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Distributed Observer for Full-Measured Nonlinear systems Based on Knowledge of FMCF

IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 69-85页

作者： Haotian Xu Shuai Liu Yueyang Li Ke Li the School of Control Science and Engineering Shandong University and also with Key Laboratory of Machine Intelligence and System Control Ministry of Education IEEE the School of Electrical Engineering University of Jinan

Driven by practical applications, the achievement of distributed observers for nonlinear systems has emerged as a crucial advancement in recent years. However, existing theoretical advancements face certain limitations: They either fail to address more complex nonlinear phenomena, rely on hard-to-verify assumptions, or encounter difficulties in solving system ***, this paper aims to address these challenges by investigating distributed observers for nonlinear systems through the full-measured canonical form(FMCF), which is inspired by full-measured system(FMS) theory. To begin with, this study addresses the fact that the FMCF can only be obtained through the observable canonical form(OCF) in existing FMS *** paper demonstrates that a class of nonlinear systems can directly obtain FMCF through state space equations, independent of OCF. Also, a general method for solving FMCF in such systems is provided. Furthermore, based on the FMCF, A distributed observer is developed for nonlinear systems under two scenarios: Lipschitz conditions and open-loop bounded *** paper establishes their asymptotic omniscience and demonstrates that the designed distributed observer in this study has fewer design parameters and is more convenient to construct than existing approaches. Finally, the effectiveness of the proposed methods is validated through simulation results on Van der Pol oscillators and microgrid systems.

关键词： Distributed observer full-actuated system full-measured system (FMS) nonlinear observer sensor networks

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Two-stage Optimal Scheduling of Community Integrated Energy system Considering Operation Sequences of Hydrogen Energy Storage systems

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Journal of Modern Power systems and Clean Energy 2025年第1期13卷 276-288页

作者： Wei Kong Kai Sun Jinghong Zhao School of Electrical Engineering Naval University of EngineeringWuhanChina Department of Electrical Engineering State Key Laboratory of Power System Operation and ControlTsinghua UniversityBeijingChina

The hydrogen energy storage system(HESS)integrated with renewable energy power generation exhibits low reliability and flexibility under source-load *** address the above issues,a two-stage optimal scheduling model considering the operation sequences of HESSs is proposed for commercial community integrated energy systems(CIESs)with power to hydrogen and heat(P2HH)*** aims to optimize the energy flow of HESS and improve the flexibility of hydrogen production and the reliability of energy supply for ***,the refined operation model of HESS is established,and its operation model is linearized according to the operation domain of HESS,which simplifies the difficulty in solving the optimization problem under the premise of maintaining high approximate ***,considering the flexible start-stop of alkaline electrolyzer(AEL)and the avoidance of multiple energy conversions,the operation sequences of HESS are ***,a two-stage optimal scheduling model combining day-ahead economic optimization and intra-day rolling optimization is established,and the model is simulated and verified using the source-load prediction data of typical days in each *** simulation results show that the two-stage optimal scheduling reduces the total load offset by about 14%while maintaining similar operating cost to the day-ahead economic optimal ***,by formulating the operation sequences of HESS,the operating cost of CIES is reduced by up to about 4.4%.

关键词： Community integrated energy system(CIES) hydrogen storage operation sequence two-stage optimal scheduling

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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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Elliptical Model-Based Robust Pedestrian Pose Tracking by LiDAR via Bi-Level Moving Horizon Random Sample Consensus

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IEEE Access 2025年 13卷 72829-72840页

作者： Muhammad, Haziq Ismail, Zool H. Sekiguchi, Kazuma Nonaka, Kenichiro Tokyo City University Advanced Control System Engineering Laboratory Tokyo Setagaya158-8557 Japan Kuala Lumpur54100 Malaysia

