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7th Asia Conference on Power and Electrical Engineering, ACPEE 2022

作者： Zhang, Shaopeng Yan, Jiongcheng Li, Xin Yang, Dong Ma, Huan Li, Changgang Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong Jinan China State Grid Shandong Electric Power Company Shandong Jinan China Electric Power Research Institute State Grid Shandong Electric Power Company Shandong Jinan China

ISBN: (纸本)9781665418195

Wind power integration makes the uncertainty of power system increasing dramatically, which brings new challenges to the calculation of Total Transfer Capability (TTC). A fast assessment method for probabilistic TTC based on Copula and deep ensemble learning is proposed. Considering wind power output uncertainties and correlation of wind speed in geographical close wind farms, Copula function is adopted to generate scenarios. Stacked Denoising Autoencoder (SDAE) is used to extract features directly from source data. Support Vector Regression (SVR) is selected as regressor and bagging ensemble strategy is applied to further improve the accuracy of the TTC estimation. The case study in simplified Shandong grid validates the effectiveness of the proposed method. © 2022 IEEE.

关键词： Learning systems

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Data-Driven Early Warning for Dynamic Insecurity Risk of Hybrid AC/DC Power Grids

Data-Driven Early Warning for Dynamic Insecurity Risk of Hyb...

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International Conference on Power system Technology (POWERCON)

作者： Jiongcheng Yan Changgang Li Yutian Liu Yuanzhen Zhu Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China Electric Power Research Institute of State Grid Shandong Electric Power Company Jinan China

The dynamic interactions between AC and DC systems and the uncertainty of renewable generation increase the risk of cascading failures and bring challenges for the secure operation of hybrid AC/DC grids. Insecurity early warning identifies the security risk and guides the control decision-making, which is important for the secure power system operation. To achieve fast insecurity early warning, a data-driven early warning method for dynamic insecurity risk is proposed in this paper. First, Latin hypercube sampling and improved K-medoids algorithm are utilized to generate typical operating conditions (OCs) in the future. Then, stacking denoising autoencoders and ensemble extreme learning machines are deployed to construct security risk assessment models to fast assess the dynamic security of typical OCs. And model update is performed to ensure the assessment accuracy when cascading failures occur. Finally, the insecure OCs are ranked into different insecure levels based on the control cost needed to ensure the system security. Simulation results of the Northwest hybrid AC/DC grid in China demonstrate that the proposed method can achieve fast insecurity early warning and effectively track the security risk tendency during the process of cascading failures.

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Decentralized Zeno-Free Event-Triggered control For Multiple Networks Subject to Stochastic Network Delays and Poisson Pulsing Attacks

arXiv

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arXiv 2024年

作者： Zhang, Dandan Jin, Xin Su, Hongye The State Key Laboratory of Industrial Control Technology The Institute of Cyber-Systems and Control The College of Control Science and Engineering Zhejiang University Hangzhou310027 China The Research Institute of Intelligent Complex Systems Fudan University Shanghai200433 China The Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology Shanghai200237 China

By designing the decentralized time-regularized (Zeno-free) event-triggered strategies for the state-feedback control law, this paper considers the stochastic stabilization of a class of networked control systems, where two sources of randomness exist in multiple decentralized networks that operate asynchronously and independently: the communication channels are constrained by the stochastic network delays and also by Poisson pulsing denial-of-service (Pp-DoS) attacks. The time delay in the network denotes the length from a transmission instant to the corresponding update instant, and is supposed to be a continuous random variable subject to certain continuous probability distribution;while the attacks' cardinal number is a discrete random variable supposed to be subject to Poisson distribution, so the inter-attack time, i.e., the time between two consecutive attack instants, is subject to exponential distribution. The considered system is modeled as a stochastic hybrid formalism, where the randomness enters through the jump map into the reset value (the inter-attack time directly related) of each triggered strategy. By only sampling/transmitting state measurements when needed and simultaneously by taking the specific medium access protocols into account, the designed event-triggered strategies are synthesized in a state-based and decentralized form, which are robust (tolerable well) to stochastic network delays, under different tradeoff-conditions between the minimum inter-event times, maximum allowable delays (i.e., potentially tolerable delays) and the frequencies of attacks. Using stochastic hybrid tools to combine attack-active parts with attack-over parts, the designed triggered strategies, if designed well according to the actual system needs, can tolerate (be resilient to) the Pp-DoS attacks and stochastic network delays without jeopardizing the stability and Zeno-freeness, which is verified by the robust global attitude stabilization of flexible combined ro

关键词： Networked control systems

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Extended NNs-Based Adaptive Event-Triggered Asymptotic control for Nonlinear systems Against Actuator Faults

Extended NNs-Based Adaptive Event-Triggered Asymptotic Contr...

