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Control of Three-Phase Voltage Source Converters with the Derivative-Free Nonlinear Kalman Filter

Intelligent Industrial Systems 2016年第1期2卷 21-33页

作者： G. Rigatos P. Siano N. Zervos C. Cecati Unit of Industrial Automation Industrial Systems Institute Patras Greece Dept. of Industrial Eng. University of Salerno Fisciano Italy Department of Information Engineering Computer Science and Mathematics University of L’ Aquila Via Vetoio L’Aquila Italy

The paper is concerned with proving differential flatness of the three-phase voltage source converter (VSC) model and its resulting description in the Brunovsky (canonical) form. For the linearized canonical model of the converter a feedback controller is designed. At a second stage, a novel Kalman Filtering method (Derivative-free nonlinear Kalman Filtering) is introduced. The proposed Kalman Filter is redesigned as disturbance observer for estimating additive input disturbances to the VSC model. These estimated disturbance terms are finally used by a feedback controller that enables the DC output voltage track desirable setpoints. The efficiency of the proposed state estimation-based control scheme is tested through simulation experiments.

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A Novel Approach to Generating an Interval Type-2 Fuzzy Neural Network Based on a Well-Behaving Type-1 Fuzzy TSK System

A Novel Approach to Generating an Interval Type-2 Fuzzy Neur...

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IEEE International Conference on Systems, Man, and Cybernetics

作者： Junlong Gao Ruyi Yuan Jianqiang Yi Hao Ying Chengdong Li Institute of Automation Chinese Academy of Sciences Beijing 10090 China Dept. of Electrical & Computer Engineering Wayne State University Detroit 48202 USA School of Information & Electrical Engineering Shandong Jianzhu University Jinan 250101 China

ISBN: (纸本)9781509018987

This paper presents a novel approach to automatically creating an interval type-2 fuzzy neural network (IT2-FNN) from a type-1 fuzzy TSK system (Tl-TSK). The IT2-FNN is constructed in such a way that it takes advantage of the well-behaving Tl-TSK. Our approach makes designing the IT2-FNN more efficient and the resulting system is expected to perform better than the Tl-TSK due to the footprint of uncertainty of the IT2 fuzzy sets, especially when the system is subject to heavy external or internal uncertainties. There are two automated procedures in the IT2-FNN formation: (1) antecedent structure construction, and (2) learning of the parameters in both the antecedent and consequent. The structure construction is based on antecedent structure of the Tl-TSK and consists of three steps - IT2 fuzzy set creation, similarity categorization, and mergence. The IT2 fuzzy sets are directly initialized from the fuzzy sets of the Tl-TSK. Then, the IT2 fuzzy sets are classified into different groups based on their similarities. Finally, the IT2 fuzzy sets in each group are merged to create a representative IT2 fuzzy set for each group. The parameter learning procedure uses a hybrid learning algorithm to attain the optimal values for all the parameters. The learning algorithm adopts a new adaptive steepest descent algorithm and a linear least-squares method to adjust the antecedent parameters and consequent parameters, respectively. One benchmark modelling problem is utilized to compare our approach with the Tl-TSK systems in the literature under various scenarios. The comparison results show our IT2-FNN performs better than the Tl-TSK systems, especially when there are strong uncertainties. In summary, the IT2-FNN can not only achieve better performance but its structure is simpler than that of the similar type-2 fuzzy neural networks in the literature.

关键词： adaptive steepest decent algorithm fuzzy logic system type transition fuzzy set mergence interval type-2 fuzzy neural network

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A comparison of voltage balancing versus energy balancing approach for modular multilevel converters

A comparison of voltage balancing versus energy balancing ap...

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Annual Conference of Industrial Electronics Society

作者： Apparao Dekka Bin Wu Ricardo Lizana Navid R. Zargari Dept. of Electrical and Computer Engineering Ryerson University Toronto ON Canada Faculty of Engineering Universidad Catolica de la Santisima Concepcion Concepcion Chile Medium-Voltage Drive R&D Rockwell Automation Cambridge ON Canada

The multilevel submodules (SMs) bring the added advantages of compact size and improved efficiency over standard submodules to the modular multilevel converter (MMC). These SMs have more than one floating capacitor, which stores the arm energy. Each arm of MMC has several SMs connected in series to meet the required operating voltage. The SM capacitors voltage or energy must be controlled to ensure the safe and reliable operation of MMC. This objective can be achieved by using either voltage balancing or energy balancing approaches. When all the SMs have equal capacitance value, then the voltage and energy balancing approaches have identical performance. However, the SM capacitance deteriorates over a long run, which affects the performance of MMC. This paper presents the performance comparison of voltage and energy balancing approaches for MMC with equal and unequal SM capacitance. The performance of balancing approaches is evaluated in terms of active and reactive power loading of individual SMs, rating of IGBT devices and SM capacitors, and output voltage and current harmonic distortion.

