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On Resilience Against Cyber-Physical Uncertainties in Distributed Nash Equilibrium Seeking Strategies for Heterogeneous Games

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 138-147页

作者： Maojiao Ye IEEE the school of automation Nanjing University of Science and Technology

This paper designs distributed Nash equilibrium seeking strategies for heterogeneous dynamic cyber-physical *** particular, we are concerned with parametric uncertainties in the control channel of the players. Moreover, the weights on communication links can be compromised by time-varying uncertainties, which can result from possibly malicious attacks,faults and disturbances. To deal with the unavailability of measurement of optimization errors, an output observer is constructed,based on which adaptive laws are designed to compensate for physical uncertainties. With adaptive laws, a new distributed Nash equilibrium seeking strategy is designed by further integrating consensus protocols and gradient search ***, to further accommodate compromised communication weights resulting from cyber-uncertainties, the coupling strengths of the consensus module are designed to be adaptive. As a byproduct, the coupling strengths are independent of any global information. With theoretical investigations, it is proven that the proposed strategies are resilient to these uncertainties and players' actions are convergent to the Nash equilibrium. Simulation examples are given to numerically validate the effectiveness of the proposed strategies.

关键词： Adaptive law cyber-physical systems distributed Nash equilibrium seeking uncertainties

Global adaptive output feedback control of nonlinear time-delay systems with measurement uncertainty

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Control Theory and Technology 2025年第1期23卷 145-152页

作者： Weiguo Cai Xianglei Jia Xinxu Ju school of automation Hangzhou Dianzi UniversityHangzhou310018ZhejiangChina

In this paper,a pair of dynamic high-gain observer and output feedback controller is proposed for nonlinear systems with multiple unknown time *** constructing Lyapunov-Krasovskii functionals,it shows that global state asymptotic regulation can be ensured by introducing a single dynamic gain;furthermore,global asymptotic stabilization can be achieved by choosing a sufficiently large static scaling gain when the upper bounds of all system parameters are ***,the output coefficient is allowed to be non-differentiable with unknown upper *** paper proposes a generalized Lyapunov matrix inequality based dynamic-gain scaling method,which significantly simplifies the design computational complexity by comparing with the classic backstepping method.

关键词： Output feedback Measurement uncertainty Nonlinear adaptive control Time delays

The optimal control theory——a scientific approach to fundamentally solving control problems

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Science China(Information Sciences) 2025年第1期68卷 389-391页

作者： Huanshui ZHANG school of Electrical and automation Engineering Shandong University of Science and Technology school of Control Science and Engineering Shandong University

The maximum principle has bridged mathematical optimization to optimal control,ushering in significant developments and refinements in optimal control theory,notably during the 1960s with the advent of linear quadratic (LQ)control and linear quadratic estimation (LQE).This progression propelled optimal control theory into further advancements,encompassing stochastic control,robust/H-infinity control,model predictive control (MPC),networked control,and reinforcement learning *** control,established upon a rigorous mathematical foundation,extends static optimization theory to dynamic systems,exhibiting scientific essence,unity,and ***,since its inception,optimal control theory has served as an indispensable core role across all control-related domains,including communication-constrained control in networked systems,consensus control,cooperative control,and reinforcement learning control.

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Dynamic event-triggered data-driven iterative learning bipartite tracking control for nonlinear MASs with prescribed performance

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Science China(Information Sciences) 2025年第1期68卷 292-305页

作者： Tao SHI Wei-Wei CHE school of Mechatronic Engineering and automation Shanghai University State Key Laboratory of Synthetical automation for Process Industries Northeastern University College of Information Science and Engineering Northeastern University

This article proposes a distributed dynamic event-triggered data-driven iterative learning control(DET-DDILC)scheme under a predefined performance to tackle the bipartite tracking control problem for multiagent systems(MASs). An improved dynamic linearization technique is utilized to convert the nonlinear MASs into an iterative linear data model. First,a peer-to-peer mapping function is introduced to map the constrained distributed system output homeomorphism to an unconstrained one. In addition, a DET mechanism based on a time-iteration-varying function is devised to conserve network communication resources. Based on the unconstrained transformation and the designed DET mechanism, the DET-DDILC algorithm is devised to ensure that the bipartite tracking performance of MASs can be within the preset range. Finally, the effectiveness and feasibility of the designed control scheme are demonstrated via a simulation case by a comparison.

关键词： bipartite tracking control prescribed performance event-triggered iterative learning control multiagent systems

A Power Battery Fault Diagnosis Method Based on Long-Short Term Memory-Back Propagation

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Energy Engineering 2025年第2期122卷 709-731页

作者： Yuheng Yin Jiahao Song Minghui Yang school of automation Harbin University of Science and TechnologyHarbin150080China

The lithium battery is an essential component of electric cars;prompt and accurate problem detection is vital in guaranteeing electric cars’safe and dependable functioning and addressing the limitations of Back Propagation(BP)neural networks in terms of vanishing gradients and inability to effectively capture dependencies in time series,and the limitations of Long-Short Term Memory(LSTM)neural network models in terms of risk of overfitting.A method based on LSTM-BP is put forward for power battery fault diagnosis to improve the accuracy of lithium battery fault ***,a lithium battery model is constructed based on the second-order RC equivalent circuit and the electro-thermal coupling model,and various lithium battery failures are simulated to examine the fault ***,the lithium battery charging and discharging experiments collect,clean,and process the battery *** constructing a neural network LSTM-BP model,we verified the superiority and accuracy of the LSTM-BP neural network model by comparing the LSTM model and BP model vertically and by comparing the Recurrent Neural Network(RNN)model,the Gated Recurrent Unit(GRU)model,and the Residual Neural Network(ResNet)model of a more advanced architecture ***,the lithium battery fault diagnosis process is summarized through the threshold quantitative criteria,and different faults are diagnosed and *** show that the LSTM-BP neural network not only overcomes the limitations of the LSTMneural network and BP neural network but also improves the ability to process sequence data and reduces the risk of overfitting.

