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HUID:DBN-Based Fingerprint Localization and Tracking System with Hybrid UWB and IMU

China Communications 2023年第2期20卷 139-154页

作者： Junchang Sun Rongyan Gu Shiyin Li Shuai Ma Hongmei Wang Zongyan Li Weizhou Feng School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China Peng Cheng Laboratory Shenzhen 518055China School of Information and Communications Engineering University of Electronic Science and Technology of ChinaChengdu 611731China

High-precision localization technology is attracting widespread attention in harsh indoor *** this paper,we present a fingerprint localization and tracking system to estimate the locations of the tag based on a deep belief network(DBN).In this system,we propose using coefficients as fingerprints to combine the ultra-wideband(UWB)and inertial measurement unit(IMU)estimation linearly,termed as a HUID *** particular,the fingerprints are trained by a DBN and estimated by a radial basis function(RBF).However,UWB-based estimation via a trilateral method is severely affected by the non-line-of-sight(NLoS)problem,which limits the localization *** tackle this problem,we adopt the random forest classifier to identify line-of-sight(LoS)and NLoS ***,we adopt the random forest regressor to mitigate ranging errors based on the identification results for improving UWB localization *** experimental results show that the mean square error(MSE)of the localization error for the proposed HUID system reduces by 12.96%,50.16%,and 64.92%compared with that of the existing extended Kalman filter(EKF),single UWB,and single IMU estimation methods,respectively.

关键词： Ultra-wideband(UWB) inertial measurement unit(IMU) fingerprints positioning NLoS identification estimated errors mitigation deep belief network(DBN) radial basis function(RBF)

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Enhanced UAV Pursuit-Evasion Using Boids Modelling:A Synergistic Integration of Bird Swarm Intelligence and DRL

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Computers, Materials & Continua 2024年第9期80卷 3523-3553页

作者： Weiqiang Jin Xingwu Tian Bohang Shi Biao Zhao Haibin Duan Hao Wu School of Information and Communications Engineering Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an710049China China Academy of Electronics and Information Technology China Electronics Technology Group Corporation(CETC)Beijing100041China Department ofAutomatic Control School of Automation Science and Electrical EngineeringBeihangUniversityBeijing100191China

TheUAV pursuit-evasion problem focuses on the efficient tracking and capture of evading targets using unmanned aerial vehicles(UAVs),which is pivotal in public safety applications,particularly in scenarios involving intrusion monitoring and *** address the challenges of data acquisition,real-world deployment,and the limited intelligence of existing algorithms in UAV pursuit-evasion tasks,we propose an innovative swarm intelligencebased UAV pursuit-evasion control framework,namely“Boids Model-based DRL Approach for Pursuit and Escape”(Boids-PE),which synergizes the strengths of swarm intelligence from bio-inspired algorithms and deep reinforcement learning(DRL).The Boids model,which simulates collective behavior through three fundamental rules,separation,alignment,and cohesion,is adopted in our *** integrating Boids model with the Apollonian Circles algorithm,significant improvements are achieved in capturing UAVs against simple evasion *** further enhance decision-making precision,we incorporate a DRL algorithm to facilitate more accurate strategic *** also leverage self-play training to continuously optimize the performance of pursuit *** experimental evaluation,we meticulously designed both one-on-one and multi-to-one pursuit-evasion scenarios,customizing the state space,action space,and reward function models for each *** simulations,supported by the PyBullet physics engine,validate the effectiveness of our proposed *** overall results demonstrate that Boids-PE significantly enhance the efficiency and reliability of UAV pursuit-evasion tasks,providing a practical and robust solution for the real-world application of UAV pursuit-evasion missions.

