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Data Driven control and Learning Systems (DDCLS)

作者： Kaixin Liu Xin Zhong Ping Chen Yun Dai Yi Liu The State Key Lab for Electronic Testing Technology North University of China China Department of Information and Communication Engineering North University of China Taiyuan China College of Mechanical Engineering Nantong Vocational University Nantong China Institute of Process Equipment and Control Engineering Zhejiang University of Technology Hangzhou China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

In recent years, various methods for processing and analyzing thermographic data have been applied in non-destructive testing to improve the visibility of defects. Representatively, traditional linear dimensionality reduction methods (e.g. principal component analysis) have achieved good results in thermographic data analysis. In this work, a slow feature thermography (SFT) method for non-destructive evaluation of defects in composite materials. Thermographic data can be regarded as a continuous time series generated by an infrared imager at different moments. Slow feature analysis algorithm is subsequently used to extract slow features of the thermal image sequence. Slow features refer to features that are unchanged or slowly changing in time-series data, such as the background of a thermal image. By extracting the slow features of data, the inhomogeneous background, noise and defect features contained in thermal images can be effectively distinguished. Test results on carbon fiber reinforced polymer specimens demonstrate the feasibility and effectiveness of the SFT method.

关键词： Image recognition Composite materials Time series analysis Infrared imaging Feature extraction Thermal noise Thermal analysis

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Air-Ground Collaborative control for Angle-Specified Heterogeneous Formations

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-13页

作者： Chen, Liangming Xiao, Jiaping Teo, Clarence Wei Rui Li, Jianqing Feroskhan, Mir School of System Design and Intelligent Manufacturing and Shenzhen Key Laboratory of Control Theory and Intelligent Systems Southern University of Science and Technology Shenzhen China school of Mechanical and Aerospace Engineering Nanyang Technological University Singapore Singapore College of Communication Engineering Hangzhou Dianzi University Hangzhou China

The need for better search and rescue capabilities has led to the increased demand for collaborative aerial-ground multi-robot deployments. However, most existing solutions require high communication bandwidth or bulky sensor equipment that is not suitable especially for aerial robots. To make the execution of these tasks more efficient, this paper proposes an angle-specified heterogeneous leader-follower formation framework consisting of unmanned aerial vehicles (UAVs) flying in a 3D space and ground robots moving in a 2D plane. The UAVs are controlled to maintain a desired angle-specified formation with the first three UAVs as the leaders forming a triangular shape and the remaining UAVs as the followers. The follower UAVs only need direction measurements to track the leader UAVs. For the ground robots, two leader robots track the UAV group and determine the orientation and scale of the ground formation, while the follower robots track the leader robots using only direction measurements. The proposed heterogeneous formation framework is energy-efficient as most robots only require low-cost and lightweight direction measurements. The stability of the proposed formation control algorithms is proved and validated through various physical application experiments. IEEE

关键词： Multi agent systems

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Fast Finite-Time Adaptive Neural control for Pure-Feedback Stochastic Nonlinear Systems

Fast Finite-Time Adaptive Neural Control for Pure-Feedback S...

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Memristive Computing and Applications (ICMCA), IEEE International Conference on

作者： Ximei Zhao Hanyu Zhang Lijun Shao Lili Huang Jiao Li School of Intelligent Manufacturing and Control Engineering Qilu Institute of Technology Jinan China Collaborative Innovation Center of Memristive Computing Application(CICCA) Qilu Institute of Technology Jinan China College of Computer and Communication Engineering Qilu Institute of Technology Jinan China

In this article, we solve the fast finite-time stabilization as well as adaptive neural control design issues for a class uncertain stochastic nonlinear systems. By employing the mean value theorem, the pure-feedback form can be transformed into strict-feedback case. Firstly, a new fast finite-time control scheme is proposed in virtue of generalizing the fast finite-time adaptive control strategy for deterministic systems to the stochastic case. Next, a novel adaptive neural control strategy is developed to simultaneously deal with the stochastic nonlinear systems with completely unknown nonlinearities as well as the disturbances term. Then, stability analysis have been given based on a Jensen's inequality.

