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第三十八届中国控制会议

作者： Zhipeng Li Minyue Fu Qianqian Cai Wei Meng School of Automation Guangdong University of Technology Guangdong Province Key Laboratory of Intelligent Decision and Cooperative Control School of Electrical Engineering and Computer Science University of Newcastle

This paper searches for the leader-follower stochastic differential Stackelberg game under a partial observed information. The controlled system equation and the observation equation are looked as the equality constraints, and then variation method is used to derive the necessary condition of this differential game problem for follower and leader respectively. Finally,an example is given to illustrate its application.

关键词： Stochastic differential game partial observation

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Exponentially Convergent Algorithm Design for Constrained Distributed Optimization via Non-smooth Approach

arXiv

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arXiv 2020年

作者： Li, Weijian Zeng, Xianlin Liang, Shu Hong, Yiguang Department of Automation University of Science and Technology of China HefeiAnhui230027 China Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China Institute of Artificial Intelligence University of Science and Technology Beijing Beijing100083 China

We consider minimizing a sum of non-smooth objective functions with set constraints in a distributed manner. As to this problem, we propose a distributed algorithm with an exponential convergence rate for the first time. By the exact penalty method, we reformulate the problem equivalently as a standard distributed one without consensus constraints. Then we design a distributed projected subgradient algorithm with the help of differential inclusions. Furthermore, we show that the algorithm converges to the optimal solution exponentially for strongly convex objective functions. Copyright © 2020, The Authors. All rights reserved.

关键词： Constrained optimization

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Development of hydroxyapatite-enhanced membrane for nanoplastics removal: Multiple scenarios and mechanism exploration

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Journal of hazardous materials 2025年 495卷 138781页

作者： Mengna Li Guohe Huang Shuguang Wang Jing Huang Zeyuan Xu Environmental Systems Engineering Program University of Regina Regina Saskatchewan S4S 0A2 Canada China-Canada Center of Energy Environment and Sustainability Research UR-SDU School of Environmental Science and Engineering Shandong University Qingdao 266237 China. China-Canada Center of Energy Environment and Sustainability Research UR-SDU School of Environmental Science and Engineering Shandong University Qingdao 266237 China. Electronic address: huangg@uregina.ca. Shandong Key Laboratory of Water Pollution Control and Resource Reuse School of Environmental Science and Engineering Shandong University Qingdao 266237 China. Environmental Systems Engineering Program University of Regina Regina Saskatchewan S4S 0A2 Canada. Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia 27100 Italy.

Nanoplastics (NPs) are widespread in wastewater systems and more toxic than microplastics (MPs), necessitating effective removal techniques. Although membranes can effectively remove MPs, their efficiency and mechanisms for NPs removal require further study. A novel hydroxyapatite functionalized PVDF (HAPF) membrane was developed for NPs removal. The optimized HAPF membrane was prepared via a one-step method with 800 mg/L HAP at pH 7.3 for 8 hours. It achieved a water flux of 4376.44 LMH, 3.4 times higher than that of the pristine PVDF membrane, while maintaining a polystyrene (PS) NPs rejection above 99.5 %. The HAPF membrane maintained 95 % of its pure water flux when treating wastewater with only PS NPs, but exhibited severe flux decline under varying conditions, such as surface-functionalized PS NPs, pH changes, or coexisting contaminants. Among these, the presence of MgSO alongside PS NPs caused the most severe water flux reduction, with the HAPF membrane undergoing complete blocking, followed by the formation of a cake layer. XDLVO results revealed that there is an attractive interaction between the HAPF membrane and PS NPs, primarily driven by acid-base interaction. The HAPF membrane exhibited significantly lower R and R values than the PVDF membrane and achieved a flux recovery rate of 92.94 % over multiple fouling-cleaning cycles. Its water flux was 18.9 times that of the PVDF membrane during long-term filtration. The developed HAPF membrane holds significant potential for advanced water treatment and fouling resistance .

关键词： Coexisting pollutants Hermia theory Hydroxyapatite functionalized PVDF (HAPF) membrane Nanoplastic removal XDLVO theory

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Design of Deviation Correction control System in Vertical Drilling Process

Design of Deviation Correction Control System in Vertical Dr...

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第三十八届中国控制会议

作者： Dian Zhang Luefeng Chen Chengda Lu Min Wu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Software and Electrical Engineering Swinburne University of Technology

This paper is concerned with design of a deviation correction control system for vertical drilling process. Notice that only inclination angle is considered by traditional deviation correction systems, which may cause that the drilling trajectory extends around the wellhead's plumb line or gets away from the line. In this paper, focusing on the drilling trajectory itself, a deviation correction control scheme is provided to improve the vertical precision of the vertical drilling while maintaining small inclination angles. A hybrid modeling method for establishing the trajectory extension model and a model predictive control strategy based on the model are integrated in the scheme. It is expected that the phenomenon of spiral-like drilling trajectory can be attenuated by our control system over the traditional ones.

