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Parameter Estimation and Tracking control of MIMO Linear Systems Without Prior Knowledge of control Signs and Parameter Bounds

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IEEE Transactions on Automatic control 2024年第6期70卷 3695-3710页

作者： Xu, Yuchun Zhang, Yanjun Zhang, Ji-Feng Chinese Academy of Sciences Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Beijing100190 China Beijing Institute of Technology School of Automation Beijing100081 China Beijing Institute of Technology State Key Lab of Automation Intelligent Unmanned Systems Beijing100081 China University of Chinese Academy of Sciences School of Mathematics Sciences Beijing100149 China Zhongyuan University of Technology School of Automation and Electrical Engineering Zhengzhou450007 China Chinese Academy of Sciences Academy of Mathematics and Systems Science Beijing100190 China

Dealing with the uncertain high-frequency gain matrix, denoted as Kp, is a fundamental problem in multivariable adaptive control systems. In this paper, we propose a new solution for parameter estimation and adaptive control for a general class of multi-input multi-output discrete-time linear time-invariant systems. The proposed scheme does not require any prior knowledge of the sign or bound information of Kp, and thus, significantly relaxes the design conditions in traditional multivariable adaptive control systems. Compared with the commonly used Nussbaum gain or multi-model techniques for addressing the unknown signs of Kp, the proposed scheme does not rely on any additional design conditions or any switching mechanism, while still ensuring closed-loop stability and asymptotic output tracking. Specifically, an output feedback adaptive control law is developed based on a matrix decomposition technique, which leads to derivation of a modified estimation error model. Subsequently, a gradient-based parameter update law is formulated only relying on the non-zero condition of the leading principle minors of Kp. Through designing gain functions and stable filters, the controller is always non-singular and does not involve any causal contradiction problem. Simulation study showcases the design process and demonstrates the effectiveness of the proposed scheme. © 1963-2012 IEEE.

关键词： MIMO systems

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Semi-asynchronous personalized federated learning for short-term photovoltaic power forecasting

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Digital Communications and Networks 2023年第5期9卷 1221-1229页

作者： Weishan Zhang Xiao Chen Ke He Leiming Chen Liang Xu Xiao Wang Su Yang College of Computer Science and Technology China University of Petroleum(East China)China Sichuan Energy Internet Research Institute Tsinghua UniversityChina School of Computer and Communication Engineering Beijing University of Science and TechnologyChina State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijingChina School of Computer Science Fudan UniversityChina

Accurate forecasting for photovoltaic power generation is one of the key enablers for the integration of solar photovoltaic systems into power *** deep-learning-based methods can perform well if there are sufficient training data and enough computational ***,there are challenges in building models through centralized shared data due to data privacy concerns and industry *** learning is a new distributed machine learning approach which enables training models across edge devices while data reside *** this paper,we propose an efficient semi-asynchronous federated learning framework for short-term solar power forecasting and evaluate the framework performance using a CNN-LSTM *** design a personalization technique and a semi-asynchronous aggregation strategy to improve the efficiency of the proposed federated forecasting *** evaluations using a real-world dataset demonstrate that the federated models can achieve significantly higher forecasting performance than fully local models while protecting data privacy,and the proposed semi-asynchronous aggregation and the personalization technique can make the forecasting framework more robust in real-world scenarios.

关键词： Photovoltaic power forecasting Federated learning Edge computing CNN-LSTM

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Synthesis of Decoherence-Free Modes in Linear Quantum Passive Systems via Robust Pole Placement

Synthesis of Decoherence-Free Modes in Linear Quantum Passiv...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Miao, Zibo Pan, Yu Gao, Qing School of Mechanical Engineering and Automation Adaptive Robotics Harbin Institute of Technology Guangdong Key Laboratory of Intelligent Morphing Mechanisms Shenzhen518055 China The Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China The School of Automation Science and Electrical Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China

ISBN: (纸本)9781665410205

In this paper we extend our previous research on coherent observer-based pole placement approach to study the synthesis of robust decoherence-free (DF) modes for linear quantum passive systems, which is aimed at preservation of quantum information. In particular, DF modes can be generated by placing the poles on the imaginary axis via a coherent feedback design scheme, and these modes can further be simultaneously made robust against perturbations to the system parameters by minimizing the condition number associated with imaginary poles. We develop explicit algebraic conditions for the existence of such a coherent quantum controller, with the corresponding deign procedure provided. Examples are given to illustrate the process of tuning the DF modes towards perfect robustness via the proposed pole placement technique. © 2024 IEEE.

