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

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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Constrained Moving Path Following control for UAV With Robust control Barrier Function

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IEEE/CAA Journal of Automatica Sinica 2023年第7期10卷 1557-1570页

作者： Zewei Zheng Jiazhe Li Zhiyuan Guan Zongyu Zuo Seventh Research Division School of Automation Science and Electrical EngineeringBeihang UniversityBeijing 100191 Beijing Institute of Control Engineering Beijing 100094China

This paper studies the moving path following(MPF)problem for fixed-wing unmanned aerial vehicle(UAV)under output constraints and wind *** vehicle is required to converge to a reference path moving with respect to the inertial frame,while the path following error is not expected to violate the predefined *** from existing moving path following guidance laws,the proposed method removes complex geometric transformation by formulating the moving path following problem into a second-order time-varying control problem.A nominal moving path following guidance law is designed with disturbances and their derivatives estimated by high-order disturbance *** guarantee that the path following error will not exceed the prescribed bounds,a robust control barrier function is developed and incorporated into controller design with quadratic program based *** proposed method does not require the initial position of the UAV to be within predefined *** the safety margin concept makes error-constraint be respected even if in a noisy *** proposed guidance law is validated through numerical simulations of shipboard landing and hardware-in-theloop(HIL)experiments.

关键词： Moving path following(MPF) robust control barrier function safety margin shipboard landing unmanned aerial vehicle(UAV)

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Enhanced Tube-Based Event-Triggered Stochastic Model Predictive control With Additive Uncertainties

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IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 596-605页

作者： Chenxi Gu Xinli Wang Kang Li Xiaohong Yin Shaoyuan Li Lei Wang the School of Control Science and Engineering Shandong University IEEE the School of Electronic and Electrical Engineering University of Leeds the Qingdao University of Science and Technology the Department of Automation Shanghai Jiao Tong University the Key Laboratory of System Control and Information Processing Ministry of Education of China

This paper proposes an event-triggered stochastic model predictive control for discrete-time linear time-invariant(LTI) systems under additive stochastic disturbances. It first constructs a probabilistic invariant set and a probabilistic reachable set based on the priori knowledge of system *** with enhanced robust tubes, the chance constraints are then formulated into a deterministic form. To alleviate the online computational burden, a novel event-triggered stochastic model predictive control is developed, where the triggering condition is designed based on the past and future optimal trajectory tracking errors in order to achieve a good trade-off between system resource utilization and control performance. Two triggering parameters σ and γ are used to adjust the frequency of solving the optimization problem. The probabilistic feasibility and stability of the system under the event-triggered mechanism are also examined. Finally, numerical studies on the control of a heating, ventilation, and air conditioning(HVAC) system confirm the efficacy of the proposed control.

关键词： Event-triggered mechanism heating, ventilation, and air conditioning (HVAC) control probabilistic reachable set stochastic model predictive control

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State Transition Modeling Method for Optimal Dispatching for Integrated Energy System Based on Cyber-Physical System

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Journal of Modern Power Systems and Clean Energy 2024年第5期12卷 1617-1630页

作者： Yi Yang Peng Zhang Can Wang Zhuoli Zhao Loi Lei Lai the Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station College of Electrical Engineering and New EnergyChina Three Gorges UniversityYichangChina the Department of Electrical Engineering School of AutomationGuangdong University of TechnologyGuangzhouChina

The traditional energy hub based model has difficulties in clearly describing the state transition and transition conditions of the energy unit in the integrated energy system(IES).Therefore,this study proposes a state transition modeling method for an IES based on a cyber-physical system(CPS)to optimize the state transition of energy unit in the *** method uses the physical,integration,and optimization layers as a three-layer modeling *** physical layer is used to describe the physical models of energy units in the *** the integration layer,the information flow is integrated into the physical model of energy unit in the IES to establish the state transition model,and the transition conditions between different states of the energy unit are *** optimization layer aims to minimize the operating cost of the IES and enables the operating state of energy units to be transferred to the target *** simulations show that,compared with the traditional modeling method,the state transition modeling method based on CPS achieves the observability of the operating state of the energy unit and its state transition in the dispatching cycle,which obtains an optimal state of the energy unit and further reduces the system operating costs.

