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Variational Bayesian Learning based Joint Localization and Channel Parameter Estimation in Wireless Sensor Networks with Distance-dependent Noise

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IEEE Transactions on Vehicular Technology 2024年第5期74卷 6877-6891页

作者： Li, Yunfei Luo, Yiting Tan, Weiqiang Li, Chunguo Ma, Shaodan Yang, Guanghua Anhui Polytechnic University Department of Electrical Engineering Wuhu China Guangzhou University School of Computer Science and Cyber Engineering Guangzhou China Southeast University School of Information Science and Engineering Nanjing China Purple Mountain Laboratories Nanjing China University of Macau State Key Lab. of Internet of Things for Smart City and the Dept. of Elec. and Computer Engineering Taipa China Jinan University School of Intelligent Systems Science and Engineering Zhuhai519070 China

This paper focuses on the challenge of jointly optimizing location and path loss exponent (PLE) in distancedependent noise. Departing from the conventional independent noise model used in localization and path loss exponent estimation problems, we consider a more realistic model incorporating distance-dependent noise variance, as revealed in recent theoretical analyses and experimental results. The distance-dependent noise introduces a complex noise model with unknown noise power and PLE, resulting in an exceptionally challenging nonconvex and nonlinear optimization problem. In this study, we address a joint localization and path loss exponent estimation problem encompassing distance-dependent noise, unknown parameters, and uncertainties in sensor node locations. To surmount the intractable nonlinear and non-convex objective function inherent in the problem, we introduce a variational Bayesian learning-based framework that enables the joint optimization of localization, path loss exponent, and reference noise parameters by leveraging an effective approximation to the true posterior distribution. Furthermore, the proposed joint learning algorithm provides an iterative closed-form solution and exhibits superior performance in terms of computational complexity compared to existing algorithms. Computer simulation results demonstrate that the proposed algorithm approaches the performance of the Bayesian Cramer-Rao bound (BCRB), achieves localization performance comparable to the (maximum likelihood-Gaussian message passing) ML-GMP algorithm in some cases, and outperforms the other comparison algorithm in all cases. © 1967-2012 IEEE.

关键词： Iterative methods

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Data-Driven Stabilization for a Class of Unknown Switched Linear systems with Asynchronism 43

Data-Driven Stabilization for a Class of Unknown Switched Li...

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43rd Chinese control Conference, CCC 2024

作者： Qi, Wan-Ling Liu, Kun-Zhi Cheng, Xiao-Lin Wang, Rui Dalian University of Technology School of Control Science and Engineering Dalian116024 China Dalian University of Technology Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian116024 China Dalian University of Technology School of Aeronautics and Astronautics Dalian116024 China

ISBN: (纸本)9789887581581

This brief investigates the data-driven stabilization for a class of unknown switched linear systems in both continuous and discrete time. We assume that the switching signal is known but the system matrices of each subsystem are unknown and belong to some sets described by finite noisy input-state data. Data-driven parameterization of each unknown subsystem is built on the instantaneous bound of the external disturbance rather than the energy bound. The closed-loop stability is guaranteed by adopting a controller-mode-dependent Lyapunov function and the resulting stability conditions are data-based rather than model-based. The switching signals are arbitrary as long as they satisfy the average dwell time (ADT) condition that derived from noisy data. Two numerical examples are presented to illustrate how to enhance the feasibility of the proposed methods. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Stabilization

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ESO-Based Data Driven Set-Point Learning control for Nonlinear batch Processes with PD-Type Feedback control Structure Subject to Nonrepetitive Uncertainties* 13

ESO-Based Data Driven Set-Point Learning Control for Nonline...

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13th IEEE Data Driven control and Learning systems Conference, DDCLS 2024

作者： Ahmad, Naseem Hao, Shoulin Liu, Tao Gong, Yihui Zhang, Jiyan Wang, Haixia Zhu, Yong Dalian University of Technology Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian116024 China Institute of Advanced Control Technology Dalian University of Technology Dalian116024 China School of Biomedical Engineering Dalian University of Technology Dalian116024 China

ISBN: (纸本)9798350361674

In this paper, an extended state observer (ESO) based data-driven set-point learning control (DDSPLC) scheme is proposed for nonlinear batch processes configured with an inherent PD-type control loop, so as to actively suppress the adverse effect of nonrepetitive external disturbances and nonidentical initial resetting conditions, by only utilizing the availab.e process input/output data. The controlled process is firstly reformulated as an iterative dynamic linearization data model (IDLDM) with an extra generalized disturbance, where the unknown pseudo partial derivative and the generalized disturbance are, respectively, estimated by a projection-like algorithm and iterative ESO along the batch direction. By virtue of the estimated PPD and generalized disturbance, a set-point learning updating law with adaptive learning gain is then developed to optimize the tracking performance from batch-to-batch, by tuning the set-point command of the closed-loop PD-type control. Robust convergence analysis for the established closed-loop learning system is analyzed rigorously. The effectiveness and superiority of the proposed scheme are verified by an illustrative example. © 2024 IEEE.

