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Design of Process control system in Water Cooling Processing Interaction Tank using Integral control and Robust control in The Tire Industry

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IOP Conference Series: Materials Science and Engineering 2018年第1期384卷

作者： D Handaya P Bakti Y P Nugraha Electronic Engineering Politeknik Gajah Tunggal Jl. Gatot Subroto KM. 7 Tangerang 15135 Indonesia Research Center for Quality System and Testing Technology Indonesian Institute of Science Gedung 417 Jl. Kawasan Puspitek Muncul Setu Tangerang Selatan 15314 Indonesia Control System and Computer Laboratory School of Electrical Engineering and Informatics Bandung Institute of Technology Jl. Ganesha no. 10 Bandung 40132 Indonesia

This laboratory based research build a process control system as water level scanner in interaction tank used for water cooling. The control valve parameter based on water level between tanks are interacted. The control method of tank valve ratio choosed in this reasearch is integral control and robust control. The desired control specification for maximum overshoot is 10%, peak time is 1 second, and error steady state is 0. The design process executed in physic system modelling step and system design criteria. Experiment executed using Matlab Script and Matlab Simulink. The simulation result will be compared to see an effective performance for processing of water cooling interaction tank control method. The design result for integral control can tracking reference accord to system design criteria and robust control can tracking reference without different experience either the system without disturbance or the system with disturbance.

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Design of Rated Power control Strategy of Wind Turbine Based on Particle Swarm Optimization

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IOP Conference Series: Earth and Environmental Science 2018年第1期192卷

作者： YC Yang Y Liu P Song Y Cui Y Bai Department of Control and Computer Engineering North China Electric Power University Beijing 102206 China North China Electric Power Research Institute Co. Ltd. Smart Grid and New Energy Institute Beijing 100045 China Grid-connected Operation Technology for Wind-Solar-Storage Hybrid System State Grid Corporation Key Laboratory

In view of the reduction of wind turbine operating efficiency caused by wind speed measurement errors, this paper proposes a rated power control strategy for wind turbines for practical applications; in order to solve the problem that the pitch PI controller parameters of wind turbines are not easy to calculate and tune in the process of design and optimization, this paper proposes a complete set of methods for parameter tuning of pitch control PI controllers for wind turbines. This paper establishes a Bladed-Matlab co-simulation platform, uses Bladed software to build a complete model of a 2MW wind turbine, and designs a rated power control strategy for wind turbines. After the wind turbine model is linearized at different wind speed points by applying Bladed software, the linearized model for PI parameter tuning is obtained, and then the optimal PI parameters for each wind speed point are set by using particle swarm algorithm. According to the variation law between the PI parameters and the pitch angle obtained before, the PI parameters are adjusted adaptively by variable gain PI control. The simulation results show the superiority of the control strategy and parameter tuning method used in this paper.

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METU-MMDS: An intelligent multimedia database system for multimodal content extraction and querying 22nd

METU-MMDS: An intelligent multimedia database system for mul...

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22nd International Conference on MultiMedia Modeling, MMM 2016

作者： Yazici, Adnan Sattari, Saeid Yilmaz, Turgay Sert, Mustafa Koyuncu, Murat Gulen, Elvan Multimedia Database Laboratory Department of Computer Engineering METU Ankara Turkey Command Control and Combat Systems HAVELSAN Inc Ankara Turkey Department of Computer Engineering Baskent University Ankara Turkey Department of Information System Engineering Atilim University Ankara Turkey C + E Management Microsoft Corporation RedmondWA United States

ISBN: (纸本)9783319276731

Managing a large volume of multimedia data, which contain various modalities (visual, audio, and text), reveals the need for a specialized multimedia database system (MMDS) to efficiently model, process, store and retrieve video shots based on their semantic content. This demo introduces METU-MMDS, an intelligent MMDS which employs both machine learning and database techniques. The system extracts semantic content automatically by using visual, audio and textual data, stores the extracted content in an appropriate format and uses this content to efficiently retrieve video shots. The system architecture supports various multimedia query types including unimodal querying, multimodal querying, query-by-concept, query-by-example, and utilizes a multimedia index structure for efficiently querying multi-dimensional multimedia data. We demonstrate METU-MMDS for semantic data extraction from videos and complex multimedia querying by considering content and concept-based queries containing all modalities. © Springer International Publishing Switzerland 2016.

