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Performance Evaluation of CFB Unit Combustion System Based on Comprehensive Economics and Entropy Weight Method

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Performance Evaluation of CFB Unit Combustion System Based o...

International Conference on Sensing, Diagnostics, Prognostics, and control (SDPC)

作者： Ce Qin Mingming Gao Hongfu Zhang The State Key Laboratory of Alternate Electric Power System with Renewable Energy Sources School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (数字)9781728101996

ISBN: (纸本)9781728102009

A performance evaluation method for the combustion system in the variable load process of circulating fluidized bed (CFB) unit based on the minimum variance control is proposed. Each operating parameter are initially weighted according to the dynamic economic index of the operating parameters, and entropy weight method is used to adjust the weights of operating parameter under different operating conditions. Then, the minimum variance index based on comprehensive economic and entropy weight method is proposed to evaluate the performance of the combustion system of CFB unit, which reduces the polarization effect generated by the single weighting performance evaluation method and improves the objective scientificality of the operating parameter weighting. Finally, a case study on the combustion system of a 300MW CFB unit reveals that the minimum variance index based on the comprehensive economy and entropy weight method can better evaluate the performance of the combustion system in the dynamic process of the unit, compared with the traditional performance evaluation method. It is of great significance to the operational safety and economy of CFB boiler units.

关键词： Combustion Time series analysis Data models Performance evaluation Entropy Indexes Boilers

Fault-tolerant Individual Pitch control using Adaptive Sliding Mode Observer

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IFAC-PapersOnLine 2018年第24期51卷 1127-1132页

作者： Liu, Yanhua Patton, Ron J. Lan, Jianglin School of Engineering and Computer Science University of Hull Cottingham Road HullHUG 7RX United Kingdom Department of Automatic Control and Systems Engineering University of Sheffield Portobello Street SheffieldS1 3JD United Kingdom

Due to the increasing size of wind turbines, the unbalanced loads caused by the uneven spatial distribution of wind speed and turbulence are becoming larger and larger. As has been proved, individual pitch control (IPC) can mitigate the blade asymmetric loads greatly in region 3. On the other hand, the pitch actuator faults can affect the pitching performance with slow dynamics, resulting in generator power instability and even deteriorating the unbalanced loads of blades. However, the effects of unbalanced blade loads deterioration caused by pitch actuator faults have not been taken into account by the traditional IPC design. In the present paper, a fault-tolerant control (FTC) strategy using adaptive sliding mode estimation is combined with a traditional IPC system based on two different control methods (Proportional-Integral and H∞ loop-shaping). It maintains the nominal pitch performance and removes the negative effects of pitch actuator faults on generator power and unbalanced blade loads perfectly. The effectiveness of the proposed strategy is verified on the 5MW NREL wind turbine system. © 2018

关键词： Adaptive control systems Actuators Deterioration Fault tolerance Sliding mode control Two term control systems Wind Wind turbines Actuator fault Adaptive sliding mode Adaptive sliding mode observer Fault tolerant control Individual pitch control Load reduction Proportional integral Sliding mode observers

Randomised benchmarking for characterizing and forecasting correlated processes

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arXiv 2023年

作者： Zhang, Xinfang Wu, Zhihao White, Gregory A.L. Xiang, Zhongcheng Hu, Shun Peng, Zhihui Liu, Yong Zheng, Dongning Fu, Xiang Huang, Anqi Poletti, Dario Modi, Kavan Wu, Junjie Deng, Mingtang Guo, Chu Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China School of Physics and Astronomy Monash University VIC3800 Australia Dahlem Center for Complex Quantum Systems Freie Universität Berlin Berlin14195 Germany Institute of Physics Chinese Academy of Sciences Beijing100190 China Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Department of Physics Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha410081 China Science Mathematics and Technology Cluster and Engineering Product Development Pillar Singapore University of Technology and Design 8 Somapah Road 487372 Singapore Centre for Quantum Technologies National University of Singapore 117543 Singapore MajuLab CNRS-UNS-NUS-NTU International Joint Research Unit UMI 3654 Singapore Quantum for NSW Sydney2000 Australia