关键词： State estimation

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Synchronized UAV Group Flight control under Data Rate Limitations and Actuator Saturation 7

Synchronized UAV Group Flight Control under Data Rate Limita...

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7th Scientific School: Dynamics of Complex Networks and their Applications, DCNA 2023

作者： Andrievsky, Boris Zaitceva, Luliia St. Petersburg State University Control of Complex Systems Lab. Institute for Problems in Mechanical Engineering of Ras Department of Applied Cybernetics Saint Petersburg Russia St. Petersburg State University St. Petersburg Electrotechnical University ''LETI" Control of Complex Systems Lab. Institute for Problems in Mechanical Engineering of Ras Department of Applied Cybernetics Saint Petersburg Russia

ISBN: (纸本)9798350305746

This work specifically addresses the challenges associated with information transfer between agents in pursuit of desired control objectives. Seamless communication is crucial, especially during formation synchronization, as delays can lead to disintegration. Additionally, large-scale systems may face string or mesh instability, where state deviations increase. This work aims to advance decentralized control in multi-agent systems with complex information graph structures, considering nonlinear limitations on the control signal. A sequential nonlinear corrective unit is employed to mitigate this effect. The present study incorporates data rate limitations on information exchange between UAVs in formation. An adaptive coding/decoding procedure is utilized for data transfer, and the minimal data transmission rate required for maintaining formation stability is numerically evaluated. © 2023 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Adaptive Differentially Private Robust Federated Learning Against Backdoor Attacks 1

Adaptive Differentially Private Robust Federated Learning Ag...

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1st International Conference on intelligent Manufacturing and Cloud Computing, ICIMCC 2024

作者： Yao, Ruixiang Wen, Hong Hou, Wenjing Ma, Wendi Sun, Fan Zhao, Ziang School of Aeronautics and Astronautics University of Elec.Science and Tech. of China Chengdu611731 China Aircraft Swarm Intelligent Sensing and Cooperative Control Key Lab. of Sichuan Province UESTC 611731 China Intelligent IoT Communication Technology Engineering Research Center of Sichuan Province UESTC 611731 China

ISBN: (纸本)9781643685779

In federated learning systems, malicious attackers can manipulate training datasets by injecting backdoor triggers to achieve data poisoning. Addressing this vulnerability, this paper proposes a new defense method, the adaptive differential privacy stochastic gradient descent (ADP-SGD) algorithm, which increases the Euclidean distance between malicious and benign updates to enhance aggregation efficiency. Experiments were conducted on typical datasets, and the results show that combining ADP-SGD with the m-Krum aggregation algorithm can effectively defend against backdoor attacks in complex attack environments. While ensuring the accuracy of the main task, it significantly reduces the success rate of backdoor attacks, especially under the condition of unknown proportions of malicious participants, proving to be effective and robust. © 2025 The Authors.

关键词： Federated learning

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Design of Orthogonal Polyphase Codes for MIMO Radar Using an Enhanced Salp Swarm Algorithm 1

Design of Orthogonal Polyphase Codes for MIMO Radar Using an...

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1st International Conference on intelligent Manufacturing and Cloud Computing, ICIMCC 2024

作者： Pang, Yu Zhao, Runhui Wen, Hong Wang, Yongfeng Feng, Xuewei Tang, Tao Zhao, Ziang Ma, Wendi School of Aeronautics and Astronautics University of Elec.Science and Tech. of China Chengdu611731 China Aircraft Swarm Intelligent Sensing and Cooperative Control Key Lab. of Sichuan Province UESTC 611731 China Intelligent IoT Communication Technology Engineering Research Center of Sichuan Province UESTC 611731 China

ISBN: (纸本)9781643685779

This paper presents the design of highly orthogonal waveforms focusing on minimizing autocorrelation sidelobes and cross-correlation peaks. An enhanced Salp Swarm Algorithm is proposed to improve global search capabilities through refined population initialization and leader position updates. The feasibility and benefits of this approach are demonstrated through practical implementation. © 2025 The Authors.

关键词： MIMO radar

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Driving Performance Analysis for Connected Vehicle Platoons: Velocity Perturbation and Fuel Consumption

Driving Performance Analysis for Connected Vehicle Platoons:...

