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Robust exponential load frequency control for time delay power system considering wind power ⁎

IFAC-PapersOnLine 2020年第2期53卷 12536-12541页

作者： Li Jin Xingchen Shang-Guan Yong He Chuan-Ke Zhang Lin Jiang Min Wu School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China Department of Electrical Engineering and Electronics University of Liverpool Liverpool L69 3GJ United Kingdom

The injection of intermittent wind power reduces the equivalent inertia of power systems, and therefore, the change rate of frequency deviation for the load frequency control (LFC) schemes is increased. LFC schemes employ communication channels to transmit signals, which introduces time delays resulting in badly dynamic performance. This paper presents a delay-dependent approach to obtain the robust load frequency controllers based on decay rate for a multi-area LFC scheme integrated with wind power. An index of decay rate related to settling time is introduced. For a preset delay upper bound, controller gains are optimized by maximizing the decay rate. Also, the controller gains can be designed under the desired decay rate while obtaining the allowable maximum delay margins. Case studies are based on the deregulated multi-area LFC system to verify the robustness of developed controller against inertia reduction. Moreover, the proposed method enables the frequency deviation to be restrained and eliminated within a few seconds.

关键词： Load frequency control wind power communication delay decay rate

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Switching Method Based Load Frequency control for Power System with Energy-Limited DoS Attacks ⁎

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IFAC-PapersOnLine 2020年第2期53卷 13508-13513页

作者： Xingchen Shang-Guan Li Jin Yong He Chuan-Ke Zhang Lin Jiang Joseph William Spencer Min Wu School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China Department of Electrical Engineering and Electronics University of Liverpool Liverpool L69 3GJ United Kingdom

A load frequency control (LFC) scheme for modern power systems employs an open communication network to transmit control/measurement signals. The usage of the open communication network in power system makes the LFC scheme more vulnerable to communication network attacks, for example, a denial-of-service (DoS) attack. This attack will prevent a certain amount of transmission of the signals so as to degrade the performance of LFC scheme, or even lead to instability of power system. Therefore, this paper concerns LFC scheme for single-area power system with energy-limited DoS attack based on switching method. Compared with the latest schemes only considering duration of a DoS attacks, the proposed LFC takes fully into account both the duration and attack frequency of the DoS attack. A switching LFC model for a single-area power system is firstly constructed based on the characteristic of periodical sampling and DoS attacks. Then, an exponential stability criterion is developed in terms of the duration and frequency of a DoS attack. Next, a feasible controller of LFC scheme is derived by solving linear matrix inequalities in the criterion. Finally, a detailed design algorithm of LFC scheme is presented for a known DoS attack or an unknown DoS attack. The effectiveness of the proposed LFC scheme is evaluated on a single-area power system under DoS attacks. The proposed LFC scheme is compared with a robust LFC scheme and an event-triggered H ∞ LFC scheme. The obtained contrasting results demonstrate that the proposed LFC scheme can defend DoS attacks with limited energy, and can perform better control effect in the presence of load fluctuations.

关键词： Power system Load frequency control Open communication network Switching system DoS attacks Exponential stability

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A Simulation-based Online Evolutionary Algorithm for Combat in StarCraft II

A Simulation-based Online Evolutionary Algorithm for Combat ...

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International Conference on intelligent Human-Machine Systems and Cybernetics, IHMSC

作者： Yongfeng Liu Changhe Li Sanyou Zeng School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan China

ISBN: (数字)9781728165172

ISBN: (纸本)9781728165189

Real-time strategy (RTS) games have become one of the hotspots in the field of artificial intelligence research due to the large search space, long-term planning, and real-time constraint. In view of the fact that most of the current research on solving the RTS combat problem uses offline training methods, and these methods may need a lot of training time, this work uses an evolutionary algorithm (EA) to directly optimize the units' action sequences online. In order to solve the problems of repetitive actions caused by the neutral area and the size correlation caused by cooperation between units, three search operators are proposed. It is shown that this method can effectively solve the combat problem in RTS games.

关键词： Games Genomics Bioinformatics Sociology Statistics Data models Springs

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Asymmetric Barrier Function-based Adaptive control of a Four-Wheel-Steering Mobile Robot*

Asymmetric Barrier Function-based Adaptive Control of a Four...

