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Parallel Seeds:From Foundation Models to Foundation Intelligence for Agricultural Sustainability

IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 481-484页

作者： Laiyi Fu Shunkang Ling Danyang Wu Mengzhen Kang Fei-Yue Wang Hequan Sun the Shool of Automation Science and Engineering Faculty of Electronic and Information Engineering Xi'an Jiaotong University the College of Information Engineering Northwest A&F University IEEE the State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences

THE development of agriculture faces significant challenges due to population growth, climate change, land depletion, and environmental pollution, threatening global food security [1]. This necessitates the development of sustainable agriculture, where a fundamental step is crop breeding to improve agronomic or economic traits, e.g., increasing yields of crops while decreasing resource usage and minimizing pollution to the environment [2].

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A Fractional-Order Nonlinear Backstepping controller Design for Current-controlled Maglev System

arXiv

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arXiv 2025年

作者： Astekin, Dorukhan Adigüzel, Fatih Yıldız Technical University Electric-Electronic Faculty Department of Control and Automation Engineering İstanbul Turkey

The magnetic levitation system (Maglev) is a nonlinear system by which an object is suspended with no support other than magnetic fields. The main control perspective of the Maglev system is to levitate a steel ball in air by the electromagnetic force. However, the Maglev system has highly nonlinear dynamics which is inconvenient in the sense of sensitive control/regulation of its nonlinear dynamics. In this paper, the nonlinear backstepping controller based on the fractional-order derivative is proposed for the control of the nonlinear current-controlled Maglev system. After, the system dynamics and fractional-order backstepping controller design are given, the asymptotic stability of the closed-loop system is proved by employing the Lyapunov theory. Some computer-based numerical experiments are carried out to show the effectiveness of the proposed controller for the control of Maglev system. © 2025, CC BY.

关键词： Magnetic levitation

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Data-Driven Group Formation control of Cyber-Physical Systems via Distributed Cloud Computing

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical Systems 2025年 3卷 341-350页

作者： Ren, Hongru Long, Yinren Li, Hongyi Huang, Tingwen Guangdong University of Technology School of Automation Guangdong-Hong Kong Joint Laboratory for Intelligent Decision and Cooperative Control Guangdong Provincial Key Laboratory for Intelligent Decision and Cooperative Control Guangzhou510006 China Southwest University College of Electronic and Information Engineering Chongqing400715 China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China

This paper investigates the group formation control problem for cyber-physical systems (CPSs) with random communication constraints. The distributed cloud computing system is constructed to divide agents into groups and establish communication between agents. A data-driven predictive control strategy is proposed by combining networked predictive control and model-free adaptive control method. The desired group formation control performance can be achieved and the three-channel random communication constraints of CPSs are actively compensated. Thisstrategy does not require the system model and relies solely on the system's I/O data for adaptive learning. Further analyses concludes the conditions for simultaneous reach stability and group formation of the closed-loop CPSs using the data-driven predictive control strategy. The effectiveness of the proposed strategy is validated by simulation results. © 2023 IEEE.

关键词： Distributed cloud

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Research on twistor-based complex collisions of a quadrotor UAV suspension system

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International Journal of Dynamics and control 2025年第3期13卷 1-14页

作者： Zhou, Jiaxing Chen, Yuhao Deng, Yifan Li, Qing School of Electric Engineering and Automation Xiamen University of Technology 600 Ligong Road Fujian Xiamen361024 China Xiamen Key Laboratory of Frontier Electric Power Equipment and Intelligent Control 600 Ligong Road Fujian Xiamen361024 China Faculty of Electronic and Information Engineering Xi’an Jiaotong University No. 28 Xianning West Shaanxi Xi’an710075 China School of Aerospace Northwestern Polytechnical University No. 127 Youyi West Road Xi’an710072 China

The disturbances of wind fields and collisions introduce additional uncertain disturbance during the collision deicing process of UAV suspended load. The UAV suspension system’s position and attitude models are established separately based on traditional method such as Newton–Euler. Consequently, the introduction of multiple algebraic methods, including position vector and Euler angle, increases computational complexity. Accordingly, the system response delays and the control accuracy cannot meet the mission requirements. Therefore, it is essential to find a method for integrated position–attitude modeling and control. To address this problem, this paper proposes a collision dynamic model for a quadrotor UAV suspension system based on twistor. This twistor provides a unified description of translational and rotational motion. In addition, the introduction of twistor avoids the normalization constraints and parameter redundancy in dual quaternion. The stability of the UAV cannot be ensured due to the uncertain disturbances introduced by the wind field and collisions. As a result, there is a need to design a strong disturbance rejection controller. To mitigate impacts of these disturbances, a fuzzy sliding mode controller within the twistor framework is presented. Lyapunov theory and LaSalle invariance principles are used to prove the stability of the system. The simulation demonstrates that the fuzzy sliding mode controller within the twistor framework effectively ensures the stability and adaptability of the quadrotor UAV suspended system under the disturbances of wind fields and collisions. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Disturbance rejection

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Frequency shift-based 3D shape measurement in the presence of strong inter-reflection

Frequency shift-based 3D shape measurement in the presence o...