关键词： UAV pursuit-evasion swarm intelligence algorithm Boids model deep reinforcement learning self-play training

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Time-Varying Formation Tracking control of Heterogeneous Multi-Agent Systems With Intermittent Communications and Directed Switching Networks

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 294-296页

作者： Yuhan Wang Zhuping Wang Hao Zhang Huaicheng Yan the Shanghai Research Institute for Intelligent Autonomous Systems Tongji University the National Key Laboratory of Autonomous Intelligent Unmanned Systems the Frontiers Science Center for Intelligent Autonomous System of Ministry of Education the College of Electronic and Information Engineering the Department of Control Science and Engineering Tongji University the Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education the School of Information Science and Engineering East China University of Science and Technology

Dear Editor,This letter is concerned with the problem of time-varying formation tracking for heterogeneous multi-agent systems(MASs) under directed switching networks. For this purpose, our first step is to present so... 详细信息

关键词： Switches Topology Observers Formation control Event detection Switched systems Multi-agent systems control theory Autonomous systems Stability

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Optimal control of differential quasivariational-hemivariational inequalities with applications

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science China Mathematics 2024年第11期67卷 2587-2606页

作者： Dong-ling Cai Stanislaw Migórski Yi-bin Xiao School of Mathematical Sciences University of Electronic Science and Technology of ChinaChengdu 611731China College of Applied Mathematics Chengdu University of Information TechnologyChengdu 610225China Chair of Optimization and Control Jagiellonian University in KrakowKrakow 30348Poland

In this paper,we study a new class of differential quasivariational-hemivariational inequalities of the elliptic *** problem consists of a system coupling the Cauchy problem for an ordinary differential equation with the variational-hemivariational inequalities,unilateral constraints,and history-dependent ***,based on the Minty formulation and the continuity of the solution map of a parametrized quasivariational-hemivariational inequality,and a fixed point theorem for a history-dependent operator,we prove a result on the ***,we examine optimal control problems for differential quasivariational-hemivariational inequalities,including a time-optimal control problem and a maximum stay control problem,for which we show the existence of *** all the optimal control problems,the system is controlled through a distributed and boundary control,a control in initial conditions,and a control that appears in history-dependent ***,we illustrate the results by considering a nonlinear controlled system for a time-dependent elliptic equation with unilateral constraints.

关键词： differential variational-hemivariational inequality unilateral constraint history-dependent operator optimal control time-optimal control maximum stay problem

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Dynamic Charging and Path Planning for UAV-Powered Rechargeable WSNs Using Multi-Agent Deep Reinforcement Learning

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IEEE Transactions on Automation science and Engineering 2025年 22卷 15610-15626页

作者： Betalo, Mesfin Leranso Leng, Supeng Seid, Abegaz Mohammed Abishu, Hayla Nahom Erbad, Aiman Bai, Xiaoshan Shenzhen University College of Mechatronics and Control Engineering Shenzhen518060 China University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Hamad Bin Khalifa University Division of Information and Computing Technology College of Science and Engineering Doha Qatar Shenzhen University College of Mechatronics and Control Engineering National Engineering Laboratory for Big Data System Computing Technology Shenzhen518060 China

Unmanned Aerial Vehicle (UAV)-powered 5G/6G networks integrated with rechargeable wireless sensor networks (RWSNs) offer promising solutions for extending system lifetime, collecting data, and providing computing services and power to sensor nodes (SNs). UAVs offer significant advantages, including exceptional mobility, cost-effective deployment, and the ability to be easily reprogrammed for a wide range of missions. However, the limited onboard power capacity of UAVs, coupled with the lack of dynamic and intelligent charging station (CS) management and inefficient path planning, can lead to SN failure in dynamic mobile environments. To address these challenges, we propose an energy-efficient laser-charged UAV (LCU)-enabled RWSN environment, wherein UAVs, powered by laser beams from ground-based stations, provide services, collect data, and transfer energy to SNs. We formulate a joint optimization problem involving power allocation, dynamic charging strategy (DCS), and path planning to minimize task completion time and sensor node death time. Given the NP-hard nature of the problem, we employ a stochastic game model based on a Markov decision process (MDP) for its solution. To solve this problem, we propose a deep reinforcement learning (DRL) based algorithm that enables real-time charging scheduling decisions while optimizing network performance. We introduce a multi-agent double deep Q-network (MA-DDQN) model to determine the optimal trajectories for all UAVs in large and complex environments. Simulation results demonstrate that the MA-DDQN approach outperforms state-of-the-art techniques, showing significant improvements in terms of average delay, energy consumption, and task completion time. © 2004-2012 IEEE.