关键词： Semantics

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Sum-Mse performance gain of DFT-based channel estimator over frequency-domain ls one in full-duplex OFDM systems with colored interference

arXiv

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arXiv 2017年

作者： Wang, Jin Shu, Feng Lu, Jinhui Yu, Hai Chen, Riqing Li, Jun Jayakody, Dushantha Nalin K. School of Electronic and Optical Engineering Nanjing University of Science and Technology 210094 China College of Computer and Information Sciences Fujian Agriculture and Forestry University Fuzhou350002 China China Research Institute of Radiowave Propagation National Key Laboratory of Electromagnetic Environment Qingdao266107 China National Research Tomsk Polytechnic University Department of Control System Optimization Institute of Cybernetics Russia

In this paper, we make an investigation on the summean-square-error (sum-MSE) performance gain achieved by DFT-based least-square (LS) channel estimator over frequencydomain LS one in full-duplex OFDM system in the presence of colored interference and noise. The closed-form expression of the sum-MSE performance gain is given. Its simple upper and lower bounds are derived by using inequalities of matrix eigen-values. By simulation and analysis, the upper lower bound is shown to be close to the exact value of MSE gain as the ratio of the number N of total subcarriers to the cyclic prefix length L grows and the correlation factor of colored interference increases. More importantly, we also find that the MSE gain varies from one to N/L as the correlation among colored interferences decreases gradually. According to theoretical analysis, we also find the MSE gain has very simple forms in two extreme scenarios. In the first extreme case that the colored interferences over all subchannels are fully correlated, i.e., their covariance matrix is a matrix of allones, the sum-MSE gain reduces to 1. In other words, there is no performance gain. In the second extreme case that the coloredinterference covariance matrix is an identity matrix, i.e, they are mutually independent, the achievable sum-MSE performance gain is N/L. A large ratio N/L will achieve a significant sum-MSE gain. Copyright © 2017, The Authors. All rights reserved.

关键词： Covariance matrix

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Towards multi-functional light-weight long-term real-time coastal ocean observation system 11

Towards multi-functional light-weight long-term real-time co...

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11th ACM International Conference on Underwater Networks and systems, WUWNet 2016

作者： Jiang, Zhenfeng Ma, Yanming Chen, Jiali Wang, Zigeng Peng, Zheng Liu, Jun Han, Guitao Smart Ocean Industry Research Institute Nantong Jiangsu226000 China Computer Science and Engineering Department University of Connecticut StorrsCT06269 United States Computer Science Deparment City College of New York NY10031 United States Computer Science and Technology Department Jilin University Changchun Jilin130012 China State Key Laboratory of Robotics Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

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Bandwidth Allocation with Minimum Rate Constraints in Cluster-based Femtocell Networks

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International Journal of Automation and computing 2015年第1期12卷 77-82页

作者： Kai Ma Liang Li Jie Yang Zhi-Xin Liu Xin-Bin Li Xin-Ping Guan School of Electrical Engineering Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information ProcessingMinistry of Education

Inter-femtocell interference becomes serious when femtocells are densely deployed. To mitigate the inter-femtocell interference, this paper proposes a cluster-based bandwidth allocation algorithm. We create femtocell clusters by constructing a weighted interference graph and allocate bandwidth to each cluster based on a Nash bargaining solution(NBS). Simulation results show that the cluster-based bandwidth allocation algorithm can reduce the inter-femtocell interference and meet the minimum rate constraint of each cluster.

关键词： Femtocell cluster inter-femtocell interference bandwidth allocation Nash bargaining solution(NBS)

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Mixed pitch control of wind turbine generator system based on global exact linearization and regional pole placement

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International Journal of Machine Learning and Cybernetics 2016年第5期7卷 921-930页

作者： Zhu, Mu Liu, Jizhen Lin, Zhongwei Meng, Hongmin State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer Engineering North China Electric Power University Beijing People’s Republic of China

When the wind power electricity system working above the rated wind speed, the disturbed wind speed can lead to the output ripple easily, which causes a significant negative influence on the stability of the power grid. In order to overcome this disadvantage, this paper discusses the mixed $$H_2/H_{\infty }$$ pitch angle control design problem for the nonlinear wind turbine generator system, where the turbulence is regarded as the disturbance input. Especially, the global exact linearization and the pole placement techniques are also applied to guarantee the desired control performance and expected dynamic characteristics in the situation of a large-scale variety of the system operation points. The simulation results show the effectiveness of the proposed method.

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AUV dead-reckoning navigation based on neural network using a single accelerometer 11

AUV dead-reckoning navigation based on neural network using ...

