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On PID control for synchronization of complex dynamical network with delayed nodes

Science China(Technological Sciences) 2019年第8期62卷 1412-1422页

作者： GU HaiBo Lv JinHu LIN ZongLi Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing 100049 China School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environment and Beijing Advanced Innovation Center for Big Data and Brain Machine Intelligence Beihang University Beijing 100083 China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia Charlottesville VA 22904-4743 USA

Over the past two decades, synchronization, as an interesting collective behavior of complex dynamical networks, has been attracting much attention. To reveal and analyze the inherent mechanism of synchronization in complex dynamical networks with time delays in nodes, this paper attempts to use PD and PI control protocols to achieve synchronization. Based on a classical network model, we investigate the PD and PI control for synchronization of complex dynamical networks with delayed nodes and obtain some sufficient conditions. By using Lyapunov functions and appropriate state transformations, we prove that global synchronization can be achieved via the above control protocols. Finally, some simulation examples are illustrated to validate the effectiveness of the proposed theoretical results.

关键词： synchronization PID control complex dynamical network networked control system delayed node

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A convolutional neural network-based diagnostic method using resting-state electroencephalograph signals for major depressive and bipolar disorders

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Biomedical Signal Processing and control 2022年 72卷

作者： Lei, Yu Belkacem, Abdelkader Nasreddine Wang, Xiaotian Sha, Sha Wang, Changming Chen, Chao Beijing Institute of Basic Medical Sciences Beijing China Department of Computer and Network Engineering College of Information Technology United Arab Emirates University Al Ain United Arab Emirates School of Artificial Intelligence Xidian University Xian China National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders Beijing Anding Hospital Capital Medical University Beijing China Brain-inspired Intelligence and Clinical Translational Research Center/Department of Neurosurgery Xuanwu Hospital Capitap Medical University Beijing China Key Laboratory of Complex System Control Theory and Application Tianjin University of Technology China Academy of Medical Engineering and Translational Medicine Tianjin University Tianjin China

Background: Early and accurate diagnosis of bipolar and major depressive disorders is important in clinical practice. However, no diagnostic biomarkers can discriminate bipolar from major depressive disorder with high accuracy at present. Methods: We propose a novel convolutional neural network architecture using multichannel raw resting-state electroencephalograph signals to differentiate bipolar disorder from major depressive disorder. This method has great potential in diagnosing mental disorders. In total, 101 patients with major depressive disorder, 82 patients with bipolar disorder, and 81 healthy controls were assessed. Clinical diagnosis was performed by psychiatrists based on the Diagnostic and Statistical Manual of Mental Disorders, fifth edition. Participants were instructed to fix their eyes on a cross on the monitor during the collection of resting-state electroencephalograph signals. Results: A classification mean accuracy of 96.88% was achieved using the resting-state electroencephalograph signals with the 10-fold cross-validation method. The results indicate that deep neural networks could learn efficient feature patterns automatically without manual feature selections. Both statistical analysis and feature visualization on different brain regions showed that the classification performance and the learned features of the proposed model were consistent with that obtained in neurobiological studies on bipolar and major depressive disorders. Conclusions: The combined use of deep neural networks and electroencephalograph signals is an effective approach for the computer-aided diagnosis of bipolar and major depressive disorders. © 2021 Elsevier Ltd

关键词： Deep neural networks

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A Study on Tuning Methods of Linear Active Disturbance Rejection control for a Class of Thermal Processes 7

A Study on Tuning Methods of Linear Active Disturbance Rejec...

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7th International Conference on Information Science and control engineering, ICISCE 2020

作者： Li, Bo Wang, Li Zhao, Rui Zhang, Shuang Sun, Ming Thermal Power Technology Research Institute China Datang Corporation Science and Technology Research Institute Co. Ltd Inner Mongolia Branch Huhhot China China Datang Corporation Science and Technology Research Institute Co. Ltd Thermal Power Technology Research Institute Beijing China North China Electric Power University School of Control and Computer Engineering Baoding China

ISBN: (纸本)9781728164069

Active disturbance rejection controllers have been applied in a certain range in industrial processes. Aiming at the control difficulties of a class of large inertia and large delay thermal processes in thermal power plant, this paper studies two second-order linear ADRC parameter setting methods, and discusses their control effects and applicability. Based on the known process model, one method is to transform model into the form of K/(Ts+1)-{n}, and then based on the given maximum sensitivity function, the controller parameter tuning formula is obtained through the asymptote of the Nyquist curve;the other is to transform model into the form of Ke-{-tau s}/(Ts+1), and then the controller parameters are designed with this approximate model. Taking the superheated steam temperature system of a 330MW thermal power unit as the controlled object, the simulation study was performed by LADRC. The calculation of the control efficiency index and the integration index of ITAE and ISE is carried out from the three aspects, which are set-point tracking, robust performance and noise test. The control effect and scope of application of the two empirical setting formulas are analyzed and the valuable guidance is given. © 2020 IEEE.

