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Stability and Stabilization of Sampled-Data Based LFC for Power Systems:A Data-Driven Method

IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 291-293页

作者： Yu-Long Fan Chuan-Ke Zhang Yong He the School of Automation China University of Geosciences the Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems the Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education IEEE

Dear Editor,This letter is concerned with stability analysis and stabilization design for sampled-data based load frequency control(LFC) systems via a data-driven method. By describing the dynamic behavior of LFC systems based on a data-based representation, a stability criterion is derived to obtain the admissible maximum sampling interval(MSI) for a given controller and a design condition of the PI-type controller is further developed to meet the required MSI. Finally, the effectiveness of the proposed methods is verified by a case study.

关键词： Sampled data control systems

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Broad-Learning-System-Based Model-Free Adaptive Predictive control for Nonlinear MASs Under DoS Attacks

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IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 381-393页

作者： Hongxing Xiong Guangdeng Chen Hongru Ren Hongyi Li the School of Automation Guangdong-Hong Kong Joint Laboratory for Intelligent Decision and Cooperative Control Guangdong University of Technology Guangdong Provincial Key Laboratory for Intelligent Decision and Cooperative Control Guangdong University of Technology the College of Electronic and Information Engineering Southwest University IEEE

In this paper, the containment control problem in nonlinear multi-agent systems(NMASs) under denial-of-service(DoS) attacks is addressed. Firstly, a prediction model is obtained using the broad learning technique to train historical data generated by the system offline without DoS attacks. Secondly, the dynamic linearization method is used to obtain the equivalent linearization model of NMASs. Then, a novel model-free adaptive predictive control(MFAPC) framework based on historical and online data generated by the system is proposed, which combines the trained prediction model with the model-free adaptive control method. The development of the MFAPC method motivates a much simpler robust predictive control solution that is convenient to use in the case of DoS attacks. Meanwhile, the MFAPC algorithm provides a unified predictive framework for solving consensus tracking and containment control problems. The boundedness of the containment error can be proven by using the contraction mapping principle and the mathematical induction method. Finally, the proposed MFAPC is assessed through comparative experiments.

关键词： Broad learning technique denial-of-service (DoS) model-free adaptive predictive control (MFAPC) nonlinear multi-agent systems (NMASs)

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A nonlinear hysteresis compensation control of hydro-viscous drive in air transport operations

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Chinese Journal of Aeronautics 2025年第2期38卷 161-174页

作者： Liang WANG Jianjian LIANG Lin ZHANG Shoukun WANG Junzheng WANG School of Automation and Software Shanxi UniversityTaiyuan 030031China Key Laboratory of Autonomous Intelligent Unmanned Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China

The Hydro-Viscous Drive(HVD)speed regulating system finds extensive application in air transport transmission systems to regulate the stepless speed or conduct overload ***,its intrinsic hysteretic behaviors,such as the asymmetric hysteretic and dead zone,could introduce inaccuracy and delay in control applications,posing challenges to system *** paper investigates a Nonlinear Hysteresis Compensation control(NHCC)that consists of two parts to control the HVD output speed by operating the valve under different engine operating *** the first part,the Inverse Hysteresis Compensator(IHC)based on major loop data is introduced for the asymmetric hysteresis characterization and compensation of the HVD speed control system of the power generation and distribution,which aims to reduce the hysteresis and dead zone effect and expand the effective input *** the second part,the Active Disturbance Rejection controller(ADRC)is employed to mitigate the hysteresis effects of the compensated system and remove the steady-state error,which allows real-time compensation of the estimated perturbations as state feedback to achieve the required *** experimental laboratory station has been fabricated to evaluate the proposed *** test results show that the NHCC method can regulate the fan speed to the desired value(45 r/min at steady state)and broaden the effective input range to the full range under different engine ***,the proposed control method can reduce the non-linearity of the input and output curves(from 18%to 4%)and compensate for the asymmetric hysteresis(from 38%to 5%).

关键词： Hydro-viscous drive Nonlinear hysteresis compensation Inverse hysteresis compensation Speed regulating system ADRC

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Event-based non-fragile state estimation for time-varying systems under deception attacks

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Science China(Information Sciences) 2025年第4期68卷 349-362页

作者： Xiao-Meng LI Tao ZOU Renquan LU Zhijia ZHAO School of Mechanical and Electrical Engineering Guangzhou University School of Automation Guangdong Hong Kong Joint Laboratory for Intelligent Decision and Cooperative ControlGuangdong University of Technology

This paper addresses the challenge of dynamic event-based non-fragile state estimation for discrete time-varying systems under deception attacks. These attacks involve injecting deceptive signals into the communication channel, which can consume limited network resources and disrupt system estimation tasks. To tackle this issue, the study introduces a comprehensive and realistic deception attack model that accounts for the various hard physical constraints. To mitigate the influence of these attacks and reduce communication demands, a dynamic event-triggered scheme that uses dynamic threshold parameters is developed. The main purpose of the addressed problem is to design an event-based non-fragile estimator that ensures the estimation error systems meet the H∞performance constraint over a finite horizon. The paper provides two key criteria to ensure the existence of the proposed estimator, leveraging stochastic analysis techniques. The desired estimator gains are determined using a recursive process of solving matrix inequalities. Finally, a numerical example illustrates the effectiveness of the developed event-based non-fragile estimator design method.