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IEEE Region 10 International Conference TENCON

作者： Yuanlong Xie Liquan Jiang Jie Meng Shuting Wang Shiqi Zheng Hao Wu School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan China School of Automation China University of Geosciences Wuhan China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

ISBN: (数字)9781728184555

ISBN: (纸本)9781728184562

Four-wheel-steering mobile robots (FMR) are extensively-adopted for manufacturing applications. However, the robust trajectory tracking of FMR is hard to achieve due to the complex disturbances. For addressing the challenge, an asymmetric barrier function-based adaptive control (ABFAC) method is presented here for obtaining a robust direct yaw moment control scheme for the FMR. The praiseworthy features of the proposed ABFAC method are twofold: (a) It does not need the information concerning the upper boundary information of the unknown uncertainties; (b) By introducing the barrier function, the output signals are guaranteed to be within the desired neighborhood since the sliding mode gains will grow once the disturbance derivatives increase. In this context, the proposed ABFAC method drives the resultant trajectory tracks the variation tendency of the disturbances, guaranteeing robust closed-loop responses. The global stability of the FMR can be ensured theoretically. Finally, experimental results of real-time FMR are provided to validate the applicability of our ABFAC method.

关键词： Asymptotic stability Trajectory tracking Stability analysis Trajectory Mobile robots Adaptive control Convergence

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Design of audio to image cross-modal learning and generation based on single-layer CoPt spin-orbit torque devices

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Journal of Magnetism and Magnetic Materials 2025年 629卷

作者： Likun Qian Liu Yang Chao Zuo Ying Tao Wendi Li Fang Jin Huihui Li Kaifeng Dong School of Future Technology China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan 430074 China School of Automation China University of Geosciences Wuhan 430074 China Wuhan Second Ship Design and Research Institute Wuhan 430064 China Beijing Superstring Academy of Memory Technology Beijing 100176 China

Despite remarkable achievements in neural network applications using spin–orbit torque (SOT) devices, current research predominantly focuses on unimodal classification tasks, while cross-modal learning tasks often suffer from suboptimal generation quality. To address this limitation, we employ generative adversarial networks (GANs) based on CoPt-SOT to achieve cross-modal learning and generation from speech to handwritten digit images. Initially, we explore the field-free switching characteristics of single-layer CoPt devices, developing spin-based implementations of Scaled Rectified Linear Unit (SReLu), Sigmoid, and Tanh neuronal functions. Simultaneously, we leverage the nonvolatile multistate characteristics of CoPt devices to realize excitatory-inhibitory synaptic plasticity. Subsequently, for the first time, we construct half-spin and full-spin GAN networks using these spin-based neurons and synapses, enabling cross-modal learning and generation between speech and image domains. Finally, we evaluate the performance of these networks through handwritten digit recognition tasks, achieving impressive recognition accuracies of 93.78 % and 88.61 % for half-spin and full-spin implementations, respectively. Notably, this work overcomes the existing bottleneck in SOT device applications, which have been largely confined to unimodal classification tasks, and demonstrates significant potential for expanding the scope of SOT-based technologies.

关键词： CoPt single-layer Cross-modal learning Field-free switching Neural network

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An Efficient Method to Discover Association Rules of Mode-Dependent Alarms Based on the FP-Growth Algorithm

An Efficient Method to Discover Association Rules of Mode-De...

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IEEE Canada Electric Power Conference, EPEC

作者： Kai Ru Wang Wenkai Hu Tongwen Chen University of Alberta Edmonton Alberta T6G 1H9 Canada School of Automation and Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences Wuhan China

ISBN: (数字)9781728164892

ISBN: (纸本)9781728164908

State-based alarming is an advanced technique to reduce nuisance alarms and alarm floods by suppressing alarms associated with certain conditions or operating modes. To implement this technique, the key is to find the associations between operating modes and alarms. In practice, this is mainly done based on the experience of plant operators and expert knowledge of process engineers, and thus is very time consuming. Therefore, this paper proposes a data driven method to discover the association rules of mode-dependent alarms for both single and multiple operating modes from the historical Alarm and Event (A&E) logs in an efficient way based on a data mining approach named FP-Growth. The effectiveness of the proposed method is demonstrated by an industrial case study.

关键词： Data mining Databases Alarm systems Power systems Conferences Systematics Standards

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nonlocal quark condensate from Dyson-Schwinger Equation and its contributions to the gluon vacuum polarization based on OPE approach

arXiv

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arXiv 2021年

作者： Huang, Jing-Hui Duan, Xue-Ying Huan, Chen Wang, Guang-Jun Hu, Xiang-Yun School of Institute of Geophysics and Geomatics China University of Geosciences Lumo Road 388 Wuhan430074 China School of Automation China University of Geosciences Lumo Road 388 Wuhan430074 China School of Mathematics and Physics China University of Geosiciences Lumo Road 388 Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China

The operator-product expansion(OPE) could be employed to obtain the lowest-order, nonlocal quark scalar condensate component of gluon vacuum polarization. In particular, nonlocal quark scalar condensate can be calculated by solving Dyson-Schwinger Equation(DSE) of QCD. Then, field-theoretic aspects of the gluon vacuum polarization and nonperturbative gluon propagator will be considered in the Landau gauge of the Lorentz gauge fixing. The gluon propagator we obtained is finite in the infrared domain where the single gluon mass mg can be determined. Our results of the ratio mg/ΛQCD the range of that from 1.33 to 1.39 agree with previous determinations for this ratio. Besides, the analytic structure of the gluon propagators from the OPE's result is explored. Our numerical analysis of the gluon' Schwinger function finds clear evidence of the positivity violations in the gluon propagator. In addition, a new method for obtaining the chemical potential dependence of the gluon vacuum polarization and the dressed gluon propagator is developed. © 2021, CC BY.