Recent advancements in autonomous vehicle research have heightened the need for precise pedestrian pose tracking to ensure safe navigation. Utilizing LiDAR sensors, conventional bounding box (BB) methods are generally used but are sensitive to limb motion. The previous moving horizon-based maximum likelihood estimation sample consensus (MHESAC) study addressed this robustness limitation but suffered from extensive point cloud (PC) sampling, limiting real-time applications. This paper proposes an elliptical pedestrian model tracking within a sequential bi-level MHESAC (B-MHESAC) framework that combines random sampling consensus (RANSAC) for local model fitting per time step and maximum likelihood estimation sample consensus (MLESAC) for optimal model sequence selection throughout the horizon, significantly reducing PC sampling while preserving accuracy. Under significant outlier contamination, B-MHESAC requires less trials than MHESAC for multiple horizons and samples. Moreover, at long horizon lengths, B-MHESAC required trial’s exponential growth is at least reduced to the fifth root of MHESAC, allowing real-time estimations. The proposed method was evaluated in an indoor single pedestrian tracking experiment. Experimental results demonstrate that B-MHESAC is more robust than conventional RANSAC in model fitting. Additionally, the elliptical model-based B-MHESAC’s tracking performance is competitive with the MHESAC method’s and superior to other Kalman filter-based BB and circle model methods. © 2013 IEEE.

关键词： Maximum likelihood estimation

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Comparative Analysis of Noise Margin Between Pure SET-SET and Hybrid SET-PMOS Inverters

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Chinese Journal of Electronics 2025年第1期34卷 146-155页

作者： Fan Zhang Yi Liu Yibo Wang Minghu Wu Sheng Hu Youli Dong Hubei Key Laboratory for High-Efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Hubei University of Technology School of Electrical and Electronic Engineering Hubei University of Technology

Single-electron transistor（SET） is considered as one of the promising candidates for future electronic devices due to its advantages of low power consumption and high integration. The comparative analysis of SET-based inverters, especially the noise margin, is carried out. Pure SET-SET and hybrid SET with p type metal oxide semiconductor（SET-PMOS） inverters are designed for investigation. The effects of SET supply voltage, junction resistance and junction capacitance on noise tolerance and power consumption of inverters are studied. For hybrid SET-PMOS inverters, the noise margin for a logic high（NMH） is less than 60 mV under various conditions, which may become the bottleneck of its application. For pure SET-SET inverters, both NMH and the noise margin for a logic low（NML） could reach 300 mV at a supply voltage of 0.8 V. The minimum power consumption of pure SET-SET and hybrid SET-PMOS inverters is 2.85 nW and 58 nW, respectively. The pure SET-SET inverters have greater noise tolerance and lower power consumption, which is more conducive to large-scale integration. When junction capacitance CJ= 0.0273 aF and junction resistance RT≥1 MΩ in SET-SET inverters at a supply voltage of 0.8 V, the NMH and NML are not significantly affected by the junction resistance and the noise margin fluctuates at 300 mV.

关键词： Resistance Power demand Noise Metals Capacitance Inverters Large scale integration Logic Junctions Single electron transistors

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D-FUSION SLAM: A VSLAM system OPTIMIZED BY INTEGRATING DEPTH INFORMATION AND RGBD FEATURE POINTS

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical engineering and Computer Science 2025年第1期87卷 121-138页

作者： Zheng, Qingchun Wu, Moudong Zhu, Peihao Yang, Bin Li, Shubo Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China China

This paper introduces D-Fusion SLAM, an advanced VSLAM system based on ORB-SLAM2. D-Fusion SLAM integrates depth information to enhance feature selection, aiming to improve accuracy and speed in visual SLAM applications. The system mainly comprises two modules: an image grid filtering module based on grayscale information and a feature selection module integrating depth information. These modules effectively eliminate redundant and useless features, ensuring high-quality features for pose estimation. We tested D-Fusion SLAM on the TUM dataset and compared it with ORB-SLAM2. Experimental results demonstrate that D-Fusion SLAM outperforms ORB-SLAM2, significantly enhancing the system's accuracy and robustness. © 2025, Politechnica University of Bucharest. All rights reserved.

