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Chinese Automation Congress (CAC)

作者： Yi-Yuan Huang Min-Rong Chen Liu-Qing Yang Kang-Di Lu Guo-Qiang Zeng School of Computer Science South China Normal University Guangzhou China Institute of Cyber Systems and Control Zhejiang University Hangzhou China National-Local Joint Engineering Laboratory of Digitalize Electrical Design Technology Wenzhou University Wenzhou China

Electric load forecasting is a vital role in obtaining effective management of modern power systems. The accuracy forecasting results will lead to the improvement of the energy efficiency and reduction of production cost. This paper presents a novel electric load forecasting model by using BP neural network and improved bat algorithm with extremal optimization called IBA-EO-BP model. First, to enhance the global search ability and diversity of original bat algorithm (BA), we propose IBA-EO by improving original BA and combining with extremal optimization. Then, considering traditional BP is more likely converge to local optimal values, the IBA-EO is employed to find out the optimal connection weight parameters in BP. Two datasets from energy market operation in Australia are selected as case study. The simulation results demonstrate that the proposed IBA-EO-BP model is much more accurate than the traditional BP forecasting model and persistence model in terms of three widely used performance indices and two statistical tests.

关键词： Load modeling Load forecasting Predictive models Mathematical model Neural networks Optimization Biological system modeling

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Surrogate Thermal Model for Power Electronic Modules using Artificial Neural Network

Surrogate Thermal Model for Power Electronic Modules using A...

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Annual Conference of the IEEE Industrial Electronics Society

作者： Zhigen Xu Yuan Gao Xin Wang Xiaoyu Tao Qingui Xu School of Electronic and Electrical Dongguan Polytechnic Dongguan China Faculty of Engineering Power Electronics Machi nes and Control Group University of Nottingham Nottingham UK Institute for Aerospace Technology University of Nottingham Nottingham UK School of Sciences Wuhan University of Technology Wuhan China School of Computer Sciences Dongguan University of Technology Dongguan China

Virtual prototyping of power electronic modules aims to allow rapid evaluation of potential designs without building and testing physical prototypes. Among the interests in thermal models of the virtual modules, process of compact thermal models needs effective methodology to fast generate small models describing the thermal performance of a potential design. This study chooses the Generalized Minimized Residual (GMRES) Algorithm to process thermal models due to its efficiency. Based on that, a machine learning aided surrogate model is proposed for the prediction of thermal performance since existing approaches take much time to determine the thermal response to a particular input power. This surrogate model is created by training a dedicated artificial neural network (ANN) on simulation data, after that this model can quickly map the module temperature and the power input in time domain. In the training process, cross-validation method is introduced to determine which neuron structure should be selected for the practical data generated by thermal equations. The test group is noted in cross-validation to give the prediction performance of structure candidates. To verify the proposed method, the resulting data of trained surrogate models are compared with the accurate simulation data after the ANN based cross-validation.

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An Improved Firefly Algorithm Hybridized with Extremal optimization for Parameter Identification of Photovoltaic Models

An Improved Firefly Algorithm Hybridized with Extremal optim...

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Chinese Automation Congress (CAC)

作者： Liu-Qing Yang Min-Rong Chen Yi-Yuan Huang Kang-Di Lu Guo-Qiang Zeng School of Computer Science South China Normal University Guangzhou China Institute of Cyber Systems and Control Zhejiang University Hangzhou China National-Local Joint Engineering Laboratory of Digitalize Electrical Design Technology Wenzhou University Wenzhou China

Firefly algorithm (FA) has widely used to solve various complex optimization problems. However, FA has significant drawbacks in slow convergence rate and easily trapped into local optimum. To tackle these defects, this paper proposes an improved FA combined with extremal optimization (EO), named IFA-EO, where three strategies are incorporated. First, to balance tradeoff between exploration and exploitation, we adopt a new attraction model for FA operation, which combines the full attraction model and the single attraction model through the probability choice strategy. In single attraction model, inspired by the simulated annealing idea, small probability accepts the worse solution to improve the diversity of the offspring. Second, the adaptive step size is proposed according to the number of iterations. Third, we combine EO algorithm with powerful ability in local-search. IFA-EO is employed to handle three different parameters identification problems of photovoltaic model. For comparisons, we choose three swarm intelligence algorithms to compare with IFA-EO. Simulation results demonstrate the superiority of IFA-EO to other three competitors.

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A Method of Conflict Detection for Cooperative Defense Strategy in Power Industrial control System

A Method of Conflict Detection for Cooperative Defense Strat...

