检索结果-内蒙古大学图书馆

Intelligent control for Flotation process

IFAC Proceedings Volumes 2008年第2期41卷 10009-10014页

作者： Zengxian Geng Tianyou Chai Heng Yue Hong Wang Chunyi Su Key Laboratory of Process Industry Automation Ministry of Education Shenyang 110004 China (Tel: 086-024-83674489 Research Center of Automation Northeastern University Shenyang 110004 China Control Systems Centre University of Manchester Manchester M60 1QD UK Department of Mechanical Engineering Concordia University Quebec Canada

In the flotation process, the concentrate grade and the tailing grade are crucial technical indices which reflect the product quality and efficiency. There are strong nonlinearity and uncertainty in such technical indices dynamic behaviors, which can hardly be described using accurate mathematical model. The technical indices which cannot be measured online continuously vary with boundary conditions. Therefore conventional control methods are incapable of keeping the actual the concentrate grade and the tailing grade within the target ranges. In this paper, an intelligent control method comprised of the setting layer and the closed loop control layer for the flotation reagent addition to the process has been presented. In flotation reagent feeding setting layer, a unit reagent pre-setting model, a feedback compensator and a feed forward compensator RBR based on (Rule-based reasoning) are integrated with a flotation reagent computation model to set the flotation reagent feeding. The control system updates automatically flotation reagent feeding when the boundary conditions changes. Successfully industrial application has shown that the concentrate grate has been increased by 0.52%, the tailing grade has been reduced by 4%, and the consumption of the flotation reagent feeding has been reduced by 17.5%. Significant application effect has been achieved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

IEEE Transactions on Haptics: Editorial

引用

IEEE Transactions on Haptics 2008年第1期1卷 2-8页

作者： Edward Colgate, J. Lederman, Susan Prattichizzo, Domenico Barbagli, Federico Basdogan, Cagatay Buss, Martin Ernst, Marc Frisoli, Antonio Gillespie, Brent Grant, Danny Harders, Matthias Hayward, Vincent Jones, Lynette Kajimoto, Hiroyuki Kappers, Astrid Kheddar, Abderrahmane Lin, Ming C. MacLean, Karon Miller, Brian Noma, Haruo Okamura, Allison M. O'Malley, Mareia Ryu, Jeha Tan, Hong Z. Yokokohji, Yasuyoshi Department of Psychology School of Computing Queen's University Canada IEEE Robotics and Automation Society Tübingen Germany Stanford University's Computer Science Department Tübingen Germany Institute of Automatic Control Engineering Technische Universität München Germany Independent Research Group Multisensory Perception and Action Max Planck Institute for Biological Cybernetics Tübingen Germany Department of Applied Mechanics SSSA Japan Research Division Virtual Reality and Telerobotic Systems PERCRO Laboratory Japan Department of Mechanical Engineering Japan Department of Robotics McGill University Canada Computer Vision Lab ETH Zurich Japan Virtual Reality in Medicine Group Japan IEEE CS/RAS Technical Committee on Haptics Japan Department of Electrical and Computer Engineering McGill University Canada Department of Mechanical Engineering MIT Japan University of Electro-Communications Japan Department of Physics and Astronomy Utrecht University Netherlands University of Evry France Chapel Hill United States Department of Computer Science University of British Columbia Canada ATR Knowledge Science Lab United Kingdom Department of Mechanical Engineering Denmark Johns Hopkins University United States Laboratory for Computational Sensing and Robotics United Kingdom Engineering Research Center for Computer-Integrated Surgical Systems and Technology United States Mechanical Engineering and Materials Science Department Rice University United States Korea Republic of Department of Electrical and Computer Engineering Mechanical Engineering and Psychological Sciences Purdue University United States Department of Mechanical Engineering and Science Graduate School of Engineering Kyoto University Japan

