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7th International Symposium on Autonomous systems, ISAS 2024

作者： Liu, Shanlin Zhang, Yingwei Zhao, Xudong Wang, Hesheng Northeastern University College of Information Science and Engineering Shenyang China Northeastern University State Laboratory of Synthesis Automation of Process Industry Shenyang China Dalian University of Technology Faculty of Electronic Information and Electrical Engineering Dalian China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9798350363173

In this article, an adaptive event-triggered asymp¬totically fault-tolerant control (FTC) issue for nonlinear systems with actuator faults is investigated. An extended neural networks (NNs) technique is introduced to estimate unknown functions of the system under consideration. Compared with traditional NNs that ignore approximation errors, the proposed extended NNs further processes approximation errors, reducing the conservatism of the proposed algorithm. Then, within the framework of backstepping method, a new adaptive control strategy is developed by combining event-triggered mechanism (ETM) and bound estimation (BE) approach, which ensures the asymptotic convergence of system states while also reducing the transmission of unnecessary information, thus improving the utilization of communication resources. At the same time, the designed controller eliminates the adverse effects of actuator failures and system nonlinear terms. Finally, a simulation example of a single-link robot system is provided to demonstrate that the developed control strategy can ensure that all signals are bounded and system states are asymptotically convergent. © 2024 IEEE.

关键词： Approximation algorithms

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RIS-Aided Localization Method Based on DNN-SSA Fusion in NLOS Scenarios 5

RIS-Aided Localization Method Based on DNN-SSA Fusion in NLO...

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5th International Conference on Computer, Big Data and Artificial Intelligence, ICCBD+AI 2024

作者： Luo, Yujia Hu, Qingsong Cheng, Yuanxun Yuan, Shuya Zhang, Yuansheng China University of Mining and Technology School of Information and Control Engineering Xuzhou China State Key Laboratory of Intelligent Optimized Manufacturing in Mining & Metallurgy Process Beijing China Beijing Key Laboratory of Process Automation in Mining & Metallurgy Beijing China

ISBN: (纸本)9798331533991

With the advent of the 6G era, precise positioning and reliable, energy-efficient data transmission have become critical for the Internet of Things. However, high-frequency signals like millimeter-wave and terahertz are easily obstructed, making traditional LOS-based methods ineffective in complex environments. To overcome this, NLOS localization methods and Reconfigurable Intelligent Surfaces offer promising solutions by dynamically modifying the wireless environment. This paper introduces a Direct Position Determination method that integrates Deep Neural Networks (DNN) with the Sparrow Search Algorithm (SSA) to tackle the challenges of high computational complexity and low localization accuracy in RIS-aided systems. An NLOS scenario with RIS is established, and a far-field channel model is derived. The method uses DNN to model the nonlinear relationship between the likelihood function and user position, and then employs SSA to optimize the DNN-based fitness function, efficiently solving the objective function. Experimental results show that the DNN-SSA method consistently achieves high localization accuracy across different scenarios, even at low SNR levels, demonstrating its effectiveness and potential for 6G high-precision localization. © 2024 IEEE.

关键词： Deep neural networks

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Investigation on Slug Flow Parameters Based on PIV Phase Discrimination

Investigation on Slug Flow Parameters Based on PIV Phase Dis...

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2023 Tianjin University-IET Electrical and information Engineering Doctoral Forum, TJU IET 2023

作者： Wang, Haixia Xue, Ting College of Electrical and Information Engineering Tianjin Key Laboratory of Process Measurement and Control Tianjin University Tianjin China

ISBN: (纸本)9781839539824

Investigation of synchronously acquiring multiple parameters holds valuable insights into flow characteristics. When employing particle image velocimetry in gas-liquid slug flow, the integration of phase discrimination assumes an unequivocal role. This not only facilitates the separation of gas and liquid phases to distinctly capture velocity field distributions but also enables the extraction of characteristic parameters beyond velocity from gas or liquid phase. In this study, in addition to velocity measurements employing particle image velocimetry, structural parameters measurement methodologies within slug flow, such as liquid film thickness and elongated bubble length, are introduced based on phase discrimination results. By leveraging the inherent relationships among flow rate parameters, the measurement parameters are cross-validated based on experimental findings to assess the feasibility of the method. Ultimately, an exploration and analysis of flow characteristics in slug flow under different flow conditions are undertaken. © The Institution of Engineering & Technology 2023.