关键词： Poles

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Social Radars: Finding Targets in Cyberspace for Cybersecurity

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 279-282页

作者： Lili Fan Changxian Zeng Yutong Wang Jiaqi Ma Fei-Yue Wang School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China School of Science Dalian Minzu UniversityDalian 116600China State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Department of Civil and Environmental Engineering University of CaliforniaLos AngelesCA 90024 USA IEEE State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China

INSPIRED by the insight from American political scientist Lasswell, who summarized the environmental role in societal surveillance [1], Schramm coined the term “social radar” [2] as it resembles the activities of radar in collecting and processing information, playing a crucial role in helping humans perceive changes in the internal and external environment and promptly adjusting adaptive behaviors.

关键词： prompt summarized insight

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Data-Driven Group Formation control of Cyber-Physical Systems via Distributed Cloud Computing

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical Systems 2025年 3卷 341-350页

作者： Ren, Hongru Long, Yinren Li, Hongyi Huang, Tingwen Guangdong University of Technology School of Automation Guangdong-Hong Kong Joint Laboratory for Intelligent Decision and Cooperative Control Guangdong Provincial Key Laboratory for Intelligent Decision and Cooperative Control Guangzhou510006 China Southwest University College of Electronic and Information Engineering Chongqing400715 China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China

This paper investigates the group formation control problem for cyber-physical systems (CPSs) with random communication constraints. The distributed cloud computing system is constructed to divide agents into groups and establish communication between agents. A data-driven predictive control strategy is proposed by combining networked predictive control and model-free adaptive control method. The desired group formation control performance can be achieved and the three-channel random communication constraints of CPSs are actively compensated. Thisstrategy does not require the system model and relies solely on the system's I/O data for adaptive learning. Further analyses concludes the conditions for simultaneous reach stability and group formation of the closed-loop CPSs using the data-driven predictive control strategy. The effectiveness of the proposed strategy is validated by simulation results. © 2023 IEEE.

关键词： Distributed cloud

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Reachability Analysis and Safety Synthesis of a Class of Human-Computer Collaborative Driving Systems 41

Reachability Analysis and Safety Synthesis of a Class of Hum...

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第41届中国控制会议

作者： Yang-Fan Liu Xiu-Mei Zhang Huai-Ning Wu Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical EngineeringBeihang University Peng Cheng Laboratory

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This work investigates the safety problem for a class of human-computer collaborative driving(H-CCD) systems by the approach of reachable set *** H-CCD system under consideration can monitor the human internal state(HIS)and then provide a proper human-assistance control law to the ***,a yaw-sideslip bicycle model is employed to describe the lateral dynamics of the vehicle in which a human driver is maintaining the center of gravity of the vehicle at the middle of a lane and trying to keep the vehicle away from road ***,a hidden Markov model(HMM) is used for human behavior modelling,which takes into account the random nature of HIS reasoning and the uncertainty from HIS *** integrating a vehicle model,a human model,and their interaction,a hidden Markov jump system(HMJS) model is constructed to describe the H-CCD *** the tools of reachable set computation and linear matrix inequalities(LMIs),a sufficient condition for the reachability of the H-CCD system to a prescribed safe set is given on the basis of the HMJS *** LMI approach to the human-assistance control design is then proposed such that the H-CCD system is safe in the sense of ***,theoretical results are verified by a numerical simulation.

关键词： Safety Human-computer collaborative driving system Reachable set Hidden Markov model

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A new Interleaved Full-Bridge Converter for AC battery 12

A new Interleaved Full-Bridge Converter for AC battery

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12th IEEE International Conference on control, automation and Information sciences, ICCAIS 2023

作者： Do, Tuan Anh Le, Quang Nghia Nguyen, Thang Long Dich, Nguyen Quang Hoang, Phuong Vu Hanoi University of Science and Technology School of Electrical and Electronic Engineering Hanoi Viet Nam Hanoi University of Science and Technology Institute for Control Engineering and Automation Hanoi Viet Nam

ISBN: (纸本)9798350328783

Home battery storage systems using Second-life time batteries (SLBs) are of recent research interest for resilient homes. The AC Battery is chosen for this application due to its flexibility, in which the Interleaved Full Bridge (IFB) converter is studied in this paper for the Power Correction Factor (PFC) stage. The pulse width modulation and control strategy are introduced for the IFB converter in this research. To verify the operation and the feasibility of the proposed structure in the grid-tied mode, a real-time simulation is carried out with the results meeting a good agreement with the theoretical analyst. © 2023 IEEE.