关键词： Lithium battery fault diagnosis BP neural network LSTM neural network

Cooperative output regulation of heterogeneous directed multi-agent systems:a fully distributed model-free reinforcement learning framework

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Science China(Information Sciences) 2025年第2期68卷 170-185页

作者： Xiongtao SHI Yanjie LI Chenglong DU Huiping LI Chaoyang CHEN Weihua GUI Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics School of Mechanical Engineering and AutomationHarbin Institute of Technology (Shenzhen) school of automation Central South University school of Marine Science and Technology Northwestern Polytechnical University school of Information and Electrical Engineering Hunan University of Science and Technology

In this paper, the cooperative output regulation(COR) problem of a class of unknown heterogeneous multi-agent systems(MASs) with directed graphs is studied via a model-free reinforcement learning(RL) based fully distributed eventtriggered control(ETC) strategy. First, we consider the scenario that the exosystem is accessible globally to all agents, an internal model-based augmented algebraic Riccati equation(AARE) is constructed, and its solution is learned by the proposed model-free RL algorithm via online input-output data. Further, for the scenario that the exosystem is accessible only to its adjacent followers, the distributed observers are designed for each agent to get the state of the exosystem, and an internal modelbased fully distributed adaptive ETC protocol is then synthesized to construct the corresponding AARE, and the feedback gain matrix is learned in a model-free fashion. The model-free RL-based control protocol proposed in this paper can not only remove the prior knowledge of agents' dynamics, but also release the dependence on global information by the adaptive event-triggered mechanism(ETM) and the new graph-based Lyapunov function. Finally, simulation results are illustrated to show the feasibility and effectiveness of the proposed control scheme.

关键词： model-free reinforcement learning unknown heterogeneous multi-agent systems fully distributed event-triggered control directed graph

Embedding prescribed-time adaptive control protocol unveiling distributed consensus in multirobot systems via directed topology

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Science China(Information Sciences) 2025年第2期68卷 383-384页

作者： Yonghao XIE Xinru MA Hengyu LI Shaorong XIE school of Computer Engineering and Science Shanghai University school of Mechatronic Engineering and automation Shanghai University

Recently, multirobot systems(MRSs) have found extensive applications across various domains, including industrial manufacturing, collaborative formation of unmanned equipment, emergency disaster relief, and war scenarios [1]. These advancements are largely supported by the development of consistency control theory. However, traditional dynamicsfree models may cause instability in complex robotic systems. Lagrangian dynamics offers a better approach for modeling these systems, as it facilitates controller design and optimization analysis. Despite this, challenges persist with unknown parameters and nonlinear friction within the systems.

关键词： Microrobots

Improved Zero-Dynamics Attack Scheduling With State Estimation

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IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 472-474页

作者： Zhe Wang Heng Zhang Chaoqun Yang Xianghui Cao the school of Computer Engineering Jiangsu Ocean University the school of Marine Technology and Geomatics Jiangsu Ocean University IEEE the school of automation Southeast University

Dear Editor,This letter focuses on how an attacker can design suitable improved zero-dynamics (ZD) attack signal based on state estimates of target system. Improved ZD attack is to change zero dynamic gain matrix of a...

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Overview and Prospect of Distributed Energy P2P Trading

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Energy Engineering 2025年第1期122卷 379-404页

作者： Jiajia Liu Mingxing Tian Xusheng Mao school of automation and Electrical Engineering Lanzhou Jiaotong UniversityLanzhou730070China

After a century of relative stability in the electricity sector,the widespread adoption of distributed energy resources,along with recent advancements in computing and communication technologies,has fundamentally altered how energy is consumed,traded,and *** change signifies a crucial shift as the power system evolves from its traditional hierarchical organization to a more decentralized *** the heart of this transformation are innovative energy distribution models,like peer-to-peer(P2P)sharing,which enable communities to collaboratively manage their energy *** effectiveness of P2P sharing not only improves the economic prospects for prosumers,who generate and consume energy,but also enhances energy resilience and *** allows communities to better leverage local resources while fostering a sense of collective responsibility and collaboration in energy ***,there is still no extensive implementation of such sharing models in today’s *** on distributed energy P2P trading is still in the exploratory stage,and it is particularly important to comprehensively understand and analyze the existing distributed energy P2P trading *** paper contributes with an overview of the P2P markets that starts with the network framework,market structure,technical approach for trading mechanism,and blockchain technology,moving to the outlook in this field.

关键词： Distributed energy P2P market mechanisms classification and comparison