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Stability Analysis of Networked control systems with Aperiodic Sampling and Time-Varying Delay

IEEE Transactions on Cybernetics 2017年第8期47卷 2312-2320页

作者： Chen, Jie Meng, Su Sun, Jian Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing100081 China

This paper addresses the stability of networked control systems with aperiodic sampling and time-varying network-induced delay. The sampling intervals are assumed to vary within a known interval. The transmission delay is assumed to belong to a given interval. The closed-loop system is first converted to a discrete-time system with multiple time-varying delays and norm-bounded uncertainties resulting from the variation of the sampling intervals. And then, it is transformed into a delay-free system being form of an interconnection of two subsystems. By utilizing scaled small gain theorem, an asymptotic stability criterion for the closed-loop system is proposed in terms of linear matrix inequality. Finally, numerical examples demonstrate the effectiveness of the proposed method and its advantages over existing methods. © 2013 IEEE.

关键词： Networked control systems

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Multi-criteria consensus sorting model with flexible linguistic preferences based on fuzzy information granulation from the perspective of preference disaggregation

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Engineering Applications of Artificial Intelligence 2025年 154卷

作者： Zhang, Shiji Zhang, Shitao Tian, Hao Deveci, Muhammet Liu, Xiaodi School of Microelectronics and Data Science Anhui University of Technology Ma'anshan243032 China Key Laboratory of Multidisciplinary Management and Control of Complex Systems of Anhui Higher Education Institutes Anhui University of Technology Ma'anshan243002 China Anhui Provincial Joint Key Laboratory of Disciplines for Industrial Big Data Analysis and Intelligent Decision Ma'anshan243032 China Department of Industrial Engineering Turkish Naval Academy National Defence University Tuzla Istanbul34942 Turkey The Bartlett School of Sustainable Construction University College London LondonWC1E 6BT United Kingdom Department of Information Technologies Western Caspian University Baku1001 Azerbaijan

Multi-criteria group sorting (MCGS) that considers linguistic preferences involves multiple individuals evaluating alternatives and assigning them to pre-determined ordered categories based on specific criteria. Nevertheless, due to the limited availability of class information and the constrained cognitive capacity of decision-makers (DMs), it becomes challenging for DMs to furnish explicit preference information to reach consensus. Besides, decision parameters such as consensus threshold and class thresholds are also too hard to be assumed in advance. Therefore, this paper studies the preference disaggregation problem in MCGS, in which DMs are allowed to provide their pairwise comparisons in flexible linguistic expressions (FLEs) as preference information. To more fully utilize the preferences, semantic granulation is introduced. First, an individual consistency recognition model is proposed to identify inconsistent preferences and provide modification directions to the corresponding individuals. Next, semantic granulation and maximum entropy are combined into a granulation-driven information transformation model to convert the preference information based on FLEs into triangular fuzzy numbers (TFNs). Subsequently, in the consensus-driven preference disaggregation model, decision parameters and sorting results can be obtained at the premise of consensus by adjusting weights. Ultimately, to substantiate the effectiveness of the proposal, two numerical applications concerning the sorting of government venture capitals and information system suppliers are presented, along with comparative analysis, sensitivity analysis, and simulation analysis. © 2025 The Authors

关键词： Information granules

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A Forest Fire Detection Method Based on a Deep Learning Approach

A Forest Fire Detection Method Based on a Deep Learning Appr...

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第30届中国过程控制会议（CPCC 2019）

作者： Honggang Yu Zhentian Jiao Youmin Zhang Jing Xin Lingxia Mu Shangbin Jiao Han Liu Ding Liu Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Department of Mechanical Industrial and Aerospace Engineering Concordia University

Forest fire detection has great practical significance in actual production and ***, many current solutions are still not reliable in practice and usually affected by many *** paper presents a forest fire detection method based on deep learning approach using aerial images taken by Unmanned Aerial Vehicles(UAVs).We train a full image fire classifier by exploiting YOLOv3, a latest fast and accurate real-time object detection algorithm using deep learning neural ***, the feature map of a certain size is obtained by feature extraction network, such as 13×*** the input image is divided into 13×13 grid ***, if the central coordinate of an object in the ground truth falls in a grid cell, the grid cell will predict the object, because each grid cell will predict a fixed number of bounding *** the largest bounding box with ground truth IOU(Intersection Over Union) is used to predict *** fire patch detector developed in this paper obtains 91% mAP(mean Average Precision) on the data sets used and the FPS(Frames Per Second) average can reach 80.

关键词： Forest fire detection YOLOv3 deep learning Unmanned Aerial Vehicle(UAV)

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Sensorless Speed control of PMSMs based on an Improved Particle Filter

Sensorless Speed Control of PMSMs based on an Improved Parti...