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International Conference on Advanced Cloud and Big Data (CBD)

作者： Hongqin Zhu Zi Wang Wei Li Dawei Su Jiawei Sun Muye Li Power Dispatching Control Center State Grid Nanjing Power Supply Company Nanjing P.R. China Nanjing NARI Information & Communication Technology Co. Ltd. NARI Group Co. Ltd./State Grid Electric Power Research Institute Co. Ltd. Nanjing P.R. China School of Computer Science and Engineering Southeast University Nanjing P.R. China Power Dispatching Control Center State Grid Jiangsu Electric Power Co. Ltd. Nanjing P.R. China

With the increasingly rampancy of network attacks and the steady progress of the national smart grid construction, the security protection of the power industrial control system is facing severe challenges. It is an effective means to improve the overall defense capability of the power industrial control system by formulating the security collaborative defense strategy and dynamically configuring the relevant equipment to make them have linkage response. For this purpose, a method of conflict detection for cooperative defense strategy in power industrial control system is proposed in this paper. Based on the formal description of cooperative defense strategy, the type of policy conflicts is analyzed according to the relationship between policy actions and system states. And the policy execution is simulated for detecting conflict by establishing the temporal relationship between policy actions. The experimental results show that this method can reduce the dependence on the system administrator, and can quickly and accurately find the conflicts in the collaborative defense strategy.

关键词： Couplings Industrial control Collaboration Big Data Smart grids Security

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An Effective On-line Surface Particles Inspection Instrument for Large Aperture Optical Element

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International Journal of Automation and computing 2017年第4期14卷 420-431页

作者： Wen-Dong Ding Zheng-Tao Zhang Da-Peng Zhang De Xu Hai-Bing Lv Xin-Xiang Miao Guo-Rui Zhou Hao Liu Research Center of Precision Sensing and Control Institute of Automation Chinese Academy of Sciences School of Computer and Control Engineering University of Chinese Academy of Sciences Laser Fusion Research Center China Academy of Engineering Physics

Surface particles growing in large aperture optical element （LAOE） have significant impact on LAOE＇s stable operation. It is a challenge for the online system to inspect the particles with long working distance, enough precision and high efficiency because of the system constraints. In this paper, an effective and portable inspection instrument is designed based on dark-field imaging principle. A Nikon lens and an industrial high definition （HD） camera are selected to construct the vision system to inspect particles of microns size spreading over hundreds of millimeters. Using two motors and other mechanical structure, the system can realize auto-focus and image rectification functions. The line light sources are installed on both sides of the LAOE in a sealed box while the vision system is portable and working outside the box. An adaptive binarization method is proposed to process the captured dark-field image. The distribution of particles on the LAOE＇s surface is investigated. Because of the high resolution of the captured image, the SSE2 instructions optimization method is used to reduce the time cost of the algorithm. Experiments show that the instrument can inspect LAOE effectively and accurately.

关键词： Dark-field imaging image rectification adaptive binarization particle inspection large aperture optical elements（LAOE）.

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A New FEM-based Brain Tissue Model for Neurosurgical Simulation Using the Optimization Implicit Euler Method

A New FEM-based Brain Tissue Model for Neurosurgical Simulat...

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第37届中国控制会议

作者： Wenguo Hou Peter X.Liu Minhua Zheng Shichao Liu School of Mechanical Electronic and Control EngineeringBeijing Jiaotong University Department of System and Computer Engineering Carleton University

An accurate and computationally efficient model for the deformation of brain tissue is very important in virtual neurosurgical simulation. In this paper, we introduced a new Finite Element Method(FEM) model, which is based on optimization implicit Euler method, for brain tissue deformation. Specifically, both the anisotropic and viscoelastic properties of brain tissue are incorporated into the model, providing more realistic and accurate description of the mechanical features of brain tissue. In the meantime, the model is particularly suitable for GPU-based computing, making it possible to achieve real-time performance for neurosurgical simulation. Simulation results show that the deformation model exhibits the behaviors of anisotropy and viscoelasticity. The proposed model was implemented on a neurosurgical simulator and it showed that the deformation of brain tissue can be rendered with a relatively high degree of visual realism at a refreshment rate of 23 frames per second in a normal PC.

关键词： Brain Tissue Deformation Model Neurosurgical Simulation Optimization Implicit Euler

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Reduced-order proper orthogonal decomposition extrapolating finite volume element format for two-dimensional hyperbolic equations

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Applied Mathematics and Mechanics(English Edition) 2017年第2期38卷 289-310页

作者： Zhendong LUO Fei TENG School of Mathematics and Physics North China Electric Power University Beijing 102206 China School of Control and Computer Engineering North China Electric Power University Beijing 102206 China

This paper is concerned with establishing a reduced-order extrapolating fi- nite volume element （FVE） format based on proper orthogonal decomposition （POD） for two-dimensional （2D） hyperbolic equations. For this purpose, a semi discrete variational format relative time and a fully discrete FVE format for the 2D hyperbolic equations are built, and a set of snapshots from the very few FVE solutions are extracted on the first very short time interval. Then, the POD basis from the snapshots is formulated, and the reduced-order POD extrapolating FVE format containing very few degrees of freedom but holding sufficiently high accuracy is built. Next, the error estimates of the reduced-order solutions and the algorithm procedure for solving the reduced-order for- mat are furnished. Finally, a numerical example is shown to confirm the correctness of theoretical conclusions. This means that the format is efficient and feasible to solve the 2D hyperbolic equations.