关键词： Velocity measurement

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Data Augmentation of Ship Wakes in SAR Images Based on Improved CycleGAN

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Journal of Shanghai Jiaotong university(Science) 2024年第4期29卷 702-711页

作者： YAN Congqiang GUO Zhengyun CAI Yunze Department of Automation Shanghai Jiao Tong UniversityShanghai200240China Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai200240China China Airborne Missile Academy Luoyang471009HenanChina National Key Laboratory of Air-Based Information Perception and Fusion Luoyang471000HenanChina

The study on ship wakes of synthetic aperture radar(SAR)images holds great importance in detecting ship targets in the *** this study,we focus on the issues of low quantity and insufficient diversity in ship wakes of SAR images,and propose a method of data augmentation of ship wakes in SAR images based on the improved cycle-consistent generative adversarial network(CycleGAN).The improvement measures mainly include two aspects:First,to enhance the quality of the generated images and guarantee a stable training process of the model,the least-squares loss is employed as the adversarial loss function;Second,the decoder of the generator is augmented with the convolutional block attention module(CBAM)to address the issue of missing details in the generated ship wakes of SAR images at the microscopic *** experiment findings indicate that the improved CycleGAN model generates clearer ship wakes of SAR images,and outperforms the traditional CycleGAN models in both subjective and objective aspects.

关键词： synthetic aperture radar(SAR) ship wake data augmentation cycle-consistent generative adversarial network(CycleGAN) attention mechanism

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Multi-Objective Loosely Synchronized Search for Multi-Objective Multi-Agent Path Finding with Asynchronous Actions

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Journal of Shanghai Jiaotong university(Science) 2024年第4期29卷 667-677页

作者： DU Haikuo GUO Zhengyu ZHANG Lulu CAI Yunze Department of Automation Shanghai Jiao Tong UniversityShanghai200240China Key Laboratory of System Control and Information Processing Ministry of EducationShanghai200240China China Airborne Missile Academy LuoyangHenan471000China National Key Laboratory of Air-based Information Perception and Fusion LuoyangHenan471000China

In recent years,the path planning for multi-agent technology has gradually matured,and has made breakthrough *** main difficulties in path planning for multi-agent are large state space,long algorithm running time,multiple optimization objectives,and asynchronous action of multiple *** solve the above problems,this paper first introduces the main problem of the research:multi-objective multi-agent path finding with asynchronous action,and proposes the algorithm framework of multi-objective loose synchronous(MO-LS)*** combining A*and M*,MO-LS-A*and MO-LS-M*algorithms are respectively *** completeness and optimality of the algorithm are proved,and a series of comparative experiments are designed to analyze the factors affecting the performance of the algorithm,verifying that the proposed MO-LS-M*algorithm has certain advantages.

关键词： multi-agent path finding multi-objective path planning asynchronous action loosely synchronous search

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Edge computing aileron mechatronics using antiphase hysteresis Schmitt trigger for fast flutter suppression

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control Theory and Technology 2025年第1期23卷 153-160页

作者： Tangwen Yin Dan Huang Xiaochun Zhang Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information Processing of Ministry of EducationShanghai200240China School of Aeronautics and Astronautics Shanghai Jiao Tong UniversityShanghai200240China Control Division Shanghai Aircraft Design and Research InstituteShanghai200210China

An aileron is a crucial control surface for *** jitter or shaking caused by the aileron mechatronics could have catastrophic consequences for the aircraft’s stability,maneuverability,safety,and *** paper presents a robust solution in the form of a fast flutter suppression digital control logic of edge computing aileron mechatronics(ECAM).We have effectively eliminated passive and active oscillating response biases by integrating nonlinear functional parameters and an antiphase hysteresis Schmitt *** findings demonstrate that self-tuning nonlinear parameters can optimize stability,robustness,and *** the same time,the antiphase hysteresis Schmitt trigger effectively rejects flutters without the need for collaborative navigation and *** hardware-in-the-loop simulation results confirm that this approach can eliminate aircraft jitter and shaking while ensuring expected stability and *** conclusion,this nonlinear aileron mechatronics with a Schmitt positive feedback mechanism is a highly effective solution for distributed flight control and active flutter rejection.

关键词： Aileron Edge computing Flutter suppression Mechatronics Nonlinear hysteresis control Positive feedback

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An Improved High Precision 3D Semantic Mapping of Indoor Scenes from RGB-D Images

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Computer Modeling in Engineering & Sciences 2023年第12期137卷 2621-2640页

作者： Jing Xin Kenan Du Jiale Feng Mao Shan Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of TechnologyXi’an710048China Australian Centre for Field Robotics The University of SydneySydney2006Australia

This paper proposes an improved high-precision 3D semantic mapping method for indoor scenes using RGB-D *** current semantic mapping algorithms suffer from low semantic annotation accuracy and insufficient real-time *** address these issues,we first adopt the Elastic Fusion algorithm to select key frames from indoor environment image sequences captured by the Kinect sensor and construct the indoor environment space ***,an indoor RGB-D image semantic segmentation network is proposed,which uses multi-scale feature fusion to quickly and accurately obtain object labeling information at the pixel level of the spatial point cloud ***,Bayesian updating is used to conduct incremental semantic label fusion on the established spatial point cloud *** also employ dense conditional random fields(CRF)to optimize the 3D semantic map model,resulting in a high-precision spatial semantic map of indoor *** results show that the proposed semantic mapping system can process image sequences collected by RGB-D sensors in real-time and output accurate semantic segmentation results of indoor scene images and the current local spatial semantic ***,it constructs a globally consistent high-precision indoor scenes 3D semantic map.