关键词： Capacitors Reactive power Voltage measurement Capacitance Voltage control Indexes Performance evaluation

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Timing-driven placement based on dynamic net-weighting for efficient slack histogram compression 15

Timing-driven placement based on dynamic net-weighting for e...

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18th ACM International Symposium on Physical Design, ISPD 2015

作者： Guth, Chrystian Livramento, Vinicius Netto, Renan Fonseca, Renan Güntzel, José Luís Santos, Luiz Dept. of Computer Science Federal University of Santa Catarina Brazil Dept. of Automation and Systems Engineering Federal University of Santa Catarina Brazil

ISBN: (纸本)9781450333993

Timing-driven placement (TDP) finds new legal locations for standard cells so as to minimize timing violations while preserving placement quality. Although violations may arise from unmet setup or hold constraints, most TDP approaches ignore the latter. Besides, most techniques focus on reducing the worst negative slack and let the improvements on total negative slack as a secondary goal. However, to successfully achieve timing closure, techniques must also reduce the total negative slack, which is known as slack histogram compression. This paper proposes a new Lagrangian Relaxation formulation for TDP to compress both late and early slack histograms. To solve the problem, we employ a discrete local search technique that uses the Lagrange multipliers as net-weights, which are dynamically updated using an accurate timing analyzer. To preserve placement quality, our technique uses a small fixed-size window that is anchored in the initial location of a cell. For the experimental evaluation of the proposed technique, we relied on the ICCAD 2014 TDP contest infrastructure. The results show that our technique significantly reduces the timing violations from an initial global placement. On average, late and early total negative slacks are improved by 85.03% and 42.72%, respectively, while the worst slacks are reduced by 71.55% and 34.40%. The overhead in wirelength is less than 0.1%.

关键词： Lagrange multipliers

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Online tuning method for notch filter dept. in industrial servo systems

Online tuning method for notch filter depth in industrial se...

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Chinese Control Conference (CCC)

作者： Tae-Il Kim Wook Bahn Jong-Min Yoon Ji-Seok Han Ji-Ho Park Sang-Sub Lee Sang-Hoon Lee Dong-Il Cho Dept. of Electrical and Computer Engineering Seoul National University Seoul Korea RS Automation Co. Ltd. Gyeonggi-do Korea Seoul National University Gwanak-gu Seoul KR

This paper presents an online tuning method for notch filter dept.s in industrial servo systems. Notch filters are commonly utilized to suppress resonances in servo systems. Using a damping ratio of notch-filter zeros is especially important when the resonance has a damped behavior. This paper develops an online tuning method to adjust the damping ratio of notch-filter zeros, by adjusting the dept. parameter of a bi-quad notch filter. The developed tuning method uses the electrical current command of a servo system as an input to detect a resonance. When a resonance occurs, the tuning method increases the dept. parameter to decrease the damping ratio of notch-filter zeros, and then the tuning method checks whether the resonance is suppressed. If the resonance is not suppressed and the dept. parameter has not reached the upper limit, the tuning method repeats the process of increasing the dept. parameter. After several iterations, an appropriate dept. parameter is selected and the resonance can be suppressed. Experiments are performed using two servo systems which are coupled with a ball-screw-drive load and a belt-drive load, respectively. The resonance of the belt-drive load has a behavior that is more highly damped behavior than that of the ball-screw-drive load. Experimental results show that the resonances of both systems are successfully suppressed using the developed tuning method.

关键词： Servomotors Tuning Notch filters Damping Resonant frequency Oscillators Frequency estimation

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An Efficient Classification Method for Knee MR Image Segmentation

An Efficient Classification Method for Knee MR Image Segment...

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International IEEE Conference on Signal-Image Technologies and Internet-Based System

作者： Yukiko Yamamoto Setsuo Tsuruta Syoji Kobashi Yoshitaka Sakurai Rainer Knauf School of Information Environment Tokyo Denki University Inzai Japan Department of Computer Engineering Hyogo University Himeji Japan School of Interdisciplinary Mathematical Sciences Meiji University Nakano Japan Dept. of Computer Science and Automation Technische Universität Ilmenau Ilmenau Germany

Aiming at application to automated recognition of knee bone magnetic resonance (MR) images, an evolutional classification method called CBGA-LDIC is proposed. CBGA-LDIC finds an appropriate cell set towards efficient image segmentation. This method uses location-dependent image classification (LDIC), which is integrated by genetic algorithm (GA) combined with case based reasoning (CB). LDIC introduces a new but local heuristics for image segmentation, and defines multiple classifiers dependent on location. Each classifier is trained by Gaussian mixture model. CBGA-LDIC decomposes the whole image into some cells, makes a set of cells, and then trains classifiers. Since the knee bones and/or their formations are similar in their location, good combinations of cells seem useful for other clients and are stored in case bases. Thus this method is expected to produce the better results when good combinations of cells are selected from cases as initial individuals of GA, especially through its repetition on restarting GA. This is verified by some experimentations shown in this paper.