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Robust H∞ controller Design With Regional Pole-Placement for Quarter Car Active Suspension System

Robust H∞ Controller Design With Regional Pole-Placement fo...

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control Conference (ANZCC), Australian and New Zealand

作者： Sonali Singh Ganta Jane Gladys P P Gouri Jitendra Kumar Goyal Ankit Sachan Surender Hans Shubhi Purwar Neeraj Gupta Department of Electical Engineering M.N. National Institute of Technology Allahabad Prayagraj India Department of Control and Automation School of Electrical Engineering Vellore Institute of Technology Vellore Tamil Nadu India Department of Electronics and Communication Engineering Poornima College of Engineering Jaipur India Graduate School of Advanced Science & Engineering Hiroshima University Japan Department of Electical Engineering Ajay Kumar Garg Engineering College Ghaziabad India

In the modern world, automobile suspension holds crucial importance in uplifting a cars ride comfort and handling ability. Active suspension can doubtless enhance the driving quality and traveler comfort at the same time. Its a fourth-order advanced system that requires a highly accurate and precise robust control technique. This work presents a highly robust $H_{\infty}$ controller proposed for a quarter car active suspension system and a comparison of it with the prevailing LQR controller design. Also, the design criteria to enhance the transient performance of the system consist of the concept of regional pole placement. controller behavior is examined through simulation setup using MATLAB/Simulink. Simulation results are shown to explain the efficacy of the developed design.

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INTELLIGENT TRACKING AND NAVIGATING MOVING OBJECTS IN A SMART ENVIRONMENT USING IOT NETWORK 1

INTELLIGENT TRACKING AND NAVIGATING MOVING OBJECTS IN A SMAR...

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1st International Conference on Technologies for Smart Green Connected Society 2021, ICTSGS 2021

作者： Parvathi, R. Kumar, T.Ch. Anil Nandhakumar, A. Arshad, Haqqani Singh, Ajith B. Department of Information Technology School of Computing Science Hindustan Institute of Technology and Science Padur Chennai India Department of Mechanical Engineering Vignan's Foundation for Science Technology and Research Vadlamudi Dt. Andhra Pradesh Guntur India Department of Electronics and Communication Engineering Dhaanish Ahmed Institute of Technology Chennai India Department of Mechanical Engineering Yanbu Industrial Collge Yanbu Western Region Saudi Arabia Department- Instrumentation and Control Engineering Sri Krishna College of Technology Coimbatore India

ISBN: (纸本)9781607685395

Internet of things (IoT) constitutes the combinations of sensors, controllers, actuators, connectivity. Tracking and navigating moving objects are crucial tasks for security as well as a secure and smart environment. By using the sensory data, location of objects can be identified then that sensory data will be transferred to controllers for the further processes. One pivot role of the system is to identify the trajectory and location of the object using the speed, velocity, acceleration, maps etc and this can be done by machine learning programs. Analyzing service required, prediction of the trajectory and real-world knowledge of maps or locations, To avoid the loop-carry dependency, service request parameters are dynamically changed to locate relevant virtual objects. In order to track moving items, this study provides an architecture based on IoT self-aware environment technology that facilitates the tracking and allocation of relevant virtual objects. © The Electrochemical Society

关键词： IoT loop-carry dependency machine learning object identification self-aware environment sensory data

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Design and Stability Analysis of Non-smooth Integral Sliding Surface for Coupled-Tank System with Matching/Non-matching Disturbance

Design and Stability Analysis of Non-smooth Integral Sliding...

