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Control valve simulation method integrable into the global gradient algorithm

ISH Journal of Hydraulic Engineering 2025年第1期31卷 1-7页

作者： Sivakumar, P. Gorev, N.B. Gorev, V.N. Kodzhespirova, I.F. Shedlovsky, I.A. Itanagar India Department for Functional Elements of Control Systems Institute of Technical Mechanics Dnipro Ukraine Department of Physics Dnipro University of Technology Dnipro Ukraine Department of Automation and Computer Systems Dnipro University of Technology Dnipro Ukraine

This paper presents a refinement of a method that simulates flow- and pressure-regulating valves by replacing them with pipes and adjusting the resistances (diameters) of those pipes to meet the valve settings. The method, referred to as the replacing pipe method (RPM), is readily integrable into the global gradient algorithm, which is the heart of the commonly used EPANET 2 water distribution system modeling software. The RPM proved to be more robust, yet slower than the EPANET 2 valve handling heuristics. In this work, the RPM was modified to increase its computational speed. The modification involved the RPM check valve handling algorithm and condition for updating the diameters of the valve-replacing pipes. The modified RPM was tested as part of a hybrid simulator, which switches from the EPANET 2 valve handling heuristics to the RPM when the former fails. The test networks included a large network with thousands of nodes, pipes, and valves, and a case of an ill-posed problem. As the testing showed, the modified RPM offers a significant reduction in the number of iterations compared to its previous version. © 2024 Indian Society for Hydraulics.

关键词： Safety valves

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Chattering-Free Fault-Tolerant Cluster Control and Fault Direction Identification for HIL UAV Swarm With Pre-Specified Performance

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 183-197页

作者： Pei-Ming Liu Xiang-Gui Guo Jian-Liang Wang Daniel Coutinho Lihua Xie the Beijing Engineering Research Center of Industrial Spectrum Imaging School of Automation and Electrical Engineering University of Science and Technology Beijing the Shunde Graduate School of University of Science and Technology Beijing IEEE Autonomous Intelligent Systems Department Hangzhou Innovation Institute of Beihang University the Department of Automation and Systems Universidade Federal de Santa Catarina the School of Electrical and Electronic Engineering Nanyang Technological University

In this paper, the problem of pre-specified performance fault-tolerant cluster consensus control and fault direction identification is solved for the human-in-the-loop(HIL) swarm unmanned aerial vehicles(UAVs) in the presence of possible nonidentical and unknown direction faults(NUDFs) in the yaw *** control strategy begins with the design of a pre-specified performance event-triggered observer for each individual *** observers estimate the outputs of the human controlled UAVs, and simultaneously achieve the distributed design of actual control signals as well as cluster consensus of the observer *** is worth mentioning that these observers require neither the high-order derivatives of the human controlled UAVs' output nor a priori knowledge of the initial conditions. The fault-tolerant controller realizes the pre-specified performance output regulation through error transformation and the Nussbaum function. It should be pointed out that there are no chattering caused by the jump of the Nussbaum function when a reverse fault occurs. In addition, to provide a basis for further solving the problem of physical malfunctions, a fault direction identification algorithm is proposed to accurately identify whether a reverse fault has occurred. Simulation results verify the effectiveness of the proposed control and fault direction identification strategies when the reverse faults occur.

关键词： Chattering-free cluster consensus fault direction identification human-in-the-loop (HIL) nonidentical and unknown direction faults (NUDFs) pre-specified performance swarm unmanned aerial vehicles (UAVs)

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Data-driven output regulation control for constrained linear systems

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Science China(Information Sciences) 2025年第3期68卷 338-353页

作者： Chaoyu XIA Yi DONG Chaoli WANG Shengyuan XU Shanghai Research Institute for Intelligent Autonomous Systems Tongji University College of Electronic and Information Engineering Shanghai Research Institute for Intelligent Autonomous SystemsTongji University Department of Control Science and Engineering School of Optical-Electrical and Computer EngineeringUniversity of Shanghai for Science and Technology Department of Automation Nanjing University of Science and Technology

This study introduces a data-driven approach for state and output feedback control addressing the constrained output regulation problem in unknown linear discrete-time systems. Our method ensures effective tracking performance while satisfying the state and input constraints, even when system matrices are not available. We first establish a sufficient condition necessary for the existence of a solution pair to the regulator equation and propose a data-based approach to obtain the feedforward and feedback control gains for state feedback control using linear programming. Furthermore, we design a refined Luenberger observer to accurately estimate the system state, while keeping the estimation error within a predefined set. By combining output regulation theory, we develop an output feedback control strategy. The stability of the closed-loop system is rigorously proved to be asymptotically stable by further leveraging the concept of λ-contractive sets.