The development of fault-tolerant quantum processors relies on the ability to control noise. A particularly insidious form of noise is temporally correlated or non-Markovian noise. By combining randomized benchmarking with supervised machine learning algorithms, we develop a method to learn the details of temporally correlated noise. In particular, we can learn the time-independent evolution operator of system plus bath and this leads to (i) the ability to characterize the degree of non-Markovianity of the dynamics and (ii) the ability to predict the dynamics of the system even beyond the times we have used to train our model. We exemplify this by implementing our method on a superconducting quantum processor. Our experimental results show a drastic change between the Markovian and non-Markovian regimes for the learning accuracies. Copyright © 2023, The Authors. All rights reserved.

关键词： Benchmarking

Robust on-line ADP-based solution of a class of hierarchical nonlinear differential game

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arXiv 2019年

作者： Satouri, Mohammad Reza Kebriaei, Hamed Razminia, Abolhassan Yazdanpanah, Mohammad Javad School of Electrical and Computer Engineering College of Engineering University of Tehran P.O. Box 4395-515 Tehran Iran Research Lab. Department of Electrical Engineering School of Engineering Persian Gulf University P.O. Box 75169 Boushehr Iran School of Electrical and Computer Engineering College of Engineering University of Tehran P.O. Box 4395-515 Tehran Iran Control & Intelligent Processing Center of Excellence

In this paper a hierarchical one-leader-multi-followers game for a class of continuous-time nonlinear systems with disturbance is investigated by a novel policy iteration reinforcement learning technique in which, the game model consists both of the zero-sum and nonzero-sum games, simultaneously. An adaptive dynamic programming (ADP) method is developed to achieve optimal control strategy under worst case of disturbance. This algorithm reduces the number of neural networks which are used for estimation for about thirty percent. Proposed algorithm uses neural networks to estimate value functions, control policies and disturbances. Convergence analysis of the estimations is investigated using Lyapunov theory and exploiting properties of the Nemytskii operator. Finally the simulation results will show effectiveness of developed ADP *** Codes 91A65, 49N70, 68T05, Copyright © 2019, The Authors. All rights reserved.

关键词： Nonlinear systems

Study on estimating quantum discord by neural network with prior knowledge

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arXiv 2019年

作者： Liu, Yong-Lei Wang, An-Min Wang, Guo-Dong Sun, Yi Zhang, Peng-Fei Department of Modern Physics University of Science and Technology of China Hefei230026 China School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing100049 China

Machine learning has achieved success in many areas because of its powerful Fitting ability, so we hope it can help us to solve some signiFicant physical quantitative problems, such as quantum correlation. In this research we will use neural networks to predict the value of quantum discord. Quantum discord is a measure of quantum correlation which is deFined as the difference between quantum mutual information and classical correlation for a bipartite system. Since the deFinition contains an optimization term, it makes analytically solving hard. For some special cases and small systems, such as two-qubit systems and some X-states, the explicit solutions have been calculated. However, for general cases, we still know very little. Therefore, we study the feasibility of estimating quantum discord by machine learning method on two-qubit systems. In order to get an interpretable and high performance model, we modify the ordinary neural network by introducing some prior knowledge which come from the analysis about quantum discord. Our results show that prior knowledge actually improve the performance of neural network. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

COSINE:a software development model integrating collective intelligence, service and ecosystem

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COSINE:a software development model integrating collective i...

IEEE World Congress on Services (SERVICES)

作者： Hongbing Wang Tianjing Hong Jian Cao Haijun Zhang Changhai Nie Bo Cheng Yangfan He Li Kuang Dunwei Gong Wuhui Chen Yuliang Shi Deyi Huang School of Computer Science and Engineering and Key Laboratory of Computer Network and Information Integration Southeast University Nanjing China Shanghai Jiaotong University Shanghai China College of Computer Science and Technology Harbin Institute of Technology Shenzhen China Nanjing University Nanjing China Wuhan University Wuhan China Research Institute of Network Technology Beijing University of Posts and Telecommunications Beijing China Software College Central South University Changsha China College of information and control engineering China University of mining and technology Xuzhou China College of data science and computer science Zhongshan University Guangzhou China Shandong University Jinan China Landry Company Shenzhen China

ISBN: (数字)9781728182032

ISBN: (纸本)9781728182049

With the development of the internet technology, a large amount of softwares have emerged to meet users' increasing needs. At the mean time, software systems have been faced with a problem that they must adapt to the dynamic network environment. It is obvious that a variety of software development models have been proposed in the past few decades. However, the majority of these methods are gradually unadaptable to new circumstances. In this paper, we proposed a new software development model integrating collective intelligence, service and ecosystem. On the one hand, we have introduced the model in detail. On the other hand, We took a practical example to demonstrate the effectiveness of the proposed model.