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11th ACM International Conference on Underwater Networks and systems, WUWNet 2016

作者： Xie, Yan-Xin Liu, Jun Hu, Cheng-Quan Cui, Jun-Hong Xu, Hongli State Key Laboratory of Robotics CAS No. 114 Nanta Street Shenhe District Shenyang China College of Computer Science and Technology Jilin University Changchun China Underwater Sensor Network Lab. University of Connecticut StorrsCT06269 United States Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

ISBN: (纸本)9781450346375

The accuracy of the Autonomous Underwater Vehicles (AUVs) navigation system determines whether they can safely operate and return. Traditional Dead-reckoning (DR) relies on the inertial sensors such as gyroscope and accelerometer. A major challenge for DR navigation is from measurement error of the inertial sensors (gyroscope, accelerometer, etc.), especially when the AUV is near or at the ocean surface. The AUV's motion is affected by ocean waves, and its pitch angle changes rapidly with the waves. This rapid change and the measurement errors will cause great noise to the direction measured by gyroscopes, and then lead to a large error to the DR navigation. To address this problem, a novel DR method based on neural network (DR-N) is proposed to explore the time-varying relationship between acceleration measurement and orientation measurement, which leverages acoustic localization and neural network estimate timely pitch angle through the explored time-varying relationship. This method enables AUV's DR navigation with a single acceleration, without relying on both acceleration and gyroscope. Most importantly, we can improve the accuracy of AUV navigation through avoiding DR errors caused by gyroscope noise at the sea surface. Simulations show DR-N significantly improves navigation accuracy.

关键词： Accelerometers

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Robust guided image filtering

arXiv

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arXiv 2017年

作者： Liu, Wei Chen, Xiaogang Shen, Chunhua Yu, Jingyi Wu, Qiang Yang, Jie Key Laboratory of Ministry of Education for System Control and Information Processing Shanghai Jiao Tong University Shanghai200240 China College of Communication and Art Design University of Shanghai for Science and Technology Shanghai200093 China School of Computer Science University of Adelaide AdelaideSA5005 Australia College of Engineering University of Delaware NewarkDE19176 United States School of Computing and Communications University of Technology SydneyNSW2007 Australia

The process of using one image to guide the filtering process of another one is called Guided Image Filtering (GIF). The main challenge of GIF is the structure inconsistency between the guidance image and the target image. Besides, noise in the target image is also a challenging issue especially when it is heavy. In this paper, we propose a general framework for Robust Guided Image Filtering (RGIF), which contains a data term and a smoothness term, to solve the two issues mentioned above. The data term makes our model simultaneously denoise the target image and perform GIF which is robust against the heavy noise. The smoothness term is able to make use of the property of both the guidance image and the target image which is robust against the structure inconsistency. While the resulting model is highly non-convex, it can be solved through the proposed Iteratively Re-weighted Least Squares (IRLS) in an efficient manner. For challenging applications such as guided depth map upsampling, we further develop a data-driven parameter optimization scheme to properly determine the parameter in our model. This optimization scheme can help to preserve small structures and sharp depth edges even for a large upsampling factor (8× for example). Moreover, the specially designed structure of the data term and the smoothness term makes our model perform well in edge-preserving smoothing for single-image tasks (i.e., the guidance image is the target image itself). It performs well in several challenging applications in avoiding halos, gradient reversals and properly preserving edges with noise/texture being well smoothed. Through extensive experimental results, we show that the proposed RGIF can have promising performance in many applications such as guided depth map upsampling, flash/no flash filtering, detail enhancement, HDR tone mapping, structure smoothing and clip-art JPEG compression artifact removal. This paper is an extension of our previous work [1], [2]. Copyright © 2017, T

关键词： Image enhancement

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Short-Term Wind Power Prediction Based on Empirical Mode Decomposition and Extreme Learning Machine

Short-Term Wind Power Prediction Based on Empirical Mode Dec...

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2016 5th International Conference on Environment, Materials, Chemistry and Power Electronics(EMCPE 2016)

作者： Jiajia Wu Changliang Liu School of Control and Computer Engineering North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (NCEPU)

Wind power prediction is important for the power system with plenty of wind power. This paper studies the method combined with empirical mode decomposition and extreme learning machine for short-term wind power prediction. The empirical mode decomposition method is utilized to decompose the signal of wind power into sequences with different characteristic scale. The extreme learning machine method is used to model and predict each sequence. Eventually, the prediction results of each sequence are added to obtain the final wind-power prediction results. The simulation result shows that the proposed method in this study improves the prediction accuracy of wind power prediction.

关键词： Wind Power Power Prediction Empirical Mode Decomposition Extreme Learning Machine

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