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control Conference (ANZCC), Australian and New Zealand

作者： Sonali Singh Ankit Sachan Jitendra Kumar Goyal Shubhi Purwar Neeraj Gupta Ganta Jane Gladys P P Gouri Surender Hans Department of Electical Engineering M.N. National Institute of Technology Allahabad Prayagraj India Graduate School of Advanced Science & Engineering Hiroshima University Japan Department of Control and Automation School of Electrical Engineering Vellore Institute of Technology Vellore Tamil Nadu India Department of Electical Engineering Ajay Kumar Garg Engineering College Ghaziabad India Department of Electronics and Communication Engineering Poornima College of Engineering Jaipur India

This paper examine the challenges posed by conventional sliding mode design in the presence of matching/nonmatching disturbances. Previously designed approaches have proven inadequate in offering an efficient and straightforward solution to non-matching disturbances. To overcome this, a novel sliding mode control strategy centered on a non-smooth integral sliding manifold is introduced. The newly proposed sliding manifold possesses two crucial characteristics. Firstly, it functions transform to a reduced-order disturbance observer by autonomously estimating the mismatched disturbances, eliminating the need for an additional observer design. Secondly, the system consistently initiates its operation from the sliding surface, eliminating any reaching phase dynamics. As a result, the system trajectory remains resilient to disturbances right from the outset. To validate the effectiveness of the proposed method, it is simulated for a coupled tank system.

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A Generic Layer Pruning Method for Signal Modulation Recognition Deep Learning Models

arXiv

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arXiv 2024年

作者： Lu, Yao Zhu, Yutao Li, Yuqi Xu, Dongwei Lin, Yun Xuan, Qi Yang, Xiaoniu The Institute of Cyberspace Security College of Information Engineering Zhejiang University of Technology Hangzhou China The Binjiang Institute of Artificial Intelligence Zhejiang University of Technology Hangzhou310056 China The Institute of Computing Technology Chinese Academy of Sciences Beijing China The College of Information and Communication Engineering Harbin Engineering University Harbin China The PCL Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen518000 China Utron Technology Company Ltd. Hangzhou310056 China The Science and Technology on Communication Information Security Control Laboratory Jiaxing China

—With the successful application of deep learning in communications systems, deep neural networks are becoming the preferred method for signal classification. Although these models yield impressive results, they often come with high computational complexity and large model sizes, which hinders their practical deployment in communication systems. To address this challenge, we propose a novel layer pruning method. Specifically, we decompose the model into several consecutive blocks, each containing consecutive layers with similar semantics. Then, we identify layers that need to be preserved within each block based on their contribution. Finally, we reassemble the pruned blocks and fine-tune the compact model. Extensive experiments on five datasets demonstrate the efficiency and effectiveness of our method over a variety of state-of-the-art baselines, including layer pruning and channel pruning methods. Copyright © 2024, The Authors. All rights reserved.

关键词： Deep neural networks

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Experimental demonstration of 8190-km long-haul semiconductor-laser chaos synchronization induced by digital optical communication signal

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光：科学与应用（英文版） 2025年第2期14卷 333-343页

作者： Anbang Wang Junli Wang Lin Jiang Longsheng Wang Yuncai Wang Lianshan Yan Yuwen Qin Key Laboratory of Photonic Technology for Integrated Sensing and Communication Ministry of Education of ChinaGuangdong University of TechnologyGuangzhou 510006China Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi ProvinceTaiyuan 030024China Institute of Advanced Photonics Technology School of Information EngineeringGuangdong University of TechnologyGuangzhou 510006China Guangdong Provincial Key Laboratory of Information Photonics Technology Guangdong University of TechnologyGuangzhou 510006China Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi ProvinceTaiyuan 030024China College of Physics and Optoelectronics Taiyuan University of TechnologyTaiyuan 030024China Center for Information Photonics and Communications Southwest Jiaotong UniversityChengdu 610031China Key Laboratory of Photonic Technology for Integrated Sensing and Communication Ministry of Education of ChinaGuangdong University of TechnologyGuangzhou 510006China Institute of Advanced Photonics Technology School of Information EngineeringGuangdong University of TechnologyGuangzhou 510006China Guangdong Provincial Key Laboratory of Information Photonics Technology Guangdong University of TechnologyGuangzhou 510006China

