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arXiv 2017年

作者： Zhang, Wenwen Wang, Kunfeng Qu, Hua Zhao, Jihong Wang, Fei-Yue School of Software Engineering Xi’an Jiaotong University Xi’an710049 China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Qingdao Academy of Intelligent Industries Qingdao266000 China School of Software Engineering Xi’an Jiaotong University Xi’an710049 China Department of Communication and Information Engineering Xi’an Jiaotong University Xi’an710049 China Research Center for Computational Experiments and Parallel Systems Technology National University of Defense Technology Changsha410073 China

As a special type of object detection, pedestrian detection in generic scenes has made a significant progress trained with large amounts of labeled training data manually. While the models trained with generic dataset work bad when they are directly used in specific scenes. With special viewpoints, flow light and backgrounds, datasets from specific scenes are much different from the datasets from generic scenes. In order to make the generic scene pedestrian detectors work well in specific scenes, the labeled data from specific scenes are needed to adapt the models to the specific scenes. While labeling the data manually spends much time and money, especially for specific scenes, each time with a new specific scene, large amounts of images must be labeled. What’s more, the labeling information is not so accurate in the pixels manually and different people make different labeling information. In this paper, we propose an ACP-based method, with augmented reality’s help, we build the virtual world of specific scenes, and make people walking in the virtual scenes where it is possible for them to appear to solve this problem of lacking labeled data and the results show that data from virtual world is helpful to adapt generic pedestrian detectors to specific scenes. Copyright © 2017, The Authors. All rights reserved.

关键词： Virtual reality

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Adaptive Dynamic Programming Based Fault Compensation control for Nonlinear systems with Actuator Failures

Adaptive Dynamic Programming Based Fault Compensation Contro...

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International Joint Conference on Neural Networks

作者： Bo Zhao Derong Liu Yuanchun Li Guang Shi State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences School of Automation and Electrical Engineering University of Science and Technology Beijing Department of Control Science and Engineering Changchun University of Technology

ISBN: (纸本)9781509006212

This paper develops a novel fault compensation control scheme based on adaptive dynamic programming for nonlinear systems with actuator failures. The control scheme consists of a policy iteration algorithm and a fault compensation. For fault-free dynamic models, the Hamilton-Jacobi-Bellman equation is solved by policy iteration algorithm via constructing a critic neural network, and then the approximate optimal control policy can be derived directly. On the other hand, the online fault compensation is achieved without the fault detection and isolation mechanism by reconstructing the actuator failure. The closed-loop system is guaranteed to be asymptotically stable based on Lyapunov stability theorem. Two simulation examples are given to demonstrate the effectiveness of the present fault compensation control scheme.

关键词： Iterative algorithms Nonlinear systems compensator control dynamic programming Defect detection faults actuators system failures

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Distributed control of second-order nonlinear time-delayed multiagent systems with disturbance using neural networks

Distributed control of second-order nonlinear time-delayed m...

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International Joint Conference on Neural Networks

作者： Hongwen Ma Derong Liu Ding Wang The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences School of Automation and Electrical Engineering University of Science and Technology

ISBN: (纸本)9781509006212

In this paper, a class of second-order nonlinear time-delayed multiagent systems with disturbance is investigated. In order to improve the adaptivity, neural networks are used to learn the unknown dynamics. Then, by utilizing Lyapunov-Krasovskii functional, time delays can be eliminated. Moreover, a robustifying term is introduced to constrain external disturbance. With divide-and-conquer idea, the distributed controller is divided into five different parts to make the multiagent systems reach consensus. To circumvent the singularity induced by the time-delay elimination part, a σ-function is developed. Finally, the simulation results demonstrate the validity of the distributed controller.