关键词： Feature Selection

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controllability of heterogeneous networked sampled-data systems

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Science China(Information Sciences) 2025年第3期68卷 302-318页

作者： Zixuan YANG Lin WANG Xiaofan WANG Guanrong CHEN Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China School of Mechatronic Engineering and Automation Shanghai University School of Electrical and Electronic Engineering Shanghai Institute of Technology Department of Electrical Engineering City University of Hong Kong

This study investigates the controllability of a general heterogeneous networked sampled-data system(HNSS) consisting of nonidentical node systems, where the inner coupling between any pair of nodes can be described by a unique *** signals on control and transmission channels are sampled and held by zero-order holders, and the control sampling period of each node can be different. Necessary and sufficient controllability conditions are developed for the general HNSS, using the Smith normal form and matrix equations, respectively. The HNSS in specific topology or dynamic settings is discussed subsequently with easier-to-verify conditions derived. These heterogeneous factors have been determined to independently or jointly affect the controllability of networked sampled-data systems. Notably, heterogeneous sampling periods have the potential to enhance the overall controllability, but not for systems with some special dynamics. When the node dynamics are heterogeneous,the overall system can be controllable even if it is topologically uncontrollable. In addition, in several typical heterogeneous sampled-data multi-agent systems, pathological sampling of single-node systems will necessarily cause overall uncontrollability.

关键词： network controllability sampled-data system heterogeneous system inner coupling multi-agent system

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Distributed Temperature Sensing Based on Chaotic Brillouin Scattering Power Measurement

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IEEE Sensors Journal 2025年第9期25卷 15968-15974页

作者： Xu, Jinglang Zhang, Jianzhong Li, Jian Ma, Zhe Liu, Shuangshuang Zhang, Yubo Wang, Zhikun Zhang, Mingjiang Taiyuan University of Technology Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province College of Physics and Optoelectronic Engineering Taiyuan030024 China

A high-accuracy distributed temperature sensing scheme utilizing chaotic Brillouin scattering power (BSP) combined with the cross correlation measurement method was proposed and experimentally demonstrated. The proposed scheme employs the chaotic laser as the sensing signal, adopting the chaotic cross correlation positioning principle instead of the conventional optical time-domain reflection (OTDR) principle. Additionally, it combines a single-path ratio method to accurately demodulate the temperature. This positioning method uses the random amplitude characteristics of chaotic lasers in the time domain. It overcomes the limitation of pulsewidth on spatial resolution in distributed temperature sensing based on OTDR principles. And it resolves the trade-off between spatial resolution and sensing distance. Experimental results demonstrated that the spatial positioning accuracy was optimized from 5.0 to 0.43 m with a 50 ns pulsewidth modulation, achieving a sensing distance of up to 10 km. This scheme aims to achieve high spatial positioning accuracy while maintaining a long sensing distance. This is crucial for early fire warning and effective emergency response in long-distance fire monitoring applications. © 2025 IEEE.

关键词： Brillouin scattering

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Tribo-informatics empowered research on triboelectrification

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Friction 2025年第2期13卷 121-129页

作者： Nian Yin Zhangli Hou Xin Wang Shumin Zhang Zhinan Zhang Stake Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong UniversityShanghai 200240China School of Mechanical Engineering Shanghai Jiao Tong UniversityShanghai 200240China Beijing Key Laboratory of Long-Life Technology of Precise Rotation and Transmission Mechanisms Beijing Institute of Control EngineeringBeijing 10009China

The triboelectric effect,known since ancient Greece,is the accumulation of electric charges due to electron transfer when materials contact and *** technological advancements,the triboelectric effect has been applied in energy harvesting equipment,sensors,and smart devices,including triboelectric nanogenerators(TENGs).This effect shows potential for sustainable energy and next-generation intelligent *** systems,as a type of tribological system,require state monitoring,behavior prediction,and system ***-informatics is an interdisciplinary field that combines tribology and *** clarifying information representations and flows within tribological systems,tribo-informatics addresses the connections between physical tribological systems and embedded information *** a focus on the triboelectric effect,this paper proposes a method for information representation in triboelectric systems from a tribo-informatics perspective and suggests a research approach based on tribo-informatics to achieve research *** aim is to enable researchers to collect,process,and analyze tribological information more effectively to achieve specific research objectives.

关键词： tribo-informatics triboelectrification artificial intelligence machine learning

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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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