关键词： Electric power factor correction

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Adaptive cubature Kalman filter with the estimation of correlation between multiplicative noise and additive measurement noise

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Chinese Journal of Aeronautics 2022年第5期35卷 40-52页

作者： Quanbo GE Zhongcheng MA Jinglan LI Qinmin YANG Zhenyu LU Hong LI School of Electronics and Information Engineering Tongji UniversityShanghai 201804China Institute of Systems Science and Control Engineering School of AutomationHangzhou Dianzi UniversityHangzhou 310018China State Key Laboratory of Industrial Control Technology and the College of Control Science and EngineeringZhejiang UniversityHangzhou 310027China Jiangsu Key Laboratory of Meteorological Observation and Information Processing Nanjing University of Information Science and TechnologyNanjing 210044China Chinese Flight Test Establishment Xi’an 710089China

Mobile robots are often subject to multiplicative noise in the target tracking tasks,where the multiplicative measurement noise is correlated with additive measurement *** this paper,first,a correlation multiplicative measurement noise model is *** is able to more accurately represent the measurement error caused by the distance sensor dependence ***,the estimated performance mismatch problem of Cubature Kalman Filter(CKF)under multiplicative noise is *** improved Gaussian filter algorithm is introduced to help obtain the CKF algorithm with correlated multiplicative *** practice,the model parameters are unknown or inaccurate,especially the correlation of noise is difficult to obtain,which can lead to a decrease in filtering accuracy or even *** address this,an adaptive CKF algorithm is further provided to achieve reliable state estimation for the unknown noise correlation coefficient and thus the application of the CKF algorithm is ***,the estimated performance is analyzed theoretically,and the simulation study is conducted to validate the effectiveness of the proposed algorithm.

关键词： Adaptive CKF Correlated noise Estimation accuracy Multiplicative noise Performance analysis Target tracking

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Positioning Method for Covered Vehicles Based on Neutrino Detection and Reinforcement Learning 3

Positioning Method for Covered Vehicles Based on Neutrino De...

引用

3rd International Conference on Electronic Information engineering and Computer, EIECT 2023

作者： Han, Mingren Gao, Jiashan Zhou, Peng Zhang, Yixin Beijing Institute of Control Engineering China Academy of Space Technology Beijing China Beihang University School of Automation Science and Electrical Engineering Beijing China

ISBN: (纸本)9798350357707

In complex environments like underwater or underground, traditional navigation technologies face limitations due to the restricted penetration of optical and radio signals. Neutrino signals, which have extremely strong penetration capabilities, offer a new possibility. This study explores the challenges of navigation and positioning of covered vehicles and proposes a neutrino-based navigation and positioning technology to overcome the limitations of traditional navigation technologies in complex environments. This research combines reinforcement learning methods and Kalman filters, using the Proximal Policy Optimization (PPO) algorithm to tune the parameters of the Kalman filter to improve navigation and positioning accuracy. In the study, a Kalman filter estimation system model for vehicles in navigation signal denied environment environments was first established, then a navigation and positioning method based on neutrino detection was designed, and finally, a parameter adaptive PPO Extended Kalman Filter (PPOEKF) state estimation method was proposed. Through mathematical simulation and comparative analysis, the research results show that using reinforcement learning methods to tune the parameters of the Kalman filter can improve the accuracy of navigation and positioning, especially in complex environments. © 2023 IEEE.

关键词： Reinforcement learning

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SAR performance-based fault diagnosis for electrohydraulic control system:A novel FDI framework for closed-loop system

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Chinese Journal of Aeronautics 2022年第10期35卷 381-392页

作者： Yang ZHANG Shaoping WANG Jian SHI Xinyu YANG Jiarui ZHANG Xi WANG School of Energy and Power Engineering Beihang UniversityBeijing 100191China School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China Institute for Automatic Control and Complex Systems(AKS) University of Duisburg-EssenDuisburg 47057Germany

Model-based fault diagnosis serves as an efficient and powerful technique in addressing fault detection and isolation(FDI)issues for control ***,the standard methods and their modifications still encounter some difficulties in algorithm design and application for complex higher-order *** avoid these difficulties,a novel fault diagnosis framework based on multiple performance indicators of closed-loop control system is *** this framework,a socalled performance residual vector is constructed to measure the differences between the real system and the nominal model in terms of system stability,accuracy,and rapidity(SAR)*** criteria for quantification,normalization of the SAR residuals and the explicit mappings between the thresholds and the required performance are *** can be easily achieved simultaneously by monitoring the normalized residual vector length and direction in the SAR performance residual space.A case study on electro-hydraulic servo control system of turbofan engine is adopted to demonstrate the effectiveness of the proposed method.

关键词： Electro-hydraulic servo valve(EHSV) Fault diagnosis Fuel metering unit Performance degradation Performance residual Stability,accuracy,and rapidity(SAR)

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