关键词： Geological Exploration Vertical Drilling Deviation Correction control Trajectory Extension Model Model Predictive control

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Short-Term Photovoltaic Power Prediction Modeling Based on AdaBoost Algorithm and Elman

Short-Term Photovoltaic Power Prediction Modeling Based on A...

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IEEE International Conference on Power and Energy systems (ICPES)

作者： Wenxuan Sun Tao Zhang Ran Tao Anna Wang College Of Information Science and Engineering Northeastern University Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China School of Electrical Engineering Dalian University of Technology Dalian China

ISBN: (数字)9781665404945

ISBN: (纸本)9781665404952

In recent years, with the rapid expansion of the installed capacity of renewable energy systems, the availability, stability and quality of smart grids have become increasingly important [1] . The application of renewable energy production forecasting has also been rapidly developed, especially in the field of solar photovoltaic (PV) [2][3] . In the example of solar PV output prediction, machine learning and hybrid technologies have been implemented for many applications. In this paper, a high-precision PV system output power prediction model based on improved AdaBoost and Elman is proposed. Multiple model using integrated AdaBoost algorithm fusion with the bat algorithm for the parameters of optimized combination of weak Elman neural network predictor to become a higher prediction precision, the method of strong predictor of the model can according to the weather information, such as temperature, solar radiation and the history of the output of the PV system data, the probability of photovoltaic power generation for 12 hours and deterministic prediction. The prediction accuracy of the model is determined by Root Mean Squared Error (RMSE). Experimental results show that the prediction accuracy of this algorithm is better than that of other benchmark models, and the algorithm can effectively predict the volatility and irregularity of complex time series.

关键词： Photovoltaic systems Renewable energy sources Machine learning algorithms Machine learning Predictive models Prediction algorithms Numerical models

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Optimization of Grouping Evacuation Strategy in High-rise Building Fires Based on Graph Theory and Computational Experiments

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IEEE/CAA Journal of Automatica Sinica 2018年第6期5卷 1104-1112页

作者： Yuling Hu Xiwei Liu School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture Beijing 100044China Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing 100044China State Key Laboratory fo Management and Control for Complex Systems Institute of Automation Chinese Academy of SciencesBeijing 100190China Qingdao Academy of Intelligent Industries Qingdao 266109China

It is difficult to rescue people from outside, and emergency evacuation is still a main measure to decrease casualties in high-rise building fires. To improve evacuation efficiency, a valid and easily manipulated grouping evacuation strategy is proposed. Occupants escape in groups according to the shortest evacuation route is determined by graph theory. In order to evaluate and find the optimal grouping, computational experiments are performed to design and simulate the evacuation processes. A case study shown the application in detail and quantitative research conclusions is obtained. The thoughts and approaches of this study can be used to guide actual high-rise building evacuation processes in future.

关键词： Computational experiments grouping evacuation graph theory high-rise building fire management strategies

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Shaping Effect of Phase-locked Loop on Impedance Characteristics of PMSG Wind Turbines Connected to Weak-grid

Shaping Effect of Phase-locked Loop on Impedance Characteris...

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IEEE General Meeting Power& Energy Society

作者： Feiya Wan Zhen Li Bin Liu Guanghui Li Xiaoliang Dong Xi Chen Samson S. Yu Amanullah M. T. Oo Zhenyu Shan Xiangdong Liu School of Automation and Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology Beijing China China Electric Power Research Institute Beijing China State Grid Corporation of China and North China Branch of State Grid Corporation of China Beijing China GEIRI North America USA School of Engineering Deakin University 75 Pigdon Rd Waurn Ponds Victoria Australia School of Electrical and Control Engineering North China University of Technology Beijing China

ISBN: (数字)9781728155081

ISBN: (纸本)9781728155098

With the booming installed capacity of permanent magnet synchronous generator (PMSG) for wind energy generation, the grid becomes weaker and the oscillation events are frequently observed in weak-grid-tied large-scale grid-connected PMSG wind farms. Although the impedance-based method is effective to analyze the stability of grid-connected systems, the mathematical relationship between external impedance characteristics and the internal controllers has not been quantitatively analyzed in depth, which is beneficial to the controller design. This paper studies the influence of phase-locked loop (PLL) on the impedance characteristics based on the analytical sequence impedance model of PMSG with typical topology and control structure. The shaping effect of PLL on the impedance characteristics is described so as to clearly describe the relationship between the external impedance characteristics of the wind turbines and the internal controller. Finally, the stability analysis of the grid-connected PMSG wind turbine system is provided in Matlab and simulation results are given to verify the oscillating mechanism caused by PLL.

