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R &D at the laboratory for control systems and automation of the Korea Advanced institute of Science and Technology

Robotica 2009年第4期8卷 333-338页

作者： Hyung S. Cho Laboratory for Control Systems and Automation Department of Production Engineering Korea Advanced Institute of Science and Technology P. O. Box 150 Cheongryang Seoul (Republic of Korea)

This paper describes the research activities at the laboratory for control systems and automation (LCA) which is a section of the Production Department of Korea Advanced institute of Science and Technology (KAIST). LCA's research activities are focused on providing fundamental technologies to cope with the current trends in manufacturing automation. The R & D activities at the laboratory cover diverse areas. The research activities at the laboratory are classified into three sections—robotics and automation, fluid servo control, and manufacturing process control. Detailed explanations are given here on robotics and its application to automation. As a laboratory belonging to a nation's leading educational institution, LCA also conducts active educational activities. Such educational programs are also introduced in detail.

关键词： Robotic manipulator Flexible manufacturing system Automated Guided Vehicle Teleoperator Assembly system Fuzzy control Expert control Neural network

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Dynamical modeling and identification of a GnRH neuron

Dynamical modeling and identification of a GnRH neuron

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作者： Csercsik, Dávid Szederkényi, Gábor Hangos, Katalin M. Farkas, Imre Process Control Research Group Systems and Control Laboratory Computer and Automation Research Institute Budapest Hungary Department of Endocrine Neurobiology Institute of Experimental Medicine HAS Budapest Hungary

ISBN: (纸本)9783902661494

GnRH neurons, as key elements of the reproductive neuroendocrine system, have important central regulating role in the dynamics of the hormonal cycle. A Hodgkin-Huxley type neural model is proposed in this paper, that takes into account up-to-date biological literature data related to ion channels. The proposed neuron model is highly nonlinear in parameters and the evaluation of the objective function is computationally flexpensive, therefore the asynchronous parallel pattern search (APPS) procedure has been used for identification. The model with high number of estimated parameters provides a qualitatively good fit of both voltage clamp and current clamp traces. © 2009 IFAC.

关键词： Neurons

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Model synthesis identification a Hodgkin-Huxley-type neuron model 10

Model synthesis identification a Hodgkin-Huxley-type neuron ...

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2009 10th European control Conference, ECC 2009

作者： Csercsik, David Szederkenyi, Gabor Hangos, Katalin M. Farkas, Imre Process Control Research Group Systems and Control Laboratory Computer and Automation Research Institute Budapest Hungary Department of Endocrine Neurobiology Institute of Experimental Medicine HAS Budapest Hungary

ISBN: (纸本)9783952417393

GnRH neurons are key elements of the reproductive neuroendocrine system and play important central regulating role in the dynamics of the hormonal cycle. A conductance-based Hodgkin-Huxley model structure is proposed in this paper in the form of nonlinear ordinary differential equations that is able to take into account up-to-date biological literature data related to ion channels. Measurement data were available for parameter estimation, which are originated from laboratory experiments done in the institute of Experimental Medicine of the Hungarian Academy of Sciences in the form of whole cell patch-clamp recordings. The proposed neuron model is highly nonlinear in parameters and the evaluation of the objective function is computationally expensive, therefore the asynchronous parallel pattern search (APPS) procedure has been used for identification which is a gradient-free optimization method that can handle linear equality and inequality constraints and has advantageous convergence properties. The model with high number of estimated parameters provides a qualitatively good fit of both voltage clamp and current clamp traces. © 2009 EUCA.

关键词： Parameter estimation

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Design and implementation of an improved and reliable pressurizer controller at the paks NPP

Design and implementation of an improved and reliable pressu...

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7th IFAC International Symposium on Fault Detection, Supervision and Safety of Technical systems, SAFEPROCESS'09

作者： Bartha, Tamás Fazekas, Csaba Varga, István Systems and Control Laboratory Computer and Automation Research Institute HAS Kende u. 13-17 H-1111 Budapest Hungary

ISBN: (纸本)9783902661463

This paper presents the design and implementation of a pressure controller for the pressurizer of the primary circuit in the Paks Nuclear Power Plant (NPP) in Hungary. The controlled process is part of a highly safety-critical environment, therefore strict reliability requirements are imposed on both the hardware and the software of the controller. The implemented controller provides robust performance and it has a redundant and distributed architecture in order to meet these demands. The control system includes measurement and control PLCs, a continuous power controller and a special supervisor module. The pressure controller has been implemented and is in use in all the four units of the Paks NPP. © 2009 IFAC.