关键词： Stochastic models

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Efficient Implementation of Aperture Fill Time Correction for Wideband Array Using the Low-complexity Keystone Transform

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Progress In Electromagnetics Research C 2023年 136卷 101-112页

作者： Wang, Lin Jiang, Yiyang Jiang, Yu Tian, Baoli Shen, Mingwei College of Computer and Information Engineering Hohai University Nanjing China Unit 95438 of PLA Air Force Meishan China Science and Technology on Electronic Information Control Laboratory Chengdu China

In order to remove the influence of the aperture fill time (AFT) for wideband array, the scaling principle of the Keystone (KT) transform is applied to eliminate the linear coupling between spatial domain and frequency domain of wideband array signal. However, the classic KT transform is implemented by interpolation Sinc which is difficult to apply in engineering and leads to the serious problem of insufficient data. To address this, a realization of the low-complexity KT transform is presented, and it is implemented using only the Chirp-z transform (CZT) and fast Fourier transforms (FFT). Additionally, an Autoregressive (AR) model is proposed to compensate the insufficient data for each range, and the order of AR is estimated by the rank of the signal covariance matrix. Simulation results demonstrate that the proposed algorithm significantly reduces computational burden and improves the performance of wideband array beamforming. © 2023, Electromagnetics Academy. All rights reserved.

关键词： Fast Fourier transforms

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An Interval Multi-Objective Evolutionary Generation Algorithm for Product Design Change Plans in Uncertain Environments

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IEEE Transactions on Evolutionary Computation 2024年第3期29卷 1-1页

作者： Zheng, Rui-zhao Zhang, Yong Sun, Xiao-yan Gong, Dun-wei Gao, Xiao-zhi School of Information and Control Engineering China University of Mining and Technology Xuzhou China College of Automation and Electronic Engineering Qingdao University of Science and Technology Qingdao China School of Computing University of Eastern Finland Kuopio Finland

Design change is an important issue in complex product development projects. In a complex product with numerous parts (also known as components), the change of one key part may spread to other parts associated with it, generating a chain reaction throughout the entire project. Therefore, it is necessary to select a suitable change plan involving only fewer crucial parts in order to enhance the product’s performance, minimize change cost, and reduce change duration/time. Focusing on the case where the correlation strength between parts cannot be accurately obtained, in this paper we study an interval multi-objective evolutionary algorithm for finding excellent design change plans. Firstly, on the basis of the established multi-layer product network with interval correlation weights, an interval multi-objective optimization model of the product design change planning problem is established, where three new objective functions regarding product performance, carbon trading cost and supply risk are defined. Then, a constraint multi-objective evolutionary algorithm based on interval Pareto dominance is proposed to search for optimal change plans. Several novel operators, including the problem characteristic-guided population update strategy, the probability-based interval Pareto dominance, and the interval constraint handling strategy, are developed to enhance the algorithm’s performance. Finally, the proposed algorithm is compared with eight existing algorithms on the two design change cases, experimental results revealed its effectiveness. IEEE

关键词： Evolutionary algorithms

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Resilient filtering for discrete-time system with multipath data packet dropout and quantization

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Asian Journal of control 2023年第4期25卷 3067-3082页

作者： Wang, Jian Chang, Xiao-Heng Xiong, Jun Li, Zhi-Min School of Information Science and Engineering Wuhan University of Science and Technology Wuhan Hubei China School of Electronic and Control Engineering North China Institute of Aerospace Engineering Langfang Hebei China

This paper proposes a two-step method to design a resilient filter and two dynamic quantizers for a class of discrete-time systems. In the first step, a filter is designed to make the discrete-time system stochastically stable, and make the (Figure presented.) norm between the filtering error and the external disturbance less than a given level. In the second step, two dynamic quantizers, which quantify the measurement output signal and the performance output signal, respectively, are designed under the condition that the filter gain matrices are obtained. In addition, the filter adopted in this paper takes the randomly occurring uncertainty into consideration, and the quantizers are designed by an inequality scaling technique which can reduce the complexity of linear matrix inequalities. Furthermore, this paper also considers the data packet dropout that may occur during network transmission. Finally, considering the data packet dropout and quantization of measurement output signal and performance output signal, the effectiveness of the proposed filter design method is demonstrated by two simulation examples. © 2023 Chinese Automatic control Society and John Wiley & Sons Australia, Ltd.