关键词： Multi-agent systems decentralised control disturbance Neural network Simulation results external disturbance Singularity disturbances nonlinearity

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Global, regional, and national sex-specific burden and control of the HIV epidemic, 1990–2019, for 204 countries and territories: the Global Burden of Diseases Study 2019

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The Lancet HIV 2021年第10期8卷 e633-e651页

作者： Jahagirdar, Deepa Walters, Magdalene K. Novotney, Amanda Brewer, Edmond D. Frank, Tahvi D. Carter, Austin Biehl, Molly H. Abbastabar, Hedayat Abhilash, E.S. Abu-Gharbieh, Eman Abu-Raddad, Laith Jamal Adekanmbi, Victor Adeyinka, Daniel Adedayo Adnani, Qorinah Estiningtyas Sakilah Afzal, Saira Aghababaei, Soodabeh Ahinkorah, Bright Opoku Ahmad, Sajjad Ahmadi, Keivan Ahmadi, Sepideh Ahmadpour, Ehsan Ahmed, Muktar Beshir Rashid, Tarik Ahmed Salih, Yusra Ahmed Aklilu, Addis Akram, Tayyaba Akunna, Chisom Joyqueenet Al Hamad, Hanadi Alahdab, Fares Alanezi, Fahad Mashhour Aleksandrova, Ekaterina A. Alene, Kefyalew Addis Ali, Liaqat Alipour, Vahid Almustanyir, Sami Alvis-Guzman, Nelson Ameyaw, Edward Kwabena Amu, Hubert Andrei, Catalina Liliana Andrei, Tudorel Anvari, Davood Arabloo, Jalal Aremu, Olatunde Arulappan, Judie Atnafu, Desta Debalkie Quintanilla, Beatriz Paulina Ayala Ayza, Muluken Altaye Azari, Samad Darshan, B.B. Banach, Maciej Bärnighausen, Till Winfried Barra, Fabio Barrow, Amadou Basu, Sanjay Bazargan-Hejazi, Shahrzad Belay, Habtamu Gebrehana Berheto, Tezera Moshago Bezabhe, Woldesellassie Mequanint Bezabih, Yihienew Mequanint Bhagavathula, Akshaya Srikanth Bhardwaj, Nikha Bhardwaj, Pankaj Bhattacharyya, Krittika Bibi, Sadia Bijani, Ali Bisignano, Catherine Bolarinwa, Obasanjo Afolabi Boloor, Archith Boltaev, Azizbek A. Briko, Nikolay Ivanovich Buonsenso, Danilo Burkart, Katrin Butt, Zahid A. Cao, Chao Charan, Jaykaran Chatterjee, Souranshu Chattu, Soosanna Kumary Chattu, Vijay Kumar Choudhari, Sonali Gajanan Chu, Dinh-Toi Couto, Rosa A.S. Cowden, Richard G. Dachew, Berihun Assefa Dadras, Omid Dagnew, Amare Belachew Dahlawi, Saad M.A. Dai, Xiaochen Dandona, Lalit Dandona, Rakhi das Neves, José Degenhardt, Louisa Demeke, Feleke Mekonnen Desta, Abebaw Alemayehu Deuba, Keshab Dhamnetiya, Deepak Dhungana, Govinda Prasad Dianatinasab, Mostafa Diaz, Daniel Djalalinia, Shirin Doan, Linh Phuong Dorostkar, Fariba Edinur, Hisham Atan Effiong, Andem Eftekharzadeh, Sahar El Sayed Zaki, Maysaa Elayedath, Rajesh Elhadi, Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Division of Allergy and Infectious Diseases University of Washington Seattle WA United States Department of Global Health University of Washington Seattle WA United States School of Social Work University of Washington Seattle WA United States Department of Medicine University of Washington Seattle WA United States Vagelos College of Physicians and Surgeones Columbia University Medical Center New York NY United States Division of Data Analytics and Delivery for Impact WHO Geneva Switzerland Advanced Diagnostic and Interventional Radiology Research Centre Tehran University of Medical Sciences Tehran Iran Multiple Sclerosis Research Centre Tehran University of Medical Sciences Tehran Iran School of Public Health Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Paediatric Chronic Kidney Disease Research Centre Tehran University of Medical Sciences Tehran Iran Department of Psychiatry Tehran University of Medical Sciences Tehran Iran Metabolomics and Genomics Research Centre Tehran University of Medical Sciences Tehran Iran Sina Trauma and Surgery Research Centre Tehran University of Medical Sciences Tehran Iran Research Centre for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Non-Communicable Diseases Research Centre Tehran University of Medical Sciences Tehran Iran Department of Botany Sree Narayana Guru College Chelannur Kozhikode India Clinical Sciences Department University of Sharjah Sharjah United Arab Emirates Mass Communication Department University of Sharjah Sharjah United Arab Emirates Department of Health-Care Policy and Research Weill Cornell Medical College in Qatar Doha Qatar Department of Population Medicine Ca