关键词： Genetic algorithms Bones Image segmentation Statistics Sociology Training Image classification

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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge

arXiv

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arXiv 2018年

作者： Bakas, Spyridon Reyes, Mauricio Jakab, Andras Bauer, Stefan Rempfler, Markus Crimi, Alessandro Shinohara, Russell Takeshi Berger, Christoph Ha, Sung Min Rozycki, Martin Prastawa, Marcel Alberts, Esther Lipkova, Jana Freymann, John Kirby, Justin Bilello, Michel Fathallah-Shaykh, Hassan M. Wiest, Roland Kirschke, Jan Wiestler, Benedikt Colen, Rivka Kotrotsou, Aikaterini Lamontagne, Pamela Marcus, Daniel Milchenko, Mikhail Nazeri, Arash Weber, Marc-Andr Mahajan, Abhishek Baid, Ujjwal Gerstner, Elizabeth Kwon, Dongjin Acharya, Gagan Agarwal, Manu Alam, Mahbubul Albiol, Alberto Albiol, Antonio Albiol, Francisco J. Alex, Varghese Allinson, Nigel Amorim, Pedro H.A. Amrutkar, Abhijit Anand, Ganesh Andermatt, Simon Arbel, Tal Arbelaez, Pablo Avery, Aaron Azmat, Muneeza Pranjal, B. Bai, Wenjia Banerjee, Subhashis Barth, Bill Batchelder, Thomas Batmanghelich, Kayhan Battistella, Enzo Beers, Andrew Belyaev, Mikhail Bendszus, Martin Benson, Eze Bernal, Jose Bharath, Halandur Nagaraja Biros, George Bisdas, Sotirios Brown, James Cabezas, Mariano Cao, Shilei Cardoso, Jorge M. Carver, Eric N. Casamitjana, Adri Castillo, Laura Silvana Cat, Marcel Cattin, Philippe Cérigues, Albert Chagas, Vinicius S. Chandra, Siddhartha Chang, Yi-Ju Chang, Shiyu Chang, Ken Chazalon, Joseph Chen, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Cheng, Kun Choudhury, Ahana Roy Chylla, Roger Clrigues, Albert Colleman, Steven Colmeiro, Ramiro German Rodriguez Combalia, Marc Costa, Anthony Cui, Xiaomeng Dai, Zhenzhen Dai, Lutao Daza, Laura Alexandra Deutsch, Eric Ding, Changxing Dong, Chao Dong, Shidu Dudzik, Wojciech Eaton-Rosen, Zach Egan, Gary Escudero, Guilherme Estienne, Tho Everson, Richard Fabrizio, Jonathan Fan, Yong Fang, Longwei Feng, Xue Ferrante, Enzo Fidon, Lucas Fischer, Martin French, Andrew P. Fridman, Naomi Fu, Huan Fuentes, David Gao, Yaozong Gates, Evan Gering, David Gholami, Amir Gierke, Willi Glocker, Ben Gong, Mingming Gonzlez-Vill, Sandra Grosges, T. Guan, Yuanfang Guo, Sheng Gupta, Sudeep Han, Woo-Sup Han, Il Song Harmuth, Ko Center for Biomedical Image Computing and Analytics University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Institute for Surgical Technology and Biomechanics University of Bern Bern Switzerland Center for MR-Research University Children's Hospital Zurich Zurich Switzerland Support Centre for Advanced Neuroimaging Inselspital Institute for Diagnostic and Interventional Neuroradiology Bern University Hospital Bern Switzerland University Hospital of Zurich Zurich Switzerland Center for Clinical Epidemiology and Biostatistics University of Pennsylvania Philadelphia United States Image-Based Biomedical Modeling Group Technical University of Munich Munich Germany Icahn School of Medicine Mount Sinai Health System New YorkNY United States Leidos Biomedical Research Inc. Frederick National Laboratory for Cancer Research FrederickMD21701 United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD20814 United States Department of Neurology University of Alabama at Birmingham BirminghamAL United States Department of Diagnostic Radiology University of Texas MD Anderson Cancer Center HoustonTX United States Department of Psychology Washington University St. LouisMO United States Neuroimaging Informatics and Analysis Center Washington University St. LouisMO United States Department of Radiology Washington University St. LouisMO United States Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology University Medical Center Rostock Ernst-Heydemann-Str. 6 Rostock18057 Germany Tata Memorial Centre Homi Bhabha National Institute Mumbai India Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India NVIDIA Santa Clara

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Tumors

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Local energy micro-storage systems in smart communities with active, reactive and harmonic control

Local energy micro-storage systems in smart communities with...