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2023 IEEE International Conference on Unmanned systems, ICUS 2023

作者： Zhao, Yihan Duan, Xuting Zhou, Jianshan Zhang, Long School of Transportation Science and Engineering Beihang University Beijing China State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beijing China State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Zhongguancun Laboratory Beijing China National Key Laboratory of Science and Technology on Information System Security Institute of Systems Engineering Beijing China

ISBN: (纸本)9798350316308

Vehicle platoon is one of the concrete manifestations of multi-vehicle cooperative control and intelligent transportation. However, the velocity perturbation in the driving process will bring about stability and safety problems. The connected autonomous vehicles (CAVs) can obtain the motion status of the lead vehicle in real time and respond to it in time, which is of far-reaching significance to platoon control. Based on this, this paper focuses on the longitudinal driving strategy of connected autonomous vehicle platoons. Specifically, we provide a discrete double-integral model controller for each vehicle in a generic scenario, and the controller performs acceleration and deceleration control at each timeslot according to the state of the vehicle in front and its own state. Simulation experiments are designed by varying the size of the platoon and the number of connected autonomous vehicles. The experimental results show that the introduction of connected autonomous vehicles can effectively suppress the platoon velocity perturbation, increase the stability of the platoon driving, and significantly reduce the fuel consumption at the same time. © 2023 IEEE.

关键词： Autonomous vehicles

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A predictive frontal and oblique collision mitigation system for autonomous vehicles

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ASME Letters in Dynamic systems and control 2021年第4期1卷 041012页

作者： Sun, Chuanyang Eskandarian, Azim Department of Mechanical Engineering Autonomous Systems and Intelligent Machines Lab. Virginia Tech BlacksburgVA24061 United States

This paper presents a collision mitigation system for an unavoidable collision with an arbitrary oncoming obstacle vehicle. A set of candidate trajectories are generated by a modelbased method and a hierarchical efficient collision-checking method is applied to check the potential collision between the predicted trajectory of the obstacle vehicle and the candidate trajectories of the ego vehicle. A novel method based on the vehicle polygon is applied to identify the specific impact location of the vehicle body. The predicted Delta-V and the identified impact location are combined to evaluate the outcome severity of the upcoming accident for each candidate trajectory. Based on the evaluated results, a path with the least damage would be selected and executed to mitigate the collision. Simulation and analysis are performed to investigate the performance of the presented system in a high-speed scenario of a detailed vehicle model. Copyright © 2021 by ASME.

关键词： Accidents

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Occupational Exposure of Therapeutic Staff in Deep Transcranial Magnetic Stimulation 35

Occupational Exposure of Therapeutic Staff in Deep Transcran...

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35th General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2023

作者： Lu, Mai Ueno, Shoogo Lanzhou Jiaotong University Key Lab. of Opto-Electronic Technology and Intelligent Control of Ministry of Education Lanzhou China The University of Tokyo Graduate School of Medicine Department of Biomedical Engineering Tokyo Japan

ISBN: (纸本)9789463968096

This study presented dosimetry analysis for therapeutic staff exposed to magnetic pulses from double cone and Halo-circular assembly (HCA) coils during deep transcranial magnetic stimulation (dTMS) applications. The magnetic field and the induced electric field in realistic human body model exposure to dTMS coils have been obtained by employing the impedance method. The exposure level by both double cone and HCA coils were assessed according to the limits defined by the International Commission on Non-Ionizing Radiation Protection (ICNIRP) guidelines. The HCA coil generates higher exposure to therapeutic staff compared to that of double cone coil. © 2023 International Union of Radio Science.

关键词： Electric fields

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Trajectory Planning for Autonomous Overtaking on Curved Roads with Avoidance of Human Driving Vehicles and Static Obstacles

Trajectory Planning for Autonomous Overtaking on Curved Road...

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2023 IEEE International Conference on Unmanned systems, ICUS 2023

作者： Shao, Chen Duan, Xuting Zhou, Jianshan Zhao, Dezong School of Transportation Science and Engineering Beihang University Beijing China State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beijing China State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Zhongguancun Laboratory Beijing China James Watt School of Engineering University of Glasgow Glasgow United Kingdom

ISBN: (纸本)9798350316308

A proposed obstacle avoidance trajectory planning method for autonomous vehicles considers social behavior characteristics to address the interaction problem with human drivers in mixed traffic environments. The method integrates graph theory and centrality functions to classify and predict driver behavior, employing model predictive control (MPC) to plan the autonomous vehicle's trajectory. By combining these social behaviors, the method ensures safe completion of the driving task based on probability. Experimental results from an interactive obstacle avoidance scenario in a curved environment confirm the successful completion of the task, validating the proposed method's feasibility and effectiveness, supporting its potential for real-world application. © 2023 IEEE.

关键词： Model predictive control

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