No abstract available

关键词：

来源：评论

学校读者我要写书评

暂无评论

NONLINEAR NETWORK STRUCTURES FOR FEEDBACK control

引用

Asian Journal of control 2008年第4期1卷

作者： F.L. Lewis Dept. of Electical Engineering The University of Texas at Arlington U.S.A. F. L. Lewis was born in Wärzburg. Germany subsequently studyning in Chile and Goruonstoun School in Scotland. He obtained the Bachelor's Degree in Physics/Electrical Engineering and the Master's of Electrical Engineering Degree at Rice University in 1971. He spent six years in the U.S. navy serving as Navigator aboard the frigate USS Trippe (FF-1075) and Executive Officer and Acting Commanding Officer aboard USS Salinan (ATF-161). In 1977 he received the Master's of Science in Aeronautical Engineering from the University of West Florida. In 1981 he obtained the Ph.D. degree at The Georgia Institute of Technology in Atlanta where he was employed as a professor from 1981 to 1990 and is currently an Adjunct Professor. He is a Professor of Electrical Engineering at The University of Texas at Arlington where he was awarded the Moncrief-O'Donnell Endowed Chair in 1990 at the Automation and Robotics Research Institute. Dr. Lewis has studied the geometric analytic and structural properties of dynamical systems and feedback control automation. His current interests include robotics intelligent control neural and fuzzy systes nonlinear systems and manufacturing process control. He is the author/co-author of 2 U.S. patents 124 journal papers 20 chapters and encyclopedia articles 210 refereed conference papers seven books: Optimal Control Optimal Estimation Applied Optimal Control and Estimation Aircraft Control and Simulation Control of Robot Manipulators Neural Network Control High-Level Feedback Control with Neural Networks and the IEEE reprint volume Robot Control. Dr. Lewis is a registered Professional Engineer in the State of Texas and was selected to the Editorial Boards of International Journal of Control Neural Computing and Applications and Int. J. Intelligent Control Systems. He is the recipient of an NSF Research Initiation Grant and has been continuously funded by NSF since 1982. Since 1991 he has received $1.8 m

A framework is given for controller design using Nonlinear Network Structures, which include both neural networks and fuzzy logic systems. These structures possess a universal approximation property that allows them to be used in feedback control of unknown systems without requirements for linearity in the system parameters or finding a regression matrix. Nonlinear nets can be linear or nonlinear in the tunable weight parameters. In the latter case weight tuning algorithms are not straightforward to obtain. Feedback control topologies and weight tuning algorithms are given here that guarantee closed-loop stability and bounded weights. Extensions are discussed to force control, backstepping control, and output feedback control, where dynamic nonlinear nets are required.

关键词： Intelligent feedback control neural networks neural network structures basis function networks fuzzy control fuzzy-neural networks universal approximation adaptive nonparametric control learning control systems

来源：评论

学校读者我要写书评

暂无评论

TRACKING control IN THE PRESENCE OF NONLINEAR DYNAMIC FRICTIONAL EFFECTS: ROBOT EXTENSION

引用

Asian Journal of control 2008年第3期1卷

作者： M. Feemster D.M. Dawson A. Behal W. Dixon Matthew Feemster received the B.S degree in Electrical Engineering from Clemson University Clemson South Carolina in December 1994. Upon graduation he remained at Clemson University and received the M.S. degree in Electrical Engineering in 1997. During this time he also served as a research/teaching assistant. His research work focused on the design and implementation of various nonlinear control algorithms with emphasis on the induction motor and mechanical systems with friction present. He is currently working toward his Ph.D. degree in Electrical Engineering at Clemson University. Darren M. Dawson was born in 1962 in Macon Georgia. He received an Associate Degree in Mathematics from Macon Junior College in 1982 and a B.S. Degree in Electrical Engineering from the Georgia Institute of Technology in 1984. He then worked for Westinghouse as a control engineer from 1985 to 1987. In 1987 he returned to the Georgia Institute of Technology where he received the Ph.D. Degree in Electrical Engineering in March 1990. During this time he also served as a research/teaching assistant. In July 1990 he joined the Electrical and Computer Engineering Department and the Center for Advanced Manufacturing (CAM) at Clemson University where he currently holds the position of Professor. Under the CAM director's supervision he currently leads the Robotics and Manufacturing Automation Laboratory which is jointly operated by the Electrical and Mechanical Engineering departments. His main research interests are in the fields of nonlinear based robust adaptive and learning control with application to electro-mechanical systems including robot manipulators motor drives magnetic bearings flexible cables flexible beams and high-speed transport systems. Aman Behal was born in India in 1973. He received his Masters Degree in Electrical Engineering from Indian Institute of Technology Bombay in 1996. He is currently working towards a Ph.D in Controls and Robotics at Clemson University. His research focuses on the control of no