关键词： controllers

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Formal modelling of list based dynamic memory allocators

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Science China(Information Sciences) 2018年第12期61卷 81-96页

作者： Bin FANG Mihaela SIGHIREANU Geguang PU Wen SU Jean-Raymond ABRIAL Mengfei YANG Lei QIAO Shanghai Key Laboratory of Trustworthy Computing East China Normal University IRIF University Paris Diderot and CNRS School of Computer Engineering and Science Shanghai University Marseille Beijing Institute of Control Engineering

Existing implementations of dynamic memory allocators(DMA) employ a large spectrum of policies and techniques. The formal specifications of these techniques are quite complicated in isolation and very complex when combined. Therefore, the formal reasoning on a specific DMA implementation is difficult for automatic tools and mostly single-use. This paper proposes a solution to this problem by providing formal models for a full class of DMA, the class using various kinds of lists to manage the memory blocks controlled by the DMA. To obtain reusable formal models and tractable formal reasoning, we organise these models in a hierarchy ranked by refinement relations. We prove the soundness of models and the refinement relations using the modeling framework Event-B and the theorem prover Rodin. We demonstrate that our hierarchy is a basis for an algorithm theory for list based DMA: it abstracts various existing implementations of DMA and leads to new DMA implementations. The applications of this formalisation include model-based code generation, testing, and static analysis.

关键词： dynamic memory allocators formal methods refinement Event-B Rodin model-based design

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Iterative rational krylov algorithms for model reduction of a class of constrained structural dynamic system with engineering applications

arXiv

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arXiv 2021年

作者： Du, Xin Uddin, Mohammad Monir Fony, A. Mostakim Hossain, Md. Tanzim Shuzan, Md. Nazmul Islam School of Mechatronic Engineering and Automation Shanghai University Shanghai200072 China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China Department of Mathematics and Physics North south University Dhaka1229 Bangladesh Department of Mathematics Chittagong University Chittagong Bangladesh Department of Electrical and Computer Engineering North South University Dhaka1229 Bangladesh

This paper discusses model order reduction of large sparse second-order index-3 differential algebraic equations (DAEs) by applying Iterative Rational Krylov Algorithm (IRKA). In general, such DAEs arise in constraint mechanics, multibody dynamics, mechatronics and many other branches of sciences and technologies. By deflecting the algebraic equations the second-order index-3 system can be altered into an equivalent standard second-order system. This can be done by projecting the system onto the null space of the constraint matrix. However, creating the projector is computationally expensive and it yields huge bottleneck during the implementation. This paper shows how to find a reduce order model without projecting the system onto the null space of the constraint matrix explicitly. To show the efficiency of the theoretical works we apply them to several data of second-order index-3 models and experimental resultants are discussed in the paper. © 2021, CC BY.

关键词： Differential equations

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Integrated carbon and nitrogen management for cost-effective environmental policies in China

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Science (New York, N.Y.) 2025年第6751期388卷 1098-1103页

作者： Xin Xu Xiuming Zhang Yiyang Zou Tianrun Chen Jingfang Zhan Luxi Cheng Wilfried Winiwarter Shaohui Zhang Peter M Vitousek Wim de Vries Baojing Gu State Key Laboratory of Soil Pollution Control and Safety Zhejiang University Hangzhou China. College of Environmental and Resource Sciences Zhejiang University Hangzhou China. International Institute for Applied Systems Analysis Laxenburg Austria. Ministry of Education Key Laboratory of Environment Remediation and Ecological Health Zhejiang University Hangzhou China. College of Computer Science and Technology Zhejiang University Hangzhou China. Policy Simulation Laboratory Zhejiang University Hangzhou China. Institute of Environmental Engineering University of Zielona Góra Zielona Góra Poland. School of Economics and Management Beihang University Beijing China. Department of Earth System Science Stanford University Stanford CA USA. Wageningen University and Research Earth Systems and Global Change Group Wageningen Netherlands. Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment Zhejiang University Hangzhou China.

Carbon and nitrogen are central elements in global biogeochemical cycles. To effectively manage carbon and nitrogen in China, we developed a comprehensive model for quantifying their fluxes, investigating their interplay across 16 human and natural subsystems. Between 1980 and 2020, nitrogen losses in China increased 2.3-fold and carbon emissions surged 6.5-fold. Integrated carbon and nitrogen management holds the potential for a 74% reduction in nitrogen losses to air and water and a 91% decrease in carbon emissions to the atmosphere by 2060. Compared with separate control of carbon or nitrogen, integrated management delivers an additional reduction of 1.8 million tons of nitrogen and 26.5 million tons of carbon by 2060, bringing out a 37% decrease in unit abatement cost and a net societal benefit of 1384 billion USD.