关键词： Polarization

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Applications of Evolutionary Computation and Artificial Intelligence in Metallurgical Industry

Applications of Evolutionary Computation and Artificial Inte...

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General Conference on Emerging Arts of Research on Management and Administration, GEAR 2018

作者： An, Jianqi She, Jinhua Chen, Huicong Wu, Min School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China School of Engineering Tokyo University of Technology Tokyo192-0982 Japan

ISBN: (纸本)9789811369353

Metallurgical industry is one of the most important industrial processes, which mainly consists of coking process, sintering process, ironmaking process, and casting and rolling process. All of the metallurgical processes are complex, multivariate and nonlinear systems with large time-delay. Some chemical or physical mechanisms are even not clear and uncertain. It is difficult to establish the models, design the controllers, devise the scheduling and optimization strategies, and make the operation decisions by the conventional mechanism-based methods. Nevertheless, these processes work continuously and repetitively, which produces large amounts of data, and consists of lots of knowledge and expert experiences. In the last decade, evolutionary computation and artificial intelligence (ECAI) began to be widely used in metallurgical industry and many good results were reported. This letter demonstrates how the development of ECAI impacts the metallurgical industry by analyzing some good applications of the ECAI in typical metallurgical processes and discusses the future development trends and challenges of the applications of the ECAI in metallurgical industries. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Sintering

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Fully linear graph convolutional networks for semi-supervised learning and clustering

arXiv

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arXiv 2021年

作者： Cai, Yaoming Zhang, Zijia Cai, Zhihua Liu, Xiaobo Ding, Yao Ghamisi, Pedram School of Computer Science China University of Geosciences Wuhan430074 China School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences Wuhan430074 China Xi'an Research Institute of High Technology Xi'an710000 China Helmholtz Institute Freiberg for Resource Technology Freiberg09599 Germany Vienna1030 Austria

This paper presents FLGC, a simple yet effective fully linear graph convolutional network for semi-supervised and unsupervised learning. Instead of using gradient descent, we train FLGC based on computing a global optimal closedform solution with a decoupled procedure, resulting in a generalized linear framework and making it easier to implement, train, and apply. We show that (1) FLGC is powerful to deal with both graph-structured data and regular data, (2) training graph convolutional models with closed-form solutions improve computational efficiency without degrading performance, and (3) FLGC acts as a natural generalization of classic linear models in the non-Euclidean domain, e.g., ridge regression and subspace clustering. Furthermore, we implement a semisupervised FLGC and an unsupervised FLGC by introducing an initial residual strategy, enabling FLGC to aggregate long-range neighborhoods and alleviate over-smoothing. We compare our semi-supervised and unsupervised FLGCs against many state-of-the-art methods on a variety of classification and clustering benchmarks, demonstrating that the proposed FLGC models consistently outperform previous methods in terms of accuracy, robustness, and learning efficiency. The core code of our FLGC is released at https://***/AngryCai/FLGC. Copyright © 2021, The Authors. All rights reserved.

关键词： Clustering algorithms

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Adaptive Fuzzy control for Fractional-Order Interconnected Systems with Unknown control Directions

arXiv

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arXiv 2020年

作者： Liang, Bingyun Zheng, Shiqi Ahn, Choon Ki School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China School of Electrical Engineering Korea University Seoul136-701 Korea Republic of

This paper concentrates on the study of the decentralized fuzzy control method for a class of fractional-order interconnected systems with unknown control directions. To overcome the difficulties caused by the multiple unknown control directions in fractional-order systems, a novel fractional-order Nussbaum function technique is proposed. This technique is much more general than those of existing works since it not only handles single/multiple unknown control directions but is also suitable for fractional/integer-order single/interconnected systems. Based on this technique, a new decentralized adaptive control method is proposed for fractional-order interconnected systems. Smooth functions are introduced to compensate for unknown interactions among subsystems adaptively. Furthermore, fuzzy logic systems are utilized to approximate unknown nonlinearities. It is proven that the designed controller can guarantee the boundedness of all signals in interconnected systems and the convergence of tracking errors. Two examples are given to show the validity of the proposed method. Copyright © 2020, The Authors. All rights reserved.

关键词： Algebra

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