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International Symposium on Autonomous systems (ISAS)

作者： Shanlin Liu Yingwei Zhang Xudong Zhao Hesheng Wang College of Information Science and Engineering Northeastern University Shenyang China State Laboratory of Synthesis Automation of Process Industry Northeastern University Shenyang China Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of IntelligentControl and Management Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350363173

ISBN: (纸本)9798350363180

In this article, an adaptive event-triggered asymp¬totically fault-tolerant control (FTC) issue for nonlinear systems with actuator faults is investigated. An extended neural networks (NNs) technique is introduced to estimate unknown functions of the system under consideration. Compared with traditional NNs that ignore approximation errors, the proposed extended NNs further processes approximation errors, reducing the conservatism of the proposed algorithm. Then, within the framework of backstepping method, a new adaptive control strategy is developed by combining event-triggered mechanism (ETM) and bound estimation (BE) approach, which ensures the asymptotic convergence of system states while also reducing the transmission of unnecessary information, thus improving the utilization of communication resources. At the same time, the designed controller eliminates the adverse effects of actuator failures and system nonlinear terms. Finally, a simulation example of a single-link robot system is provided to demonstrate that the developed control strategy can ensure that all signals are bounded and system states are asymptotically convergent.

关键词： Actuators Backstepping Fault tolerant systems Process control Artificial neural networks control systems Approximation error

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Dynamic Event-Triggered Consensus on Matrix-Weighted Networks: Leadless Case

Dynamic Event-Triggered Consensus on Matrix-Weighted Network...

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Chinese control Conference (CCC)

作者： Lintao Dou Haoyu Wei Jian Huang Lulu Pan Haibin Shao Dewei Li College of Intelligent Science National University of Defense Technology Changsha China Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China and Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

This paper examines the event-triggered consensus of the multi-agent system on matrix-weighted networks, where the interdependencies among higher-dimensional states of neighboring agents are characterized by matrix-weighted edges in the network. Specifically, a novel distributed dynamic event-triggered coordination strategy is proposed for this category of generalized networks, in which an auxiliary system is employed for each agent to dynamically adjust the triggering threshold, which plays an essential role in guaranteeing that the triggering time sequence does not exhibit Zeno behavior. Distributed event-triggered control protocols are proposed to guarantee leaderless consensus for multi-agent systems on matrix-weighted networks, respectively. Remarkably, the spectrum of matrix-valued weights is crucial in event-triggered mechanism design for matrix-weighted networks, generalizing those results only applicable for scalar-weighted networks. The proposed approach allows each agent to broadcast and receive information only at its triggering instants. Finally, simulation examples are provided to demonstrate the theoretical results.

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3D Scene Flow Estimation on Pseudo-LiDAR: Bridging the Gap on Estimating Point Motion

arXiv

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arXiv 2022年

作者： Jiang, Chaokang Wang, Guangming Miao, Yanzi Wang, Hesheng Engineering Research Center of Intelligent Control for Underground Space Ministry of Education School of Information and Control Engineering Advanced Robotics Research Center China University of Mining and Technology Xuzhou221116 China Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China

3D scene flow characterizes how the points at the current time flow to the next time in the 3D Euclidean space, which possesses the capacity to infer autonomously the non-rigid motion of all objects in the scene. The previous methods for estimating scene flow from images have limitations, which split the holistic nature of 3D scene flow by estimating optical flow and disparity separately. Learning 3D scene flow from point clouds also faces the difficulties of the gap between synthesized and real data and the sparsity of LiDAR point clouds. In this paper, the generated dense depth map is utilized to obtain explicit 3D coordinates, which achieves direct learning of 3D scene flow from 2D images. The stability of the predicted scene flow is improved by introducing the dense nature of 2D pixels into the 3D space. Outliers in the generated 3D point cloud are removed by statistical methods to weaken the impact of noisy points on the 3D scene flow estimation task. Disparity consistency loss is proposed to achieve more effective unsupervised learning of 3D scene flow. The proposed method of self-supervised learning of 3D scene flow on real-world images is compared with a variety of methods for learning on the synthesized dataset and learning on LiDAR point clouds. The comparisons of multiple scene flow metrics are shown to demonstrate the effectiveness and superiority of introducing pseudo-LiDAR point cloud to scene flow estimation. © 2022, CC BY.