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International Conference on Electrical, control and Instrumentation Engineering (ICECIE)

作者： Hai-Peng Ren Zi-Yuan Nan Jie Li Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China Xi'an University of Technology Xi'an China

ISBN: (纸本)9781728139401

Position sensors in permanent magnet synchronous motor (PMSM) are restrained in some applications because of the space restriction and the reliability of the system. A marginalized particle filter (MPF) can used to staminate the speed of the motor by combining a Kalman filter (KF) with a particle filter (PF). In the MPF algorithm, the rotor position of the permanent magnet synchronous motor (PMSM) is represented by a set of particles, and the rotor speed associated with each particle is estimated by using the KF. The PF here is used to handle the non-Gaussianity and nonlinearity of the system. In this paper, the uniform distribution of particles is proposed to replace the traditional Gaussian distribution of particles in the PF to get better performance at the low-speed range. The motor drive system prototype is built using a TMS320F28335 digital signal processor as a controller core. The proposed improved PF is used in the sensorless speed vector control PMSM system. The experimental results show that the proposed PF with a uniform distribution of initial particles enables more accurate speed estimation in the low-speed range compared to the conventional Gaussian distribution, while increasing number of particles also helps to improve the accuracy.

关键词： particle filter sensorless motor control initial distribution Particle filters Permanent magnet synchronous machines Sensors Gaussian distribution PARTICLE DISTRIBUTION Uniform distribution position sensor particles Speed Estimation

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Design of intelligent Drilling system Software Framework and Data Architecture Based on MVC Pattern

Design of Intelligent Drilling System Software Framework and...

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第三十八届中国控制会议

作者： Peilun Ouyang Weihua Cao Min Wu Chao Gan Fawen Wang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System Hubei Institute of Urban Geological Engineering

Drilling system software is crucial for the complex geological drilling process due to its vital role in improving the drilling efficiency and safety. In this paper, a Model-View-controller(MVC) pattern-based software framework and data architecture of an intelligent drilling system are proposed. First, four main functional requirements, namely, data fusion and visualization, safety assessment and efficiency calculation, efficiency and safety optimization, and coordination control have been analyzed. After that, a four-layers is established based on the above analysis and MVC pattern. Finally, a new online data architecture has been presented at the end of this paper. The proposed software framework and data architecture form a basis for the monitoring of the drilling process.

关键词： Model-View-controller intelligent Drilling Software Framework Data Architecture

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Load curve modeling based on behavior analysis of distributed power customers 4

Load curve modeling based on behavior analysis of distribute...

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2019 4th Asia Conference on Power and Electrical Engineering, ACPEE 2019

作者： Han, Xinyang Zhang, Yu Jiao, Yuqiao Zhang, Yue Qu, Yanjing Ding, Min State Grid Energy Research Institute Beijing102200 China School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System Wuhan430074 China State Grid Shanghai Municipal Electric Power Company Shanghai200122 China

As renewable power generation directly affects the customers' traditional electricity behavior and then offsets the power load, this paper proposes a load curve modeling method for renewable power customers based on the behavior analysis. Firstly, customers' active behavior is represented by the quantity of active customer households. Based on the analysis of customer behaviors, a modeling method for the quantity of active customer households is proposed based on Markov Chain Monte Carlo method. Then, with the inputs as the quantity of active customer households and time of photovoltaic power generation, an inference model based on fuzzy logic is proposed to get the quantity of customer household starting electrical appliances. By combing the average usage time of electrical appliances, load characteristics are analyzed based on usage state of electrical appliance of distributed power customers. Finally, the simulation results verify the effectiveness of the proposed method. © Published under licence by IOP Publishing Ltd.

关键词： Fuzzy logic

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Event-Based Leader-Follower Consensus for Linear Multi-Agent systems with Adaptive Weighting under Directed Communication Topologies

Event-Based Leader-Follower Consensus for Linear Multi-Agent...

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Asian control Conference

作者： Limin Zhang Jian Sun Guanyu Lai Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China Guanyu Lai is with the Faculty of Automation Guangdong University of Technology Guangzhou Guangdong China

ISBN: (纸本)9781728102634

In this paper, a novel distributed event-triggered scheme is proposed to solve the problem of the leader-following consensus for a class of multi-agent systems with linear dynamics under directed topology. At first, a sufficient condition of the leader-following consensus for multi-agent systems based on the distributed event-trigger controller is presented. Furthermore, we proof the multi-agent system can achieve consensus with the proposed distributed event-triggered control protocols and can exclude the Zeno behavior. Finally, We have applied the designed event-triggered communication strategy and controller to vehicle platooning, and the effectiveness and efficiency of the proposed approach is simulated in the prescan.