关键词： Nuclear power plants

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Fault tolerant actuators and drives - Structures, fault detection principles and applications

Fault tolerant actuators and drives - Structures, fault dete...

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7th IFAC International Symposium on Fault Detection, Supervision and Safety of Technical systems, SAFEPROCESS'09

作者： Muenchhof, Marco Beck, Mark Isermann, Rolf Technische Universität Darmstadt Institute of Automatic Control Laboratory for Control Systems and Process Automation Darmstadt Germany

ISBN: (纸本)9783902661463

As fault detection and fault diagnosis are more and more finding their way into modern industrial mechatronic products, it is now time to take the next step. Based on the research efforts for fault detection and diagnosis, a platform has been prepared for research on fault management, i.e. automatic reactions of the system to continue operation after the detection of faults. These reactions may employ hardware redundancy (i.e. switching from a faulty actuator to another, intact one) or analytical redundancy (i.e. switching from a faulty sensor to a "model sensor" or "soft sensor"). A total fault tolerance concept must encompass all components of a system, i.e. the actuators and drives, the sensors as well as the controller and communication. In many cases, a degradation of functions has to be accepted after a fault has appeared. This contribution will center on actuators and drives showing real-world examples of prototypical realizations and examples from industrial products. Concentrating on the most widespread actuation principles, the paper will focus on electric drives and hydraulic actuators. First, a review is given on fault tolerance principles and general structural considerations e.g. hot-standby and cold-standby, focusing on the scheme of an overall fault-tolerant control system. Then, fault statistics for real actuators and drives will be presented. These fault statistics give hints on the parts of the actuators that are most susceptible to faults. Different designs of fault tolerant actuators and drives, which have been realized, shall be presented and evaluated with respect to their capabilities of sustaining faults. Finally, an outlook for fault-tolerant mechatronic systems will be given. © 2009 IFAC.

关键词： Aerospace applications

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A NEW NEURAL NETWORK-BASED ADAPTIVE ILC FOR NONLINEAR DISCRETE-TIME systems WITH DEAD ZONE SCHEME

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Journal of systems Science & Complexity 2009年第3期22卷 435-445页

作者： Ronghu CHI Zhongsheng HOU Institute of Autonomous Navigation and Intelligent Control School of Automation and Electrical EngineeringQingdao University of Science and Technology Qingdao 266042 China. Advanced Control Systems Laboratory School of Electronics and Information Engineering Beijing JiaotongUniversity Beijing 100044 China.

By introducing a deadwzone scheme, a new neural network based adaptive iterative learning control （ILC）（NN-AILC） scheme is presented for nonlinear discrete-time systems, where the NN weights are time-varying. The most distinct contribution of the proposed NN-AILC is the relaxation of the identical conditions of initial state and reference trajectory, which are common requirements in traditional ILC problems. Convergence analysis indicates that the tracking error converges to a bounded ball, whose size is determined by the dead-zone nonlinearity. computer simulations verify the theoretical results.

关键词： Adaptive control iterative learning control neural network non-identical initial condition,non-identical trajectory.

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Networked control approaches for a nuclear power plant pressurizer subsystem ?

Networked control approaches for a nuclear power plant press...

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1st IFAC Workshop on Estimation and control of Networked systems, NecSys'09

作者： Szederkényi, G. Péni, T. Gáspár, P. Bokor, J. Systems and Control Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences PO. Box 63 H-1518 Budapest Hungary

ISBN: (纸本)9783902661524

This paper extends former results about the networked reference tracking control of a pressurizer in a pressurized water nuclear power plant. An L2-gain based method is used in a deterministic framework to compute the maximum allowable transmit intervals (MATIs) for the actually implemented dynamic inversion based controller that still guarantee the required performance. Furthermore, a stochastic linear quadratic regulator with a state estimator is also designed that can take packet losses into consideration. It is shown through the comparison that both methods are applicable for networked control but the LQ controller combined with a Kalman filter has better output variance properties. © 2009 IFAC.

关键词： Nuclear power plants

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An integrated control of shading blinds, natural ventilation, and HVAC systems for energy saving and human comfort

An integrated control of shading blinds, natural ventilation...