Background: The sustainable development goals (SDGs) aim to end HIV/AIDS as a public health threat by 2030. Understanding the current state of the HIV epidemic and its change over time is essential to this effort. This study assesses the current sex-specific HIV burden in 204 countries and territories and measures progress in the control of the epidemic. Methods: To estimate age-specific and sex-specific trends in 48 of 204 countries, we extended the Estimation and Projection Package Age-Sex Model to also implement the spectrum paediatric model. We used this model in cases where age and sex specific HIV-seroprevalence surveys and antenatal care-clinic sentinel surveillance data were available. For the remaining 156 of 204 locations, we developed a cohort-incidence bias adjustment to derive incidence as a function of cause-of-death data from vital registration systems. The incidence was input to a custom Spectrum model. To assess progress, we measured the percentage change in incident cases and deaths between 2010 and 2019 (threshold >75% decline), the ratio of incident cases to number of people living with HIV (incidence-to-prevalence ratio threshold <0·03), and the ratio of incident cases to deaths (incidence-to-mortality ratio threshold <1·0). Findings: In 2019, there were 36·8 million (95% uncertainty interval [UI] 35·1–38·9) people living with HIV worldwide. There were 0·84 males (95% UI 0·78–0·91) per female living with HIV in 2019, 0·99 male infections (0·91–1·10) for every female infection, and 1·02 male deaths (0·95–1·10) per female death. Global progress in incident cases and deaths between 2010 and 2019 was driven by sub-Saharan Africa (with a 28·52% decrease in incident cases, 95% UI 19·58–35·43, and a 39·66% decrease in deaths, 36·49–42·36). Elsewhere, the incidence remained stable or increased, whereas deaths generally decreased. In 2019, the global incidence-to-prevalence ratio was 0·05 (95% UI 0·05–0·06) and the global incidence-to-mortality ratio was

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Comparison of different optimization methods with support vector machine for blast furnace multi-fault classification 9

Comparison of different optimization methods with support ve...

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9th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes, SAFEPROCESS 2015

作者： An, Ruqiao Yang, Chunjie Zhou, Zhe Wang, Lin Pan, Yijun State Key Laboratory of Industrial Control Technology Institute of Industrial Process Control Zhejiang University Hangzhou Zhejiang310027 China

Aiming at the complex and volatile conditions of the blast furnace, a support vector machine with multi-fault classification is proposed to solve the problem on blast furnace fault diagnosis. The normal or failure data is handled with a normalization and dimensionality reduction of principal component analysis (PCA). As a small amount of failure sample, a C-support vector classification (C-SVC) is applied in this filed. Different optimization methods have been performed for optimizing SVM parameters, including the grid-search method (GSM), the genetic algorithm (GA) and the particle swarm optimization (PSO). It compares these optimization algorithm strengths and limitations for multi-fault classification on classification ability and classification speed. © 2015, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Failure analysis

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Impact of grid side converter of DFIG on sub-synchronous oscillation and its damping control

Impact of grid side converter of DFIG on sub-synchronous osc...

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IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)

作者： Haiyan Tang Wei He Yongning Chi Xinshou Tian Yan Li Yukun Wang State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China Electric Power Research Institute Beijing China State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781509054190

Along with the increasing of wind power penetration, the sub-synchronous oscillation phenomena may happen in wind power integrated system. This paper studies the sub-synchronous oscillation phenomena of doubly-fed induction generator (DFIG) based wind farm with series compensation, focuses on the dynamic characteristics of grid side converter control of DFIG and its optimal control. First, this paper analyzes the transfer characteristic of rotor-side and stator-side active power of DFIG, then combining with the analysis of DC capacitor voltage dynamic characteristics, the impacts of control strategy of grid side converter and its parameters on sub-synchronous oscillation behavior are studied. On this basis, a novel additional control strategy to suppress oscillation is proposed in grid side converter. The conclusions are verified by simulation cases of system integrated with DFIG based wind farm by series compensation.

关键词： Oscillators Voltage control Damping Stators Wind farms Rotors Wind power generation

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Data-Based Self-Learning Optimal control for Continuous-Time Unknown Nonlinear systems With Disturbance

Data-Based Self-Learning Optimal Control for Continuous-Time...