关键词： Adaptation models Biological system modeling Ecosystems Collective intelligence Software systems

Business models for the circular economy: Opportunities and challenges

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Business Strategy and the Environment 2019年第2期28卷 430-432页

作者： Fraccascia, Luca Giannoccaro, Ilaria Agarwal, Abhishek Hansen, Erik G. Department of Computer Control and Management Engineering “Antonio Ruberti” Sapienza University of Rome Rome Italy Department of Industrial Engineering and Business Information Systems University of Twente Enschede Netherlands Department of Mechanics Mathematics and Management Polytechnic University of Bari Bari Italy Department of Management Aberdeen Business School Robert Gordon University Aberdeen United Kingdom Institute for Integrated Quality Design (IQD) Johannes Kepler University Linz Linz Austria

Design of iterative learning control schemes for spatially interconnected systems

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Design of iterative learning control schemes for spatially i...

IEEE Annual Conference on Decision and control

作者： Robert Maniarski Kamil Klimkowicz Wojciech Paszke Eric Rogers Institute of Control and Computation Engineering University of Zielona Góra Zielona Góra Poland School of Electronics and Computer Science University of Southampton Southampton United Kingdom

ISBN: (数字)9781728113982

ISBN: (纸本)9781728113999

This paper develops novel procedures for design of iterative learning control schemes applied to spatially interconnected systems. In particular, differential linear repetitive process stability theory is used to design stabilizing and learning controllers for spatially interconnected systems composed of a finite number of linear continuous-time subsystems, where each one directly interacts with neighbouring subsystems. control law design is based on linear matrix inequality computations. Specifically, sufficient conditions for the existence of the required decentralized controllers are developed together with a design algorithm for the associated control law matrices. A simulation based case study on periodically interconnected subsystems in one spatial dimension is given to demonstrate the feasibility and effectiveness of the new design.

关键词： Symmetric matrices Stability analysis Asymptotic stability Linear matrix inequalities Interconnected systems Process control Computational modeling

A comprehensive study and comparison of core technologies for MPEG 3D point cloud compression

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arXiv 2019年

作者： Liu, Hao Yuan, Hui Liu, Qi Hou, Junhui Liu, Ju School of Information Science and Engineering Shandong University Qingdao266200 China School of Control Science and Engineering Shandong University Jinan250000 China Department of Computer Science City University of Hong Kong Hong Kong999077 Hong Kong

Point cloud based 3D visual re resentation is becoming popular due to its ability to exhibit the real world in a more comprehensive and immersive way. However, under a limited network bandwidth, it is very challenging to communicate this kind of media due to its huge data volume. Therefore, the MPEG have launched the standardization for point cloud compression (PCC), and proposed three model categories, i.e., TMC1, TMC2, and TMC3. Because the 3D geometry compression methods of TMC1 and TMC3 are similar, TMC1 and TMC3 are further merged into a new platform namely TMC13. In this paper, we first introduce some basic technologies that are usually used in 3D point cloud compression, then review the encoder architectures of these test models in detail, and finally analyze their rate distortion performance as well as complexity quantitatively for different cases (i.e., lossless geometry and lossless color, lossless geometry and lossy color, lossy geometry and lossy color) by using 16 benchmark 3D point clouds that are recommended by MPEG. Experimental results demonstrate that the coding efficiency of TMC2 is the best on average (especially for lossy geometry and lossy color compression) for dense point clouds while TMC13 achieves the optimal coding performance for sparse and noisy point clouds with lower time complexity. Copyright © 2019, The Authors. All rights reserved.

关键词： Color