关键词： reduced-order finite volume element （FVE） extrapolating format properorthogonal decomposition （POD） hyperbolic equation error estimate numerical simula-tion

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Optimized finite difference iterative scheme based on POD technique for 2D viscoelastic wave equation

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Applied Mathematics and Mechanics(English Edition) 2017年第12期38卷 1721-1732页

作者： Hong XIA Zhendong LUO School of Control and Computer Engineering North China Electric Power UniversityBeijing 102206China School of Mathematics and Physics North China Electric Power UniversityBeijing 102206China

This study develops an optimized finite difference iterative （OFDI） scheme for the two-dimensional （2D） viscoelastic wave equation. The OFDI scheme is obtained using a proper orthogonal decomposition （POD） method. It has sufficiently high accuracy with very few unknowns for the 2D viscoelastic wave equation. Existence, stability, and convergence of the OFDI solutions are analyzed. Numerical simulations verify efficiency and feasibility of the proposed scheme.

关键词： optimized finite difference iterative （OFDI） scheme viscoelastic wave equation proper orthogonal decomposition （POD） existence stability convergence numericalsimulation

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TransMut: a program to predict HLA-I peptide binding and optimize mutated peptides for vaccine design by the Transformer-derived self-attention model

Research Square

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Research Square 2021年

作者： Chu, Yanyi Zhang, Yan Wang, Qiankun Zhang, Lingfeng Wang, Xuhong Wang, Yanjing Wang, Jianmin Jiang, Xue Salahub, Dennis Russell Xiong, Yi Wei, Dong-Qing State Key Laboratory of Microbial Metabolism Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances Joint International Research Laboratory of Metabolic & Developmental Sciences School of Life Sciences and Biotechnology Shanghai Jiao Tong University Shanghai200030 China Department of Chemistry CMS - Centre for Molecular Simulation IQST - Institute for Quantum Science and Technology University of Calgary 2500 University Drive NW CalgaryABT2N 1N4 Canada Department of Clinical Oncology The University of Hong Kong-Shenzhen Hospital Shenzhen China School of Electrical Engineering and Computer Science University of Ottawa 75 Laurier Ave. OttawaONK1N 6N5 Canada The Ministry of Education Key Laboratory of System control and information processing Department of Automation School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200030 China Integrative Biotechnology & Translational Medicine Yonsei University Incheon21983 Korea Republic of Peng Cheng Laboratory Vanke Cloud City Phase I Building 8 Xili Street Nanshan District Guangdong Shenzhen518055 China

Computational prediction of the interaction between human leukocyte antigen (HLA) and peptide (pHLA) can speed up epitope screening and vaccine design. Here, we develop the TransMut framework composed of TransPHLA for pHLA binding prediction and AOMP for mutated peptide optimization, which can be generalized to any binding and mutation task of biomolecules. Firstly, TransPHLA is developed by using a Transformer-derived self-attention model to predict pHLA binding, which is significantly superior to 11 previous methods on pHLA binding prediction, neoantigen and human papilloma virus vaccine identification. For vaccine design, the AOMP program is then developed to automatically optimize mutated peptides to search for mutant peptides with higher affinity to the target HLA and with high homology to the source peptide. Among 3660 non-binding pHLAs, 3630 were successfully mutated. Of these, 94% were verified by the IEDB recommended method, and 88% have homology higher than 80% to the source peptide. © 2021, CC BY.

关键词： Peptides

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How much information is needed in quantized nonlinear control?

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中国科学（信息科学） 2018年第9期61卷 199-211页

作者： Chuang ZHENG Lin LI Leyi WANG Chanying LI School of Mathematical Sciences Beijing Normal University Beijing 100875 China Department of Electrical and Computer Engineering Wayne State University Detroit 48202 USA Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of Sciences Beijing 100190 China

Quantization rate is a crucial measure of complexity in determining stabilizability of control systems subject to quantized state *** paper investigates quantization complexity for a class of nonlinear systems which are subjected to disturbances of unknown statistics and unknown *** class of systems includes linear stablizable systems as special *** lower bounds on the quantization rates are derived which guarantee input-to-state stabilizability for continuous-time and sampled-data feedback strategies,*** examples are provided to validate the results.

关键词： nonlinear systems disturbances input-to-state stabilizability sampled systems quantization rate

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