关键词： discrete time-varying systems deception attacks dynamic event-triggered mechanism finite horizon non-fragile estimation

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Geometric size and forming force prediction in incremental flanging:A new analytical model

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Chinese Journal of Aeronautics 2025年第2期38卷 519-540页

作者： Chong TIAN Dawei ZHANG Guangcan YANG Shengdun ZHAO Xi’an Key Laboratory of Intelligent Equipment and Control School of Mechanical EngineeringXi’an Jiaotong UniversityXi’an 710049China

A new analytical model for geometric size and forming force prediction in incremental flanging(IF)is presented in this *** complex deformation characteristics of IF are considered in the modeling process,which can accurately describe the strain and stress states in *** on strain analysis,the model can predict the material thickness distribution and neck height after *** considering contact area,strain characteristics,material thickness changes,and friction,the model can predict specific moments and corresponding values of maximum axial forming force and maximum horizontal forming force during *** addition,an IF experiment involving different tool diameters,flanging diameters,and opening hole diameters is *** the basis of the experimental strain paths,the strain characteristics of different deformation zones are studied,and the stable strain ratio is quantitatively described through two dimensionless parameters:relative tool diameter and relative hole ***,the changing of material thickness and forming force in IF,and the variation of minimum material thickness,neck height,maximum axial forming force,and maximum horizontal forming force with flanging parameters are studied,and the reliability of the analytical model is verified in this ***,the influence of the horizontal forming force on the tool design and the fluctuation of the forming force are explained.

关键词： Incremental flanging Analytical model Strain characteristic Geometric size Forming force

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Attitude control of flexible satellite via three-dimensional magnetically suspended wheel

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Applied Mathematics and Mechanics(English Edition) 2025年第3期46卷 555-572页

作者： J.TAYEBI Yingjie CHEN Ti CHEN Shiyuan JIA State Key Laboratory of Mechanics and Control for Aerospace Structures Nanjing University of Aeronautics and AstronauticsNanjing 210016China School of Intelligent Engineering and Automation Beijing University of Posts and TelecommunicationsBeijing 100876China

This paper proposes an attitude control strategy for a flexible satellite equipped with an orthogonal cluster of three-dimensional(3D)magnetically suspended wheels(MSWs).The mathematical model for the satellite incorporating flexible appendages and an orthogonal cluster of magnetically suspended reaction wheel actuators is initially *** that,an adaptive attitude controller is designed with a switching surface of variable structure,an adaptive law for estimating inertia matrix uncertainty,and a fuzzy disturbance observer for estimating disturbance ***,a Moore-Penrose-based steering law is proposed to derive the tilt angle commands of the orthogonal configuration of the 3D MSW to follow the designed control ***,numerical simulations are presented to validate the effectiveness of the proposed control strategy.

关键词： flexible satellite three-dimensional(3D)magnetically suspended wheel(MSW) attitude control adaptive control disturbance observer

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Neural-based prescribed-time consensus control for multiagent systems via dynamic memory event-triggered mechanism

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Science China(Technological Sciences) 2025年第3期68卷 217-227页

作者： Xiaohong ZHENG Hui MA Qi ZHOU Hongyi LI School of Automation Guangdong-Hong Kong Joint Laboratory for Intelligent Decision and Cooperative Controland Guangdong Provincial Key Laboratory for Intelligent Decision and Cooperative ControlGuangdong University of TechnologyGuangzhou510006China School of Mathematics and Statistics Guangdong University of TechnologyGuangzhou510006China College of Electronic and Information Engineering and the Chongqing Key Laboratory of Generic Technology and System of Service Robots Southwest UniversityChongqing400715China

This work investigates the implementation of distributed prescribed-time neural network(NN)control for nonlinear multiagent systems(MASs)using a dynamic memory event-triggered mechanism(DMETM).First,it introduces a composite learning technique in NN *** method leverages the prediction error within the NN update law to enhance the accuracy of the unknown nonlinearity ***,by introducing a time-varying transformation,the study establishes a distributed prescribed-time control *** notable feature of this algorithm is its ability to predetermine the convergence time independently of initial conditions or control ***,the DMETM is established to reduce the actuation frequency of the *** the conventional memoryless dynamic event-triggered mechanism,the DMETM incorporates a memory term to further increase triggering *** a distributed estimator for the leader,the DMETM-based NN prescribed-time controller is designed in a fully distributed manner,which guarantees that all signals in the closed-loop system remain bounded within the prescribed ***,simulation results are presented to validate the effectiveness of the proposed algorithm.