关键词： Integrated energy system(IES) cyber-physical system(CPS) state transition modeling optimal dispatching

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Online distributed optimization with stochastic gradients:high probability bound of regrets

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control Theory and Technology 2024年第3期22卷 419-430页

作者： Yuchen Yang Kaihong Lu Long Wang Center for Systems and Control College of EngineeringPeking UniversityBeijing 100871China College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590ShandongChina

In this paper,the problem of online distributed optimization subject to a convex set is studied via a network of *** agent only has access to a noisy gradient of its own objective function,and can communicate with its neighbors via a *** handle this problem,an online distributed stochastic mirror descent algorithm is *** works on online distributed algorithms involving stochastic gradients only provide the expectation bounds of the *** from them,we study the high probability bound of the regrets,i.e.,the sublinear bound of the regret is characterized by the natural logarithm of the failure probability's *** mild assumptions on the graph connectivity,we prove that the dynamic regret grows sublinearly with a high probability if the deviation in the minimizer sequence is sublinear with the square root of the time ***,a simulation is provided to demonstrate the effectiveness of our theoretical results.

关键词： Distributed optimization Online optimization Stochastic gradient High probability

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Parallel System Based Quantitative Assessment and Self-evolution for Artificial Intelligence of Active Power Corrective control

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 13-28页

作者： Tianyun Zhang Jun Zhang Feiyue Wang Peidong Xu Tianlu Gao Haoran Zhang Ruiqi Si School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072HubeiChina State Key Laboratory for Management and Control of Complex System Institute of AutomationChinese Academy of SciencesBeijing 100190China

In artificial intelligence(AI)based-complex power system management and control technology,one of the urgent tasks is to evaluate AI intelligence and invent a way of autonomous intelligence ***,there is,currently,nearly no standard technical framework for objective and quantitative intelligence *** this article,based on a parallel system framework,a method is established to objectively and quantitatively assess the intelligence level of an AI agent for active power corrective control of modern power systems,by resorting to human intelligence evaluation *** this basis,this article puts forward an AI self-evolution method based on intelligence assessment through embedding a quantitative intelligence assessment method into automated reinforcement learning(AutoRL)systems.A parallel system based quantitative assessment and self-evolution(PLASE)system for power grid corrective control AI is thereby constructed,taking Bayesian Optimization as the measure of AI evolution to fulfill autonomous evolution of AI under guidance of their intelligence assessment *** results exemplified in the power grid corrective control AI agent show the PLASE system can reliably and quantitatively assess the intelligence level of the power grid corrective control agent,and it could promote evolution of the power grid corrective control agent under guidance of intelligence assessment results,effectively,as well as intuitively improving its intelligence level through selfevolution.

关键词： AI quantitative intelligence assessment and self-evolution automated reinforcement learning Bayesian optimization corrective control parallel system

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On-Policy and Off-Policy Value Iteration Algorithms for Stochastic Zero-Sum Dynamic Games

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Journal of Systems Science & Complexity 2025年第1期38卷 421-435页

作者： GUO Liangyuan WANG Bing-Chang ZHANG Ji-Feng School of Control Science and Engineering Shandong UniversityJinan 250063China School of Automation and Electrical Engineering Zhongyuan University of TechnologyZhengzhou 450007China Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China

This paper considers the value iteration algorithms of stochastic zero-sum linear quadratic games with unkown ***-policy and off-policy learning algorithms are developed to solve the stochastic zero-sum games,where the system dynamics is not *** analyzing the value function iterations,the convergence of the model-based algorithm is *** equivalence of several types of value iteration algorithms is *** effectiveness of model-free algorithms is demonstrated by a numerical example.