关键词： Linear matrix inequalities

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Rydberg-Induced Topological Solitons in Three-Dimensional Rotation Spin–Orbit-Coupled Bose–Einstein Condensates

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Chinese Physics Letters 2024年第9期41卷 9-14页

作者： Yang Wang Jinlong Cui Hongkai Zhang Yuan Zhao Siliu Xu Qin Zhou Key Laboratory of Optoelectronic Sensing and Intelligent Control Hubei University of Science and TechnologyXianning 437100China School of Electronic and Information Engineering Hubei University of Science and TechnologyXianning 437100China School of Biomedical Engineering and Imaging Xianning Medical CollegeHubei University of Science and TechnologyXianning 437100China Research Center of Nonlinear Science School of Mathematics and Physical SciencesWuhan Textile UniversityWuhan 430200China

We present a novel approach for generating stable three-dimensional(3D)spatiotemporal solitons(SSs)within a rotating Bose–Einstein condensate,incorporating spin–orbit coupling(SOC),a weakly anharmonic potential and cold Rydberg *** intricate system facilitates the emergence of quasi-stable 3D SSs with topological charges|m|≤3 in two spinor components,potentially exhibiting diverse spatial *** findings reveal that the Rydberg long-range interaction,spin–orbit coupling,and rotational angular frequency exert significant influence on the domains of existence and stability of these ***,the Rydberg interaction contributes to a reduction in the norm of topological solitons,while the SOC plays a key role in stabilizing the SSs with finite topological *** research of SSs exhibits potential applications in precision measurement,quantum information processing,and other advanced technologies.

关键词： Rydberg topological Einstein

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Strengthened Dominance Relation NSGA-Ⅲ Algorithm Based on Differential Evolution to Solve Job Shop Scheduling Problem

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Computers, Materials & Continua 2024年第1期78卷 375-392页

作者： Liang Zeng Junyang Shi Yanyan Li Shanshan Wang Weigang Li School of Electrical and Electronic Engineering Hubei University of TechnologyWuhan430068China Hubei Key Laboratory for High-Efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Hubei University of TechnologyWuhan430068China School of Information Science and Engineering Wuhan University of Science and TechnologyWuhan430081China

The job shop scheduling problem is a classical combinatorial optimization challenge frequently encountered in manufacturing *** involves determining the optimal execution sequences for a set of jobs on various machines to maximize production efficiency and meet multiple *** Non-dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ)is an effective approach for solving the multi-objective job shop scheduling ***,it has some limitations in solving scheduling problems,including inadequate global search capability,susceptibility to premature convergence,and challenges in balancing convergence and *** enhance its performance,this paper introduces a strengthened dominance relation NSGA-Ⅲ algorithm based on differential evolution(NSGA-Ⅲ-SD).By incorporating constrained differential evolution and simulated binary crossover genetic operators,this algorithm effectively improves NSGA-Ⅲ’s global search capability while mitigating pre-mature convergence ***,it introduces a reinforced dominance relation to address the trade-off between convergence and diversity in NSGA-Ⅲ.Additionally,effective encoding and decoding methods for discrete job shop scheduling are proposed,which can improve the overall performance of the algorithm without complex *** validate the algorithm’s effectiveness,NSGA-Ⅲ-SD is extensively compared with other advanced multi-objective optimization algorithms using 20 job shop scheduling test *** experimental results demonstrate that NSGA-Ⅲ-SD achieves better solution quality and diversity,proving its effectiveness in solving the multi-objective job shop scheduling problem.

关键词： Multi-objective job shop scheduling non-dominated sorting genetic algorithm differential evolution simulated binary crossover

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