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Compound control method for DC–DC converter

Compound control method for DC–DC converter

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2019 Jiangsu Annual Conference on Automation, JACA 2019

作者： Tang, Yongwei Li, Juan Li, Shengquan Lin, Zhongwei Wang, Shuwang Department of Electrical Engineering School of Electrical Energy and Power Engineering Yangzhou University Yangzhou225127 China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer Engineering North China Electric Power University Beijing102206 China

Considering the problems of internal and external disturbances, i.e. time-varying load, inaccurate system model and external uncertainties etc., a compound control strategy based on model predictive control (MPC) and non-linear extended state observer (ESO) are proposed to attenuate the output voltage fluctuation under continuous conduction mode (CCM) mode of the buck circuits. In addition, a non-linear ESO is used to observe all kinds of uncertainties caused by internal and external disturbances and to eliminate their effects by compensating these disturbances in the feed-forward channel. Compared with the pure MPC control, the simulation results show that the proposed composite control method has the better disturbance suppression effect and also can effectively improve the stability of the buck circuit. © 2019 Institution of engineering and Technology. All rights reserved.

关键词： Model predictive control

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A Geometric Approach to On-road Motion Planning for Long and Multi-Body Heavy-Duty Vehicles

A Geometric Approach to On-road Motion Planning for Long and...

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IEEE Symposium on Intelligent Vehicle

作者： Rui Oliveira Oskar Ljungqvist Pedro F. Lima Bo Wahlberg Autonomous Transport Solutions Scania CV AB Södertälje Sweden Division of Automatic Control Linköping University Linköping Sweden Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

ISBN: (数字)9781728166735

ISBN: (纸本)9781728166742

Driving heavy-duty vehicles, such as buses and tractor-trailer vehicles, is a difficult task in comparison to passenger cars. Most research on motion planning for autonomous vehicles has focused on passenger vehicles, and many unique challenges associated with heavy-duty vehicles remain open. However, recent works have started to tackle the particular difficulties related to on-road motion planning for buses and tractor-trailer vehicles using numerical optimization approaches. In this work, we propose a framework to design an optimization objective to be used in motion planners. Based on geometric derivations, the method finds the optimal trade-off between the conflicting objectives of centering different axles of the vehicle in the lane. For the buses, we consider the front and rear axles trade-off, whereas for articulated vehicles, we consider the tractor and trailer rear axles trade-off. Our results show that the proposed design strategy produces planned paths that considerably improve the behavior of heavy-duty vehicles by keeping the whole vehicle body in the center of the lane.

关键词： Axles Planning Optimization Roads Agricultural machinery Numerical models Computational modeling

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Modeling a target-selection motion by leveraging an optimal feedback control mechanism

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Science China(Information Sciences) 2018年第4期61卷 209-211页

作者： Jin HUANG Xiaolan PENG Feng TIAN Hongan WANG Guozhong DAI Beijing Key Laboratory of Human-Computer Interaction Institute of Software Chinese Academy of Sciences State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences School of Computer and Control Engineering University of Chinese Academy of Sciences

Target selection has always been a popular research topic in the human-computer interaction(HCI)*** with continuous interactive spaces,such as video games,augmented reality(AR),and virtual reality(VR),are becom-

关键词： Modeling a target-selection motion by leveraging an optimal feedback control mechanism

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NO_x emission model for coal-fired boilers using partial least squares and extreme learning machine

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Journal of Southeast University(English Edition) 2019年第2期35卷 179-184页

作者： Dong Ze Ma Ning Li Changqing Hebei Engineering Research Center of Simulation and Optimized Control for Power Generation North China Electric Power UniversityBaoding 071003China School of Control and Computer Engineering North China Electric Power UniversityBeijing 102206China

To implement a real-time reduction in NOx,a rapid and accurate model is required.A PLS-ELM model based on the combination of partial least squares(PLS)and the extreme learning machine(ELM)for the establishment of the NOx emission model of utility boilers is ***,the initial input variables of the NOx emission model are determined according to the mechanism ***,the initial input data is extracted by ***,the extracted information is used as the input of the ELM model.A large amount of real data was obtained from the distributed control system(DCS)historical database of a 1 000 MW power plant boiler to train and validate the PLS-ELM *** modeling performance of the PLS-ELM was compared with that of the back propagation(BP)neural network,support vector machine(SVM)and ELM *** mean relative errors(MRE)of the PLS-ELM model were 1.58%for the training dataset and 1.69%for the testing *** prediction precision of the PLS-ELM model is higher than those of the BP,SVM and ELM *** consumption time of the PLS-ELM model is also shorter than that of the BP,SVM and ELM models.

关键词： NOx emission partial least squares extreme learning machine coal-fired boiler

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