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International Conference on Environment and Electrical engineering (EEEIC)

作者： María-Isabel Milanés-Montero Eva González- Romera Fermín Barrero-González Enrique Romero-Cadaval Antonio Moreno-Munoz Universidad de Extremadura Caceres Extremadura ES Electrical Electronic and Automation Engineering Dept. University of Extremadura Badajoz Spain Computer Architecture Electronics and Electronic Technology Department Universidad de Córdoba Córdoba Spain

ISBN: (纸本)9781509023219

This paper aims to provide control strategies for distributed micro-storage energy systems at the residential level to contribute to smart grid goals. The operation of local Energy Storage Systems (ESS) at homes in a Smart Community with distributed generation based of renewable energies is analyzed by simulation. Each individual home receive the active and reactive power set-points from the Smart Community Energy Management System (SCEMS), acting as an aggregator of resources in the community according to the expected demand and production. Besides, in case the ESS has got available capacity, once the SCEMS requirements are satisfied, it is used to inject the harmonic current components demanded by the household circuitry. It allows a local improvement in the power quality of the demanded current, and so contributes to the global power quality consumption of the community. Simulation results showing the operation of the local ESS are presented to validate the proposed control strategies.

关键词： Harmonic analysis Reactive power Simulation Power quality Batteries Power system harmonics

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Dual-Stage Model Predictive Control of Modular Multilevel Converter

Dual-Stage Model Predictive Control of Modular Multilevel Co...

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International Conference on Industrial Technology

作者： Apparao Dekka Bin Wu Venkata Yaramsu Navid R. Zargari Dept. of Electrical and Computer Engineering Ryerson University Toronto ON M5B 2K3 Canada Dept. of Electrical Engg and Computer Science Northern Arizona University Flagstaff AZ USA Medium-Voltage Drive R&D Rockwell Automation Cambridge ON N1R 5X1 Canada

ISBN: (纸本)9781467380768

The control of modular multilevel converter (MMC) is quite challenging and demands a flexible approach to achieve multiple control objectives. The model predictive control (MPC) is highly effective and suitable to control the MMC. The control objectives are included in a single cost function and evaluated for all possible switching states. The switching state which minimizes cost function is selected and applied to converter. In MMC, the number of available switching states are quite high and drastically increase with number of submodules per arm. Therefore, the implementation of conventional MPC is difficult and contributes to unwanted switching of submodules. This paper proposes a less computational, dual-stage MPC with common-mode voltage injection for MMC. In this approach, the overall MMC control objectives are categorized into primary and secondary group. The primary group objectives are evaluated in first-stage and secondary group of control objectives are evaluated in second-stage of MPC. By doing so, the computational complexity can be significantly minimized without affecting the dynamic response of MPC. The proposed approach avoids unwanted switching of submodules and, minimizes the output voltage harmonic distortion and ripple in output current. The simulation study is conducted to verify the effectiveness of proposed approach and corresponding results are compared with standard MPC.

关键词： MMC MPC output voltage harmonic distortion

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Diagnosis of wind turbine rotor system

Diagnosis of wind turbine rotor system

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American Control Conference

作者： Henrik Niemann Mahmood Mirzaei Lars Christian Henriksen Niels Kjolstad Poulsen Dept. of Electrical Engineering Automation and Control Build. 326 Technical University of Denmark DK-2800 Kgs. Lyngby Denmark Dept. of wind energy Technical University of Denmark DK-2800 Kgs. Lyngby Denmark AF Consult Lyskaer 3F 2730 Herlev Denmark Dept. of Applied Mathematics and Computer Science Technical University of Denmark DK-2800 Kgs. Lyngby Denmark

ISBN: (纸本)9781467386838

This paper describes a model free method for monitoring and fault diagnosis of the elements in a rotor system for a wind turbine. The diagnosis as well as the monitoring is done without using any model of the wind turbine and the applied controller or a description of the wind profile. The method is based on available standard sensors on wind turbines. The method can be used both on-line as well as off-line. Faults or changes in the rotor system will result in asymmetries, which can be monitored and diagnosed. This can be done by using the multi-blade coordinate transformation. Changes in the rotor system that can be diagnosed and monitored are: actuator faults, sensor faults and internal blade changes as e.g. change in mass of a blade.

关键词： Wind turbines Monitoring Sensors Rotors Fault diagnosis Blades Aerodynamics

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