Common-signal-induced synchronization of semiconductor lasers have promising applications in physical-layer secure transmission with high speed and compatibility with the current fiber ***,we propose an ultra-long-distance laser synchronization scheme by utilizing random digital optical communication signal as the common drive *** utilizing the long-haul optical coherent communication techniques,high-fidelity fiber transmission of the digital drive can be achieved and thus ultra-long-distance synchronization is *** were implemented with distributed feedback lasers injected by a random-digital phase-modulated drive *** show that high-quality synchronization can be achieved as the drive signal rate is larger than the laser relaxation frequency and the transmission bit error ratio is below a critical *** synchronization over 8191-km fiber transmission was experimentally *** to traditional common-signal-induced synchronization using analog drive signal such as chaos,the distance is increased by 8 times,and complicated hardware devices for channel impairment compensation are no longer *** addition,the proposed method does not sacrifice communication capacity like traditional methods which need a channel to transmit analog drive *** is therefore believed that this common-digital-signal induced laser synchronization paves a way for secure backbone and submarine transmission.

关键词： communication semiconductor synchronization signal digital chaos laser demonstration experimental induced

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Adaptive neural network output-feedback tracking control for switched nonlinear ship maneuvering systems with time delays under arbitrary switching

Adaptive neural network output-feedback tracking control for...

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2022 Chinese Automation Congress, CAC 2022

作者： Li, Zhenhua Ren, Xiangxuan Dong, Botao Chen, Hong Zhang, Weidong SJTU Sanya Yazhou Bay Institute of Deepsea Science and Technology Sanya572024 China Department of Automation Shanghai Jiao Tong University Shanghai200240 China College of Mechatronics and Control Engineering Shenzhen University Shenzhen518061 China School of Information and Communication Engineering Hainan University Haikou570228 China

ISBN: (纸本)9781665465335

This paper focuses on the tracking control problem for switched nonlinear ship maneuvering time-delay systems with only a heading angle available by adaptive neural network (NN) output feedback. Using the backstepping method, an adaptive NN control mechanism is designed to solve the problem cooperated with the state observer. The uncertain terms of the system are approximated by NNs, and the state observer is designed to estimate the yaw rate and rudder angle. The unknown time delays are overcome by exploiting the common Lyapunov-Krasovskii functionals (CLKFs). Combined with error transformation, the proposed control method guarantees that i) all of the signals for the system are semi-global uniformly ultimately boundedness (SGUUB) under arbitrary switching;and, ii) the tracking error of system output keeps within a small neighborhood around the origin. The results of simulation results are shown to demonstrate the feasibility of the control strategy. © 2022 IEEE.

关键词： Time delay

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Energy Minimization Oriented Resource Allocation for Relay Assisted NOMA-MEC Networks

Energy Minimization Oriented Resource Allocation for Relay A...

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IEEE Conference on Global communications (GLOBECOM)

作者： Qianru Wang Liping Qian Yuan Wu Xiaoniu Yang College of Information Engineering Zhejiang University of Technology Hangzhou China State Key Laboratory of Internet of Things for Smart City University of Macau China Science and Technology on Communication Information Security Control Laboratory Jiaxing China Institute of Cyberspace Security Zhejiang University of Technology Hangzhou China

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

With the growing demand for image transmission, there is a need for solutions that offer low energy consumption and low latency. In this paper, we present a novel relay-assisted system based on non-orthogonal multiple access (NOMA) and mobile edge computing (MEC). Our proposed system compresses images at the device end, decompresses them at either a relay or a cloud server (CS). The primary objective is to minimize system energy consumption under given task delay constraints. Considering that this is a non-convex optimization problem, we solve it by decomposing it into a continuous subproblem and a discrete subproblem. To solve the continuous subproblem, we convexify it by introducing new parameters and change variables to get the optimal the computing power of devices, relay and CS, sampling rate of devices, transmission power of devices and relay. To solve the discrete subproblem, we propose a cross-entropy (CE) algorithm to obtain the optimal decompression decision and subcarrier allocation decision. Simulation results demonstrate the accuracy and effectiveness of our algorithm in optimizing total energy consumption compared to the Linear Interactive and General Optimizer (LINGO) and frequency division multiple access (FDMA) methods.

关键词： Performance evaluation NOMA Energy consumption Image coding Multi-access edge computing Simulation Optimization methods Resource management Servers Relays

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