关键词： Synchronous generators Stability analysis Wind turbines Topology Impedance Phase locked loops Oscillators

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RFBLS: A robust rough fuzzy broad learning system with local neighborhood structure

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Neurocomputing 2025年 647卷

作者： Yonghe Chu Yanlong Guo Peng Li Weiping Ding Witold Pedrycz Heling Cao School of Artificial Intelligence and Computer Science Nantong University Nantong 226019 China College of Information Science and Engineering Henan University of Technology Zhengzhou 450001 China Key Laboratory of Grain Information Processing and Control(Henan University of Technology) Ministry of Education Zhengzhou 450001 China Centre for Complexity Science Henan University of Technology Zhengzhou 450001 China Department of Electrical and Computer Engineering University of Alberta Edmonton AB T6G 2R3 Canada Institute of Systems Engineering Macau University of Science and Technology Macau SAR Taipa 999078 China Research Center of Performance and Productivity Analysis Istinye University Istanbul Turkiye

As an extension of random vector functional link neural network (RVFLNN), the broad learning system (BLS) has gradually been applied in various fields due to its advantages of simple network structure, rapid training, and fast model updating. Despite its remarkable achievements, there are still some difficulties and challenges that restrict its further application in practical tasks. In BLS, all samples equally contribute to constructing the optimal classification boundary. However, when training samples contain noise or outliers, it will result in the obtained classification boundary not being the true optimal classification boundary. In other words, BLS is sensitive to noise points or outliers. To address it, we propose a robust rough fuzzy broad learning system with local neighborhood structure (RFBLS). In RFBLS, fuzzy sets are utilized by associating a membership degree with each sample. This incorporation ensures diverse contributions of different samples during the minimization of the objective function. Samples with noise or outliers are assigned smaller weights, effectively eliminating the influence of noise and outlier samples in the learning process. We employ the rough set theory to explore the influence-decision degree of each conditional attribute on the decision attribute, aiming to eliminate the impact of redundant or interfering features. Subsequently, we comprehensively consider the distance between samples and class centers, as well as the local neighborhood structure relationship between samples. Initially, we calculate the initial membership degree of each sample based on the distance to class centers. Then, utilizing fuzzy K-nearest neighbors, we calculate and rank the membership degrees of K nearest neighbors for each sample. These rankings are then weighted with the initial membership degree, achieving the fusion of relationships and membership degree calculations between samples. Finally, extensive comparative experiments are conducted on var

关键词： Broad learning system Fuzzy theory K-nearest neighbors Neighborhood rough sets

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Corrigendum to “Numerical analysis of the magnetic field impact on hydrothermal characteristics of a microchannel heatsink with Fe 3 O 4 ferrofluid and various pin-fin shapes” [J. Magn. Magn. Mater. 585 (2023) 171102]

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Journal of Magnetism and Magnetic Materials 2024年 610卷

作者： Tao Hai Kamal Sharma Riyam K. Marjan Babak Farhang Mohamed H. Mahmoud Hassan Fouad Walid El-Shafai School of Computer and Information Qiannan Normal University for Nationalities Duyun Guizhou 558000 China School of Electronics and Information Engineering Ankang University China State Key Laboratory of Public Big Data Guizhou University Guizhou Guiyang 550025 China Institute of Engineering and Technology GLA University Mathura UP 281406 India Department of Intelligent Medical Systems Al-Mustaqbal University College Babylon 51001 Iraq Department of Energy Technology Aalborg University Denmark Department of Biochemistry College of Science King Saud University Riyadh Saudi Arabia Biomedical Engineering Department Faculty of Engineering Helwan University Cairo P.O. Box 11795 Egypt Department Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf 32952 Egypt

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Resilient Exponential Consensus with Time-Varying Adversary Attacks and Asynchronous Events

Resilient Exponential Consensus with Time-Varying Adversary ...

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IEEE Annual Conference on Decision and control

作者： Weiguo Xia Ji Liu Shuang Li Xi-Ming Sun Min Han Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education and the School of Control Science and Engineering Dalian University of Technology China Department of Electrical and Computer Engineering Stony Brook University USA

ISBN: (数字)9781728113982

ISBN: (纸本)9781728113999

This paper studies the resilient consensus problem with time-varying adversary attacks and asynchronous events. In the synchronous or asynchronous update case, all the nodes or only a fraction of nodes update their states at each time step, respectively. For the synchronous update case, the nodes under attack are time-varying but do not change after some finite time;for the asynchronous update case, the nodes under attack are time-invariant. For both cases, a resilient consensus can be reached exponentially fast under a network topology condition inspired by the notion of the scrambling matrix and an explicit expression for the convergence rate is provided. Numerical examples are given to validate the theoretical results and to compare the performance with an existing algorithm.

关键词： Optimization Convergence Heuristic algorithms Distributed algorithms Sun Network topology Estimation

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