关键词： output regulation constrained system data-driven.

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Data-Driven Fault-Tolerant Bipartite Consensus Tracking for Multi-Agent systems With a Non-Autonomous Leader

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 279-281页

作者： Yan Zhou Guanghui Wen Jialing Zhou Tao Yang the Department of Systems Science Southeast University the State Key Laboratory of CNS/ATM Beijing Institute of Technology the Beijing Institute of Technology (Zhuhai) the State Key Laboratory of Synthetical Automation for Process Industries Northeastern University

Dear Editor,This letter studies the bipartite consensus tracking problem for heterogeneous multi-agent systems with actuator faults and a leader's unknown time-varying control input. To handle such a problem, the continuous fault-tolerant control protocol via observer design is developed. In addition, it is strictly proved that the multi-agent system driven by the designed controllers can still achieve bipartite consensus tracking after faults occur.

关键词： Time varying control systems

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Predefined-Time Distributed Fault-Tolerant Control for Nonlinear Multiagent systems Suffering From Nonaffine Faults

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IEEE Transactions on systems, Man, and Cybernetics: systems 2025年第5期55卷 3300-3311页

作者： Cheng, Shuai Xin, Bin Chen, Jie Deng, Fang Qingdao University School of Automation Qingdao266071 China Beijing Institute of Technology School of Automation Beijing100081 China Beijing Institute of Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Beijing100081 China Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Department of Control Science and Engineering Shanghai200092 China

This article investigates the distributed predefined-time (PT) fault-tolerant control for nonlinear multiagent systems (NNMSs) with nonaffine faults. A novel distributed PT control scheme is proposed based on a new PT theorem. The switching functions are introduced into distributed control signals to avoid the singularity problem. The second-order filter technology is designed to solve "explosion of complexity" issues. The newly designed PT compensation signals are utilized to eliminate filter errors. The proposed distributed PT controller based on local information can guarantee that all signals of the closed-loop system are PT bounded, and consensus errors of NNMSs can be enforced to a small region around the origin within a predefined time. Compared with the finite/fixed time, the predefined time is an exact value given in advance, which remains constant regardless of initial states and control parameters. Finally, two comparative simulations are provided to demonstrate the presented strategy. © 2013 IEEE.

关键词： Adaptive control systems

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A Diffusion Model for Traffic Data Imputation

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IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 606-617页

作者： Bo Lu Qinghai Miao Yahui Liu Tariku Sinshaw Tamir Hongxia Zhao Xiqiao Zhang Yisheng Lv Fei-Yue Wang the School of Artificial Intelligence University of Chinese Academy of Sciences Baidu Inc. IEEE the State Key Laboratory for Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Meituan Guangdong University of Technology the Department of Transportation Engineering School of Transportation Science and Technology Harbin Institute of Technology

Imputation of missing data has long been an important topic and an essential application for intelligent transportation systems(ITS) in the real world. As a state-of-the-art generative model, the diffusion model has proven highly successful in image generation, speech generation, time series modelling *** now opens a new avenue for traffic data imputation. In this paper, we propose a conditional diffusion model, called the implicit-explicit diffusion model, for traffic data imputation. This model exploits both the implicit and explicit feature of the data simultaneously. More specifically, we design two types of feature extraction modules, one to capture the implicit dependencies hidden in the raw data at multiple time scales and the other to obtain the long-term temporal dependencies of the time series. This approach not only inherits the advantages of the diffusion model for estimating missing data, but also takes into account the multiscale correlation inherent in traffic data. To illustrate the performance of the model, extensive experiments are conducted on three real-world time series datasets using different missing *** experimental results demonstrate that the model improves imputation accuracy and generalization capability.

关键词： Data imputation diffusion model implicit feature time series traffic data

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Fast Coordinated Power Control for Improving Inertial and Voltage Support Capability of Battery Energy Storage systems

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CSEE Journal of Power and Energy systems 2025年第1期11卷 280-295页

作者： Zhen Gong Chengxi Liu Filipe Faria Da Silva Yonghao Gui Claus Leth Bak School of Electrical Engineering and Automation Wuhan UniversityWuhan430072China Department of Energy Technology Aalborg University9220 AalborgDemark Department of Electronic Systems Aalborg University9220 AalborgDenmark

This paper proposes a fast coordinated power control method based on two augmented channels(AC)in battery energy storage system(BESS)to improve inertial and voltage support capability,i.e.,a frequency-reactive power channel(FRPC)and a voltage-real power channel(VRPC).For frequency control in the power distribution system with high resistance/inductance ratio,the coupling mechanism between rate of change of frequency(RoCoF)and required reactive power(RRP)of grids is analyzed,indicating RoCoF is proportional to ***,RoCoF is utilized in FRPC to generate reactive power for complementary inertial emulating ***,for voltage control,coupling characteristics between rate of change of voltage(RoCoV)and demanding real power(DRP)of grids is also studied,revealing RoCoV is proportional to ***,it can be adopted in VRPC to generate real power for complementary voltage ***,grid-voltage-modulated direct power control is selected as the inner power control loop to track power references with faster dynamic performance compared with traditional vector-oriented ***,simulations and hardware-in-loop experiments validate improvement in performance of grid frequency and voltage control based on the proposed method.