关键词： Multi-agent systems Topology Couplings Protocols Integrated circuits Indexes

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Robust human-computer interaction for unstable camera systems

Robust human-computer interaction for unstable camera system...

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作者： Zhu, Hao You, Qing Chen, Wenjie School of Automation Beijing Institute of Technology Beijing100081 China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China

A lot of vision systems have been embedded in devices around us, like mobile phones, vehicles and UAVs. Many of them still need interactive operations of human users. However, specifying accurate object information could be a challenging task due to video jitters caused by camera shakes and target motions. In this paper, we first collect practical hand drawn bounding boxes on real-life videos which are captured by hand-held cameras and UAV-based cameras. We give a deep look into human-computer interactive operations on unstable images. The collected data shows that human input suffers heavy deviations which are harmful to interaction accuracy. To achieve robust interactions on unstable platforms, we propose a target-focused video stabilization method which utilizes a proposal-based object detector and a tracking-based motion estimation component. This method starts with a single manual click and outputs stabilized video stream in which the specified target stays almost stationary. Our method removes not only camera jitters but also target motions simultaneously, therefore offering an comfortable environment for users to do further interactive operations. The experiments demonstrate that the proposed method effectively eliminates image vibrations and significantly increases human input accuracy. © Copyright 2018 The Institute of Electronics Information and Communication Engineers.

关键词： Cameras

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An Improved Version of DMOEA-εC for Many-objective Optimization Problems: IDMOEA-εC

An Improved Version of DMOEA-εC for Many-objective Optimiza...

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第三十八届中国控制会议

作者： Juan Li Bin Xin School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology

The decomposition strategy and the ε-constraint method are two important strategies in the field of multi-objective optimization. DMOEA-εC first attempts to incorporate the ε-constraint method into the decomposition strategy and solve a multi-objective optimization problem(MOP) via optimizing a series of scalar constrained subproblems collaboratively with the help of information from neighboring subproblems. However, given the inefficiency of applying DMOEA-εC to deal with many-objective optimization problems(MaOPs), a two-stage upper bound vectors generation procedure is proposed to generate widely spread upper bound vectors in a high-dimensional space. Besides, a boundary points maintenance mechanism is put forward to remedy the diversity loss of a population in DMOEA-εC. Based on the above, DMOEA-εC with the two-stage upper bound vectors generation procedure and the boundary points maintenance mechanism, named as IDMOEA-εC, is presented for MaOPs. IDMOEA-εC is compared with four state-of-the-art many-objective evolutionary algorithms, including HypE, NSGA-Ⅲ, MOEADD, and Two Arch2. Experimental studies demonstrate that IDMOEA-εC outperforms or performs competitively against these algorithms on the majority of sixteen DTLZ test instances with up to 10 objectives.

关键词： Many-objective optimization decomposition ε-constraint method two-stage upper bound vectors generation procedure boundary points maintenance mechanism

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Distribution system state estimation: an overview of recent developments

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Frontiers of Information Technology & Electronic Engineering 2019年第1期20卷 4-17页

作者： Wang Gang Giannakis Georgios B Chen Jie Sun Jian Department of Electrical and Computer Engineering and Digital Technology Center University of Minnesota USA Minneapolis MN 55455 School of Automation Beijing Institute of Technology Beijing 100081 Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081

In the envisioned smart grid, high penetration of uncertain renewables, unpredictable participation of (industrial) customers, and purposeful manipulation of smart meter readings, all highlight the need for accurate, fast, and robust power system state estimation (PSSE). Nonetheless, most real-time data available in the current and upcoming transmission/distribution systems are nonlinear in power system states (i.e., nodal voltage phasors). Scalable approaches to dealing with PSSE tasks undergo a paradigm shift toward addressing the unique modeling and computational challenges associated with those nonlinear measurements. In this study, we provide a contemporary overview of PSSE and describe the current state of the art in the nonlinear weighted least-squares and least-absolutevalue PSSE. To benchmark the performance of unbiased estimators, the Cramer-Rao lower bound is developed. Accounting for cyber attacks, new corruption models are introduced, and robust PSSE approaches are outlined as well. Finally, distribution system state estimation is discussed along with its current challenges. Simulation tests corroborate the effectiveness of the developed algorithms as well as the practical merits of the theory.

关键词： State estimation Cramer-Rao bound Feasible point pursuit Semidefinite relaxation Proximal linear algorithm Composite optimization Cyber attack Bad data detection

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