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第28届中国控制与决策会议

作者： Qinglai Wei Derong Liu Ruizhuo Song Pengfei Yan The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences School of Automation and Electrical Engineering University of Science and Technology Beijing

ISBN: (纸本)9781467397155

In this paper,a new data-based self-learning control scheme is developed to solve infinite horizon optimal control problems for continuous-time nonlinear *** developed optimal control scheme can be implement without knowing the mathematical model of the *** to the input-output data of the nonlinear systems,a recurrent neural network(RNN) is employed to reconstruct the dynamics of the nonlinear *** to the RNN model of the system,a new two-person zero-sum adaptive dynamic programming(ADP) algorithm is developed to obtain the optimal control,where the reconstruction error and the system disturbance are considered the control input of the ***-layer neural networks are used to construct the critic and action networks,which are presented to approximate the performance index function and the control law,***,simulation results will show the effectiveness of the developed data-based ADP methods.

关键词： Adaptive critic designs Adaptive dynamic programming Approximate dynamic programming Neurodynamic programming Recurrent neural network Data-based control Optimal control

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Generalized Policy Iteration Adaptive Dynamic Programming Algorithm for Optimal Tracking control of a Class of Nonlinear systems

Generalized Policy Iteration Adaptive Dynamic Programming Al...

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第28届中国控制与决策会议

作者： Qiao Lin Qinglai Wei Derong Liu The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences School of Automation and Electrical Engineering University of Science and Technology Beijing

ISBN: (纸本)9781467397155

This paper deals with optimal tracking control problems for a class of discrete-time nonlinear systems using a generalized policy iteration adaptive dynamic programming(ADP) ***,by system transformation,the optimal tracking control problem is transformed into an optimal regulation *** the generalized policy iteration ADP algorithm is employed to obtain the optimal tracking controller with convergence and optimality *** developed algorithm uses the idea of two iteration procedures to obtain the iterative tracking control laws and the iterative value *** neural networks,including model network,critic network and action network,are used to implement the developed *** last,an simulation example is given to demonstrate the effectiveness of the developed method.

关键词： adaptive dynamic programming affine nonlinear systems discrete-time generalized policy iteration neural network tracking control

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An Adaptive Dynamic Programming Based Method for Optimization of Electricity Consumption in Office Buildings

An Adaptive Dynamic Programming Based Method for Optimizatio...

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International Joint Conference on Neural Networks

作者： Guang Shi Qinglai Wei Derong Liu The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences School of Automation and Electrical Engineering University of Science and Technology Beijing

ISBN: (纸本)9781509006212

In this paper, an adaptive dynamic programming (ADP) based method is developed to optimize electricity consumption of rooms in office buildings through optimal battery management. Rooms in office buildings are generally divided into office room, computer room, storage room, meeting room, etc., each of which has different characteristics of electricity consumption, as divided into electricity consumption from sockets, lights and air-conditioners in this paper. The developed method based on ADP is elaborated, and different optimization strategies of electricity consumption in different categories of rooms are proposed in accordance with the developed method. Finally, a detailed case study on an office building is given to show the practical effect of the developed method.

关键词： electricity consumption office buildings Rooms office Air conditioners built structure Buildings Automatic data processing Adenosine Diphosphate dynamic programming

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Optimal Self-Learning control Scheme for Discrete-Time Nonlinear systems Using Local Value Iteration

Optimal Self-Learning Control Scheme for Discrete-Time Nonli...

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International Joint Conference on Neural Networks

作者： Qinglai Wei Derong Liu The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences School of Automation and Electrical Engineering University of Science and Technology Beijing

ISBN: (纸本)9781509006212

In this paper, an optimal self-learning control scheme for discrete-time nonlinear systems is developed using a new local value iteration based adaptive dynamic programming (ADP) algorithm. The developed local value iteration algorithm permits an arbitrary positive semi-definite function to initialize the algorithm. In the developed local value iteration algorithm, the iterative value function and iterative control law are updated by a subset of the state space. A new analysis method of the convergence property is presented to show that the iterative value functions will converge to the optimum. The convergence criterion for the local value iteration algorithm is presented. A simulation example is given to demonstrate the validity of the present optimal control scheme.

关键词： state-space methods convergence discrete time systems dynamic programming iterative methods learning systems nonlinear systems optimal control

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