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IEEE International Conference on automation Science and Engineering (CASE)

作者： Biao Sun Peter B. Luh Qing-Shan Jia Ziyan Jiang Fulin Wang Chen Song Center of Intelligent and Networked Systems (CFINS) Tsinghua National Laboratory of Information Science and Technology Tsinghua University Beijing China Department of Electrical and Computer Engineering University of Connecticut Storrs CT USA Department of Building Science Tsinghua University Beijing China Safety and Control Systems China and the Tsinghu-UTC Research Institute of Integrated Building Energy United Technologies Research Center Inc. Beijing China

Improving the control of shading blinds, lights, natural ventilation, and HVAC systems while satisfying human comfort requirements can result in significant energy cost savings with time-of-day electricity pricing. Traditionally, the above-mentioned devices are controlled separately. In this paper, a novel formulation for the integrated control and the corresponding solution methodology are presented. The problem is to minimize daily energy costs of lights and HVAC systems while satisfying equipment capacities, system dynamics, and human comfort. The problem is complicated since 1) individual rooms are coupled as they compete for the HVAC with limited capacity and nonlinear characteristics, and 2) the problem is believed to be NP-hard in view that decision variables are all discrete. A solution methodology that combines Lagrangian relaxation and stochastic dynamic programming is developed within the surrogate optimization framework to obtain near-optimal strategies. These strategies are further refined to become novel control rules for easy practical implementation. Numerical simulation results show that both of the above strategies can effectively reduce the total energy cost, and that the integrated control works better than selected traditional control strategies.

关键词： Ventilation Humidity Equations Optimization Heating Humans

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Neural-net model based fault diagnosis for hydraulic servo axes

Neural-net model based fault diagnosis for hydraulic servo a...

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作者： Muenchhof, Marco Clever, Sebastian Technische Universität Darmstadt Institute of Automatic Control Laboratory for Control Systems and Process Automation 64283 Darmstadt Germany

ISBN: (纸本)9783902661463

In this paper, fault detection methods for hydraulic systems based on a parity equation approach with neural net models are presented. Hydraulic systems are used in manifold applications in industry. They are however not yet the subject of intense research in the area of fault detection and diagnosis, which can be mainly attributed to their strong nonlinear behavior, which exacerbates the physical modeling extensively. To avoid the difficulties associated with the physical modeling, a data-driven modeling approach based on the LOLIMOT neural network will be presented in this paper. Different subsystems of the hydraulic servo axis will be modeled using different sensor configurations. Experimental data from a real testbed allow to compare the model fidelity of the different resulting neural nets and can also be used to illustrate the capabilities of the parity-equation based fault detection approach, which in general allows the detection of tiny faults, such as sensor offset faults in the area of a few percent of the maximum sensor readout. © 2009 IFAC.

关键词： Fault detection

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Improved Multidisciplinary Multiobjective Collaborative Optimization Technique Based on NSGA-II Algorithm 1

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IFAC Proceedings Volumes 2010年第25期43卷 139-144页

作者： H. Li Y. Jing S. Zhang V. Ojleska T. Kolemisevska G.M. Dimirovski Key Laboratory of Integrated Automation of Process Industry Ministry of Education Northeastern University Shenyang 110004 P.R. China Northeastern University School of Information Science & Engineering Shenyang 110004 P.R. China SS Cyril and Methodius University School FEIT Institute of ASE Karpos II BB MK-1000 Skopje R. Macedonia Dogus University Computer Eng. and Control Eng. Departments TR-34722 Istanbul Turkey

The multiobjective collaborative optimization (MCO) has been widely adopted in concurrent engineering design as a good multiobjective optimization approach provided the problem of optimization results converging often to a local extremum has been taken care of. It has been demonstrated to yield useful solutions to a wide range of optimization problems under concurrent condition both technical and non-technical ones. A solution strategy for MCO that overcomes this drawback is proposed here on the grounds of genetic NSGA-II algorithm. It is an adaptive heuristic search technique that controls the distances between the individual and system's feasible region during genetic evolution. In the evolving NSGA-II based non-dominated sorting, the individual threshold of infeasibility degree is reduced gradually via genetic evolution and the individual's feasibility capacity is determined by its infeasibility degree and the threshold. It has been applied to a benchmark example of speed reducer design, and the obtained results demonstrate the proposed technique is comparably more efficient and may offer substantial advantages over the gradient-based optimization methods. Copyright © 2010 IFAC

关键词： Collaborative optimization dynamic threshold genetic algorithms multidisciplinary optimization multiobjective optimization

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