing surgery. Today's operating theaters are extremely complex and crowded. New surgical techniques bring new medical technologies and more devices in the operation rooms, which often results in complex configurations, computer based control, and cable clutter. In an effort to reduce hardware size and to the improve quality control of anesthesia, we present a field programmable gate array (FPGA) based explicit model predictive control (EMPC) scheme which can take into account the control and state constraints that naturally arise in anesthesia. Real-time implementation of model predictive control (MPC), mainly requires solving an optimization problem at regular time intervals. We propose an FPGA-based EMPC-on-a-chip algorithm with customized 32-bit floating-point addition, substation, and multiplication algorithms. Simulation results with four compartmental PK-PD model, input constraints and a variable bispectral index (BIS) set-point are presented. The real-time simulation results are achieved with Xilinx's Vertex 4 XC4VLX25-10FF668 FPGA.","PeriodicalId":173529,"journal":{"name":"2015 20th International Conference on Process Control (PC)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122405685","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

Decentralized controller for nonlinear drum boiler: Youla parametrization approach 非线性汽包锅炉的分散控制器:优拉参数化方法

2015 20th International Conference on Process Control (PC) Pub Date : 2015-06-09 DOI: 10.1109/PC.2015.7169940

Peter Balko, D. Rosinová

引用次数: 0

Internal model pre-processing tool 内部模型预处理工具

2015 20th International Conference on Process Control (PC) Pub Date : 2015-06-09 DOI: 10.1109/PC.2015.7169990

Radim Hýl, R. Wagnerová

{"title":"Internal model pre-processing tool","authors":"Radim Hýl, R. Wagnerová","doi":"10.1109/PC.2015.7169990","DOIUrl":"https://doi.org/10.1109/PC.2015.7169990","url":null,"abstract":"In industry the model predictive control (MPC) solutions are for their high computational requirements usually implemented to the PC-based devices. The main goal of our study is to implement an MPC algorithm to the programmable logic controller (PLC). This paper describes an initialization part of our solution, which represents an internal model pre-processing algorithm implemented to the function blocks created in PLC programming standard IEC 61131-3. The pre-processing algorithm changes model representation form of multivariable system (MIMO) from continuous transfer function matrix to generalized discrete state-space model. At the end of the paper there is shown created comfortable interface used for inserting of transfer functions, process model parameterization and future MPC tuning. This interface communicating with pre-processing algorithm running on PLC allows to specify MIMO internal model by continuous transfer function matrix and the discrete state-space internal model used during control is created automatically. The operator does not have to use MATLAB or other expansive mathematical software for creation of discrete state-space representation and the most widespread mathematical description in industry known like continuous transfer function can be used. The constants of transfer functions are usually obtained by operator from current visualizations on the plant.","PeriodicalId":173529,"journal":{"name":"2015 20th International Conference on Process Control (PC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132409079","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

Export of explicit model predictive control to python 将显式模型预测控制导出到python

2015 20th International Conference on Process Control (PC) Pub Date : 2015-06-09 DOI: 10.1109/PC.2015.7169942

B. Takács, Juraj Holaza, Juraj Števek, M. Kvasnica

引用次数: 9

Synchronization of passifiable linear networks by output feedback 基于输出反馈的可被动线性网络同步

2015 20th International Conference on Process Control (PC) Pub Date : 2015-06-09 DOI: 10.1109/PC.2015.7169937

I. Junussov, Alexander L. Fradkov

引用次数: 0

System identification and stochastic estimation of dielectric properties of a spherical particle using AC-induced electro-rotation 基于交流感应电旋转的球形粒子介电特性系统辨识与随机估计

2015 20th International Conference on Process Control (PC) Pub Date : 2015-06-09 DOI: 10.1109/PC.2015.7169985

P. Benhal, J. Chase

引用次数: 2

Data-driven method for fault isolation in technical systems 技术系统故障隔离的数据驱动方法

2015 20th International Conference on Process Control (PC) Pub Date : 2015-05-21 DOI: 10.1109/SIBCON.2015.7147169

A. Zhirabok, S. Pavlov

引用次数: 1