In this paper, we extend the observer/control strategies previously published in [25] to an n -link, serially connected, direct drive, rigid link, revolute robot operating in the presence of nonlinear friction effects modeled by the Lu-Gre model. In addition, we also present a new adaptive control technique for compensating for the nonlinear parameterizable Stribeck effects. Specifically, an adaptive observer/controller scheme is developed which contains a feedforward approximation of the Stribeck effects. This feedforward approximation is used in a composite controller/observer strategy which forces the average square integral of the position tracking error to an arbitrarily small value. Experimental results are included to illustrate the performance of the proposed controllers.

关键词： Friction compensation nonlinear control

来源：评论

学校读者我要写书评

暂无评论

Linear and nonlinear control of musculoskeletal systems

Linear and nonlinear control of musculoskeletal systems

引用

25th IASTED International Conference on Modelling, Identification, and control, MIC 2006

作者： Fazekas, Csaba Szederkényi, G. Hangos, K.M. Process Control Research Group Computer and Automation Research Institute HAS P.O. Box 63 H-1518 Budapest Hungary

ISBN: (纸本)0889865515

The methods of nonlinear systems and control theory were applied to a simple musculoskeletal system with one joint and two muscles in this paper. For this purpose, a nonlinear input-affine state-space model has been developed for this system with a flexor and an extensor muscle taking into account the nonlinear muscle and movement dynamics. Two types of controllers were designed: a linear pole-placement servo designed for the locally linearized model, and a nonlinear controller based on asymptotic output tracking method. It is expected and forward that during a movement with a large range of motion the nonlinearities of the system will be dominant and the nonlinear methods will outperform the linear ones. The output reference tracking properties of the controllers have been investigated by simulation and it has been found that the nonlinear controller gives more accurate tracking with no overshoots than the linear one.

关键词： Muscle

来源：评论

学校读者我要写书评

暂无评论

BAYESIAN QUBIT STATE ESTIMATION

引用

IFAC Proceedings Volumes 2006年第1期39卷 949-954页

作者： Attila Magyar Dénes Petz Katalin M. Hangos Process Control Research Group Computer and Automation Research Institute Budapest Hungary Alfréd Rényi Institute of Mathematics Budapest Hungary

In this paper a Bayesian approach for estimating the state of a qubit is proposed. It consists of two phases. First a component-wise separate Bayesian estimate of the Bloch vector components is calculated in the form of β -distributions. Then a regularization step is performed to respect the constraint that the Bloch vector must be in the unit ball. The properties of the proposed algorithm are investigated by simulation.

关键词： System identification Bayesian estimation quantum systems regularization

来源：评论

学校读者我要写书评

暂无评论

Adaptive pseudo linear RBF model for process control

引用

3rd International Symposium on Neural Networks, ISNN 2006 - Advances in Neural Networks

作者： Yu, Ding-Wen Yu, Ding-Li Department of Automation Northeast University Qinhuangdao China Control Systems Research Group School of Engineering Liverpool John Moores University Byrom Street Liverpool L3 3A United Kingdom

ISBN: (纸本)3540344373

A pseudo-linear radial basis function (PLRBF) network is developed in this paper. This network is used to model a real process and its weights are on-line updated using a recursive orthogonal least squares (ROLS) algorithm. The developed adaptive model is then used in model predictive control strategy, which is applied to a pilot multivariable chemical reactor. The first stage of the project, simulation study, has been investigated and is presented. The effectiveness of the adaptive control in improving the closed-loop performance has been demonstrated for process time-varying dynamics and model-process mismatch. © Springer-Verlag Berlin Heidelberg 2006.