关键词： Three dimensional computer graphics

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Adaptive Enhancement Technology for Screen Content Photos 17th

Adaptive Enhancement Technology for Screen Content Photos

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17th International Forum on Digital TV and Wireless Multimedia Communication, IFTC 2020

作者： Zhou, Yazhen Kyefondeme, Dakurah Collins Zhou, Huayi Zhao, Min Guo, Nan Wu, Li Faculty of Information Technology Beijing University of Technology Beijing China Key Laboratory of Artificial Intelligence Ministry of Education Shanghai China Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China Beijing Artificial Intelligence Institute Beijing China

ISBN: (纸本)9789811611933

Recent years have witnessed the widespread applications of mobiles and other portable electronic devices, involving a variety of screen content photos. Different from natural scene photos, screen content photos are composed of more lines, fewer colors and unique text messages. Thus, it is difficult to realize the satisfactory enhancement effect of screen content photos using traditional image enhancement technology since they are designed for the natural scene. In this paper, we develop a novel enhancement model for screen content photos by considering text and picture separately. To be specific, we first use a fully convolutional network to divide a screen content photo into three independent parts: picture region, foreground text region, and background. Second, an optimal modification of histogram is used to automatically enhance the picture region’s contrast, and the guided image filter is used to enhance the foreground text region. Third, the enhanced picture region, the enhanced foreground text region, and background are fused to obtain the final enhanced image. Experimental results show that our model has produced less noise and derived outstanding enhancement effect than the popular enhancement techniques. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Image segmentation

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Probabilistic Planning of Transmission Network Considering Operational Flexibility of Power system

Probabilistic Planning of Transmission Network Considering O...

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Smart Power & Internet Energy systems (SPIES), International Conference on

作者： Jianjie Li Ping Li Peng Li Junshao Guo Mingqiang Wang Binzhou Electric Company Binzhou China Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan China

The uncertainties about equipment failure will bring great challenges to the operation of transmission network. Therefore, it is important for transmission network to possess sufficient flexibility to accommodate the fluctuation of load and deal with unit failures. This paper proposes a probabilistic planning model of transmission network considering operational flexibility, which makes decision-making optimization for transmission network planning and reduces the influence of uncertainties about equipment failure. Moreover, the proposed model introduces the probability and expectation of up-flexibility-not-supplied (UFNS) and expected-energy-not-supplied (EENS), then uses penalty cost to quantify them, which enhances the reliability and economy of transmission network planning. Furthermore, the absolute value linearization method is used to linearize the expectation of UFNS and EENS, which greatly improves the calculation efficiency. The proposed model is solved using the CPLEX solver in General Algebraic Modeling system (GAMS). The practicality of model is verified by the IEEE-RTS system.

关键词： Uncertainty Fluctuations Probabilistic logic Software Planning Power system reliability Software reliability

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Synchronization Stability of PLL-Based Power Converters Connected to Weak AC Grid 6

Synchronization Stability of PLL-Based Power Converters Conn...

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6th Asia Conference on Power and Electrical Engineering, ACPEE 2021

作者： Mei, Limin Ding, Lei Wang, Zhihao Cai, Deyu Ding, Ran Wang, Jingran Xu, Haixiang Shandong University Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Jinan China State Grid Jibei Electric Power Company Limited Electric Power Dispatching and Control Center Beijing China

ISBN: (纸本)9781728191591

In this paper, the synchronization stability of converter system based on the phase-locked loop (PLL) is studied, especially when it is connected to a weak AC grid. First, the small signal model considered PLL, power control, current control and voltage feedforward (VFF) control is built. The open-loop transfer function can analyze the stability of the system but hides the dynamic of PLL. So the conjugated circuit is proposed, which describes the dynamics of PLL and the other part separately. Based on the Bode diagrams, we explore how the grid impedance and converter controller parameters influence the stability of the system. In order to verify the analysis results, simulations are conducted in MATLAB/Simulink. © 2021 IEEE.

关键词： Phase locked loops

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Slewing control of Overhead Crane Based on State-enhance Coupling Method

Slewing Control of Overhead Crane Based on State-enhance Cou...

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第43届中国控制会议

作者： Rui Liu Biao Lu Jinyang Dong Weili Ding The 6th Research Institute of China Electronic Corporation Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Engineering Research Center of Intelligent Control System and Intelligent Equipment Ministry of Education Yanshan University National Key Laboratory of Key Technologies for Lifting Machinery Yanshan University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Cranes which are frequently utilized as sizable machinery, are widely used across a range of settings, including warehouses, distribution hubs, harbors, steel plants, and manufacturing facilities. However, the current researches on cranes have paid insufficient attention to the rotation of loads during transportation. Additionally, some of the proposed control methods fail to effectively integrate information from both actuated DOFs(degrees of freedom) and unactuated DOFs, leading to a loss of controller robustness. In this paper, we establish an overhead crane model with a slewing mechanism, focusing on the analysis of crane's lifting and rotating motion. Based on that, a nonlinear controller is proposed for load slewing control. The stability of the controller is proven using Lyapunov techniques and LaSalle's invariance theorem. The effectiveness and robustness of the controller are validated through numerical simulations.

关键词： Load Rotation Nonlinear controller Robustness

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