关键词： consensus control composite learning control dynamic memory event-triggered control prescribed-time control multiagent systems(MASs)

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Attention-Modulated Feature Fusion Neural Network for Inverse Modeling of Microwave Filters

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IEEE Microwave and Wireless Technology Letters 2025年第4期35卷 376-379页

作者： Guo, Linwei Cao, Weihua Hu, Wenkai Lu, Zhengyang Wu, Min China University of Geosciences School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

Inverse modeling is extensively applied in the design and tuning of microwave filters (MFs). Inverse models (IMs) take the features extracted from the high-dimensional electromagnetic parameters as input. How to make full use of features from multiple perspective is a critical issue for improving model accuracy. To solve it, this letter proposes an attention-modulated feature fusion neural network (AMFFNN). AMFFNN achieves multiperspective feature fusion (MPFF) at the input side and independent feature fusion (IFF) at the output side. In addition, feature fusion in AMFFNN is enhanced by attention modules to dynamically identify the importance of each feature. Statistical and comparative results of simulations demonstrate that AMFFNN outperforms existing methods in terms of accuracy, stability, and generalization. © 2023 IEEE.

关键词： Inverse problems

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A zeroth-order stochastic implicit method for bilevel-structured actor-critic schemes

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Science China(Information Sciences) 2025年第5期68卷 53-71页

作者： Haochen TAO Shisheng CUI Zhuo LI Jian SUN School of Automation Beijing Institute of Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems School of AutomationBeijing Institute of Technology Beijing Institute of Technology Chongqing Innovation Center

Reinforcement learning algorithms are central to the cognition and decision-making of embodied intelligent agents. A bilevel optimization(BO) modeling approach, along with a host of efficient BO algorithms, has been proven to be an effective means of addressing actor-critic(AC) policy optimization problems. In this work, based on a bilevelstructured AC problem model, an implicit zeroth-order stochastic algorithm is developed. A locally randomized spherical smoothing technique, which can be applied to nonsmooth nonconvex implicit AC formulations and avoid the closed-form lower-level mapping, is introduced. In the proposed zeroth-order scheme, the gradient of the implicit function can be approximated through inexact lower-level value estimations that are practically available. Under suitable assumptions,the algorithmic framework designed for the bilevel AC method is characterized by convergence guarantees under a fixed stepsize and smoothing parameter. Moreover, the proposed algorithm is equipped with the overall iteration complexity of O(n2L20 L20?-1). The convergence performance of the proposed algorithm is verified through numerical simulations.

关键词： actor-critic bilevel optimization zeroth-order algorithm implicit programming stochastic approximation

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Surface-PMSM Sensorless control Strategy Based on Reduced-Order Linear Kalman Filter Cooperating with Prediction Error Rolling Compensation

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IEEE Transactions on Power Electronics 2025年第8期40卷 10804-10815页

作者： Xu, Sang Shen, Anwen Tang, Qipeng Wang, Miaomiao Luo, Pan Luo, Xin Xu, Jinbang National Key Laboratory of Science and Technology on Multispectral Information Processing Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Wuhan430074 China Science and Technology on Reactor System Design Technology Laboratory Chengdu China

Kalman filter (KF) is increasingly attracted for sensorless control of surface permanent magnet synchronous motors (SPMSMs) due to its strong robustness against measurement and system noise. However, conventional method suffers from poor position and speed estimation accuracy under dynamic conditions, and high computational cost. In order to solve these problems, an enhanced sensorless control strategy based on reduced-order linear Kalman filter (RLKF) cooperating with prediction error rolling compensation is introduced in this paper. Differing from conventional method, a reduced-order linear state equation encompassing rotor position, speed and torque disturbance is constructed. Then, by obtaining the prediction error of system output using the motor current equation in the predictive reference frame, the optimal estimation of rotor position and speed in KF algorithm is achieved based on the reduced-order model. This not only simplifies the calculation process, but also enhances the position and speed estimation accuracy under dynamic conditions. Meanwhile, a prediction error rolling compensation algorithm is developed to minimize the estimation deviations caused by motor parameters variations. Additionally, the system's dynamic performance is further improved with an adopted speed controller based on torque disturbance feedforward and acceleration feedback. Finally, experimental results verify the effectiveness and feasibility of the proposed strategy.1 © 1986-2012 IEEE.

关键词： Permanent magnets

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