关键词： Approximate dynamic programming on-policy off-policy stochastic zero-sum games valueiteration

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electrical tree degradation of MgO/epoxy resin composites at different voltage frequencies

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High Voltage 2024年第3期9卷 581-590页

作者： Yunxiao Zhang Wenxin Lin Yuanxiang Zhou Weiwei Xing Jiayu Cheng Chenyuan Teng College of Electrical Engineering and Automation Fuzhou UniversityFujian Key Laboratory of New Energy Generation and Power ConversionFuzhouChina State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical EngineeringTsinghua UniversityBeijingChina

electrical tree degradation is one of the main causes of insulation failure in high-frequency *** tree degradation is studied on pure epoxy resin(EP)and MgO/EP composites at frequencies ranging from 50 Hz to 130 *** results show that the tree initiation voltage of EP decreases,while the growth rate and the expansion coefficient increase with ***,the bubble phenomenon at high frequencies in EP composites is *** with trap distribution character-istics within the material,the intrinsic mechanism of epoxy composites to inhibit the growth of the electrical tree at different frequencies is *** can be concluded that more deep traps and blocking effect are introduced by doping nano-MgO into EP bulks,which can improve the electrical tree resistance performance of EP composites in a wide frequency range.

关键词： composites tree electrical

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Model-Based Online Adaptive Inverse Noncooperative Linear-Quadratic Differential Games via Finite-Time Concurrent Learning

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第8期5卷 4247-4257页

作者： Lin, Jie Wu, Huai-Ning Beihang University School of Automation Science and Electrical Engineering Beijing100191 China Beihang University Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical Engineering Beijing100191 China Peng Cheng Laboratory Shenzhen518066 China

Noncooperative differential games provide a basis for the study of coordination, conflict, and control for a single dynamical system with multiple players. Within the linear-quadratic differential games (LQDGs), the optimal feedback gain matrix and the weighting matrices of individual cost function depict each player's control policy and the tradeoff of various objectives, respectively. In this article, we investigate the inverse problem of LQDG with partial state observation via a model-based online method, i.e., recover the cost function of each player. First, a state observer is used to estimate the system state. Then, the feedback gain matrices of players are learned using a finite-time concurrent learning (FTCL)-based adaptive law relaxing the persistent excitation (PE) condition which is required in traditional adaptive estimation methods. With the learned feedback gain matrices, a semidefinite programming (SDP) problem with the quadratic objective function can be set up for determining the weighting matrices of the cost function. The applicability and effectiveness of the proposed method are demonstrated with a numerical example and a shared steering control simulation. © 2020 IEEE.

关键词： Cost functions

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Relaxed Stability Criteria for Time-Delay Systems:A Novel Quadratic Function Convex Approximation Approach

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 996-1006页

作者： Shenquan Wang Wenchengyu Ji Yulian Jiang Yanzheng Zhu Jian Sun College of Electrical and Electronic Engineering Changchun University of TechnologyChangchun 130012China the College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590China Key Laboratory of Complex Systems Intelligent Control and Decision Beijing Institute of TechnologyBeijing 100081China

This paper develops a quadratic function convex approximation approach to deal with the negative definite problem of the quadratic function induced by stability analysis of linear systems with time-varying *** introducing two adjustable parameters and two free variables,a novel convex function greater than or equal to the quadratic function is constructed,regardless of the sign of the coefficient in the quadratic *** developed lemma can also be degenerated into the existing quadratic function negative-determination(QFND)lemma and relaxed QFND lemma respectively,by setting two adjustable parameters and two free variables as some particular ***,for a linear system with time-varying delays,a relaxed stability criterion is established via our developed lemma,together with the quivalent reciprocal combination technique and the Bessel-Legendre *** a result,the conservatism can be reduced via the proposed approach in the context of constructing Lyapunov-Krasovskii functionals for the stability analysis of linear time-varying delay ***,the superiority of our results is illustrated through three numerical examples.

关键词： Equivalent reciprocal combination technique quadratic function convex approximation approach stability timevarying delay

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