关键词： process control

来源：评论

学校读者我要写书评

暂无评论

DYNAMIC ANALYSIS AND control OF CHEMICAL AND BIOCHEMICAL REACTION NETWORKS

引用

IFAC Proceedings Volumes 2006年第2期39卷 165-170页

作者： Irene Otero-Muras Gábor Szederkényi Antonio A. Alonso Katalin M. Hangos Department of Process Engineering IIM-CSIC Eduardo Cabello 6 36208 Vigo Spain Process Control Research Group Computer and Automation Research Institute H-1518 Budapest P.O.Box 63 Hungary

Metabolic or cell signalling pathways are examples of biochemical networks exhibiting possible complex dynamics in the form of steady-state multiplicity, sustained oscillations or even deterministic chaos. The origin of these nonlinear phenomena is not always well understood, nor it can be systematically predicted beyond a case by case basis. Despite considerable progress in dynamic aspects, efforts are still needed to develop efficient and robust methods of stabilization and control of reaction networks. In this work, we combine concepts and tools from irreversible thermodynamics and systems theory to explore the underlying dynamic properties of a general class of chemical and biochemical networks. Lyapunov and passivity based methods are given for the systematic design of globally stabilizing feedback controllers in both the concentration space and a novel minimal description of the kinetic networks dynamics: the reaction space.

关键词： biochemical reaction networks passivity nonlinear control entropy

来源：评论

学校读者我要写书评

暂无评论

Constrained control of a low power industrial gas turbine based on input-output linearization

Constrained control of a low power industrial gas turbine ba...

引用

5th International Conference on control and automation, ICCA'05

作者： Ailer, Piroska Pongrácz, Barna Szederkényi, Gábor Knorr-Bremse Brake Systems Ltd. Major u. 69 H-1119 Budapest Hungary Process Control Research Group Computer and Automation Research Institute P.O. Box 63 H-1518 Budapest Hungary

ISBN: (纸本)0780391381

A constrained linear optimal control for a lowpower industrial gas turbine based on input-output linearization is proposed in this paper. It uses a nonlinear state space model of the gas turbine in input-affine form based on first engineering principles. According to the control aims the nonlinear model is inputoutput linearized and an LQ servo controller is developed for the linearized model. We have some additional constraints on the state and input variables of the closed-loop plant fed back by the LQ servo controller. These constraints can be kept in a simple way designing an MPT-controller. The complete control structure is investigated by simulation studies. © 2005 IEEE.

关键词： control theory

来源：评论

学校读者我要写书评

暂无评论

Constrained control of a low power industrial gas turbine based on input-output linearization

Constrained control of a low power industrial gas turbine ba...

引用

International Conference on control and automation (ICCA)

作者： P. Ailer B. Pongracz G. Szederkenyi Knorr-Bremse Brake Systems Limited Budapest Hungary Process Control Research Group Computer and Automation Research Institute Budapest Hungary

A constrained linear optimal control for a low-power industrial gas turbine based on input-output linearization is proposed in this paper. It uses a nonlinear state space model of the gas turbine in input-affine form based on first engineering principles. According to the control aims the nonlinear model is input-output linearized and an LQ servo controller is developed for the linearized model. We have some additional constraints on the state and input variables of the closed-loop plant fed back by the LQ servo controller. These constraints can be kept in a simple way designing an MPT-controller. The complete control structure is investigated by simulation studies.

关键词： Gas industry Industrial control Turbines Power system modeling Engines State-space methods Servomechanisms Ducts Combustion Optimal control

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：