关键词： 3D semantic map online reconstruction RGB-D images semantic segmentation indoor mobile robot

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RESEARCH ON GAIT RECOGNITION BY USING 1DCNN BASED ON LOWER LIMB KINEMATIC POSTURE DATA 10

RESEARCH ON GAIT RECOGNITION BY USING 1DCNN BASED ON LOWER L...

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10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Li, Mu Ma, Chao Wang, Shaohong Key Laboratory of Modern Measurement and Control Technology Ministry of Edu. Beijing Information Science and Technology University Beijing China Beijing Key Laboratory of Measurement and Control of Mechanical and Electrical System Beijing Information Science and Technology University Beijing China

ISBN: (纸本)9781837242672

Gait recognition refers to the process of realizing the detection of human identity or health status and other information according to the characteristics of human plantar pressure, video images or human dynamics indicators. With the advantages of non-contact, non-aggression, no need for cooperation and easy to collect, gait recognition technology has been widely used in recent years in the field of public security criminal investigation, medical care, intelligent transportation and other fields. In this study, to meet the needs of gait recognition, IMU sensors are used to acquire human lower limb motion posture data and wavelet transform is used to decompose several components. Then the components were determined and the optimized 1DCNN model is used to carry out gait recognition research. The results showed that the optimized 1DCNN model for gait recognition task exhibits excellent performance with up to 95% accuracy, 96% recall and Fl value, as well as good computational efficiency, which is valuable for clinical automatic gait recognition analysis, rehabilitation engineering and criminal investigation work. Although there are some errors in some gait classifications, our study provides directions for further optimization of the algorithm to improve the accuracy and robustness of gait recognition. © The Institution of Engineering & Technology 2024.

关键词： Crime

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Preserving Topology of Network systems: Metric, Analysis, and Optimal Design

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IEEE Transactions on Automatic control 2024年第6期70卷 3540-3555页

作者： Li, Yushan Wang, Zitong He, Jianping Chen, Cailian Guan, Xinping Shanghai Jiao Tong University Department of Automation Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

Preserving the topology from being inferred by external adversaries has become a paramount security issue for network systems (NSs), and adding random noises to the nodal states provides a promising way. Nevertheless, recent works have revealed that the topology cannot be preserved under i.i.d. noises in the asymptotic sense. How to effectively characterize the non-asymptotic preservation performance still remains an open issue. Inspired by the deviation quantification of concentration inequalities, this paper proposes a novel metric named trace-based variance-expectation ratio. This metric effectively captures the decaying rate of the topology inference error, where a slower rate indicates better non-asymptotic preservation performance. We prove that the inference error will always decay to zero asymptotically, as long as the added noises are non-increasing and independent (milder than the i.i.d. condition). Then, the optimal noise design that produces the slowest decaying rate for the error is obtained. More importantly, we amend the noise design by introducing one-lag time dependence, achieving the zero state deviation and the non-zero topology inference error in the asymptotic sense simultaneously. Extensions to a general class of noises with multi-lag time dependence are provided. Comprehensive simulations verify the theoretical findings. © 1963-2012 IEEE.

关键词： Network topology

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Online Optimization in Power systems With High Penetration of Renewable Generation:Advances and Prospects

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 839-858页

作者： Zhaojian Wang Wei Wei John Zhen Fu Pang Feng Liu Bo Yang Xinping Guan Shengwei Mei Key Laboratory of System Control and Information Processing Ministry of Education of ChinaDepartment of AutomationShanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Power System and the Department of Electrical Engineering Tsinghua UniversityBeijing 100084China Institute of High Performance Computing(IHPC) Agency for Science Technology and Research(A*STAR)Singapore 138632Singapore

Traditionally,offline optimization of power systems is acceptable due to the largely predictable loads and reliable *** increasing penetration of fluctuating renewable generation and internet-of-things devices allowing for fine-grained controllability of loads have led to the diminishing applicability of offline optimization in the power systems domain,and have redirected attention to online optimization ***,online optimization is a broad topic that can be applied in and motivated by different settings,operated on different time scales,and built on different theoretical *** paper reviews the various types of online optimization techniques used in the power systems domain and aims to make clear the distinction between the most common techniques *** particular,we introduce and compare four distinct techniques used covering the breadth of online optimization techniques used in the power systems domain,i.e.,optimization-guided dynamic control,feedback optimization for single-period problems,Lyapunov-based optimization,and online convex optimization techniques for multi-period ***,we recommend some potential future directions for online optimization in the power systems domain.

关键词： optimization Lyapunov optimization online convex optimization online optimization optimization-guided control

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