关键词： Augmented channels direct power control frequency-reactive power channel(FRPC) inertial and voltage support voltage-real power channel(VRPC)

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Deep Reinforcement Learning-Assisted Robust Cubature Kalman Filter for Power System Dynamic State Estimation With Multi-Rate Measurements

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IEEE Transactions on automation Science and Engineering 2025年 22卷 14346-14357页

作者： Gu, Haoli Liu, Shichao Chen, Bo Wang, Rusheng Yu, Li Kaynak, Okyay Zhejiang University of Technology Department of Automation Hangzhou310023 China Zhejiang Key Laboratory of Intelligent Perception and Control for Complex Systems Hangzhou310023 China Ningbo University of Technology Ningbo315201 China Bogazici University Istanbul34342 Turkey

The coexistence of high-frequency phasor measurement units (PMUs) and conventional SCADA systems raises the challenge of heterogenous-source and multi-rate measurements which significantly degrades the performance of power system dynamic state estimation. In this work, a deep reinforcement learning (DRL) assisted robust cubature Kalman filtering (CKF) scheme is proposed to handle measurements from hybrid sources and with different time scales. In specific, a multi-rate measurement function reconstruction approach is designed with an independent discretization mechanism to lift the present limitation of requiring an integer multiple relationship of the sampling rates from multiple sources in most of existing works. Embedded with this discretization mechanism, a deep reinforcement learning assisted two-parameter linear exponential smoothing method is proposed to reconstruct the slow measurement model with online adjustable estimation parameters. A generalized correntropy loss criterion is also included in the robust CKF to counter the non-Gaussian noise and the noise distribution variation caused by the reconstruction. Comparisons results demonstrate that the proposed DRL-based robust CKF method can achieve better accuracy and robustness under various operating scenarios. © 2004-2012 IEEE.

关键词： Deep reinforcement learning

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An autonomous dynamic recovery technology for autonomous underwater vehicles based on unmanned surface vehicles

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Science China(Technological Sciences) 2025年第2期68卷 315-317页

作者： Yueying WANG Yiqi SHI Guanghui WEN Huaicheng YAN School of Mechatronic Engineering and Automation Shanghai UniversityShanghai 200444China Department of Systems Science School of MathematicsSoutheast UniversityNanjing 210096China School of Information Science and Engineering East China University of Science and TechnologyShanghai 200237China

Autonomous underwater vehicles(AUVs) have attracted considerable attention due to their vast potential applications, such as offshore oil exploration, underwater rescue, military reconnaissance, and marine scientific ... 详细信息

关键词： underwater autonomous battery

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PPLIO: Plane-to-Plane LiDAR-Inertial Odometry with Multi-view Constraint in Real-time

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IEEE Access 2025年 13卷 76185-76197页

作者： Lee, Hanyeol Jung, Jae Hyung Chung, Won Young Lee, Suyong Park, Chan Gook Seoul Natioinal University Department of Aerospace Engineering Automation and Systems Research Institute Seoul08826 Korea Republic of Technical University of Munich Smart Robotics Lab School of Computation Information and Technology Germany Samsung Electronics Global Technology Research Korea Republic of

Recent feature-based LiDAR-inertial odometry (LIO) algorithms mainly adopt a point-to-plane model, which requires complex association between numerous feature points and planes. Since these methods only use distance as a parameter to associate feature points, they are prone to a mismatch of features in the presence of initial errors. In this study, we propose a LIO system based on a plane-to-plane model with a sliding window, named PPLIO. To extract high-quality plane features, the geometric and statistical properties are utilized and robust data association is performed with two parameters from the plane basis: distance and normal vector. In the state estimator part, we design two plane-to-plane measurement models using the plane features including the proposed plane RANSAC for outlier rejection. Each measurement model is formulated in the multi-state constraint Kalman filter framework for accurate estimation. For detailed verification, we conduct the Monte-Carlo simulation to evaluate the feature accuracy and the data association. In addition, we perform comparative evaluation against state-of-the-art LIO/LIO-mapping algorithms on both indoor and outdoor experiments, and present results that PPLIO outperforms other real-time algorithms in localization performance with detailed analysis. © 2013 IEEE.

关键词： Monte Carlo methods

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