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2024 International Conference on Optical and Photonic engineering, icOPEN 2024

作者： Miao, Huisi Liu, Wan Yan, Ziyu Xu, Weidong Zhang, Dongbo Zhang, Hui School of Automation and Electronic Information Xiangtan University Xiangtan411105 China Xiangtan Electric Manufacturing Co..Ltd. Xiangtan411105 China National Engineering Research Center of Robot Visual Perception and Control Technology School of Robotics Hunan University Changsha410082 China

ISBN: (数字)9781510688117

ISBN: (纸本)9781510688100

Traditional fringe projection profilometry (FPP) struggles with robust imaging and high-precision three-dimensional (3D) reconstruction in complex lighting environments with strong inter-reflection. This paper proposes a method combining frequency-shifted fringe projection and epipolar constraint to achieve high-precision 3D profilometry in such scenarios. First, environmental light interference is mitigated and the maximum fringe frequency is reduced through window function analysis (WFA) and a four-step phase-shifting (PS). Then, direct and indirect illumination are separated in the Fourier domain. Direct illumination positions are identified using threshold segmentation and epipolar geometry constraint, enhancing imaging robustness in strong inter-reflection contexts. Experimental results demonstrate that the method constructs direct and indirect illumination feature models, accurately obtaining direct illumination information and eliminating multi-path interference. Additionally, in tests with complex geometrical surfaces, imaging efficiency and robustness significantly improve, with effective point cloud data increasing by over 30% and planar accuracy improving by 50%. © 2025 SPIE.

关键词： Light interference

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BAT Optimized SMC for Continuous Stirred Tank Reactor

BAT Optimized SMC for Continuous Stirred Tank Reactor

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IEEE Information Technology and Mechatronics engineering Conference (ITOEC)

作者： Husam E. Elfadel Haroon Congzhi Huang School of Control and Computer Engineering North China Electric Power University Beijing China Department of Electrical and Electronic Engineering Faculty of Engineering Omdurman Islamic University Khartoum Sudan

ISBN: (数字)9798331529482

ISBN: (纸本)9798331529499

This topic proposed a Sliding Mode control (SMC) strategy utilizing the BAT Algorithm (BAT-SMC) for regulating concentration and temperature in a Continuous Stirred Tank Reactor (CSTR) system. The SMC is designed to maintain concentration (CA) and temperature (T) within desired setpoints by adapting sliding surfaces in the presence of disturbances and system uncertainties. The BAT Algorithm enhances the SMC by optimizing control parameters, reducing chattering effects, and improving tracking accuracy. Simulations validate the efficacy of BAT-SMC, showing improved dynamic performance for both concentration and temperature control compared to other controllers.

关键词： Uncertainty Mechatronics Heuristic algorithms Optimal control Coolants Temperature control Continuous-stirred tank reactor Feeds Information technology Sliding mode control

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Prescribed-Time Mitigation of False Data Attacks in Microgrid Load Frequency control

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IEEE Transactions on Smart Grid 2025年

作者： Abouzeid, Said I. Chen, Y. Zaery, Mohamed Amrr, Syed Muhammad Abdelhameed, Esam H. Engineering Technology Research Center for Electric Vehicle Driving System and Safety School of Automation Engineering University of Electronic Science and Technology of China and Sichuan Province Sichuan Chengdu611731 China Aswan University Faculty of Energy Engineering Electrical Engineering Department Aswan Egypt K.A.CARE Energy Research and Innovation Center Saudi Arabia KFUPM Control and Instrumentation Engineering Department Saudi Arabia Saudi Arabia

Microgrid load frequency control (LFC) operation relies extensively on cyber networks which significantly increases their susceptibility to false data injection attacks (FDIAs) that can undermine microgrid’s stability. This paper proposes a multi-layer control framework that efficiently detects and mitigates false data injected in the actuator and measurements of the LFC. Firstly, an FDIAs detection layer based on an unknown input observer (UIO) utilizing an adaptive threshold has been proposed. An adaptive threshold aims to enhance detection sensitivity and reduce false alarms by distinguishing between actual attacks and temporal discrepancies in observer error caused by internal disturbances. Secondly, to ensure timely and accurate mitigation of FDIAs, an estimation layer utilizing a prescribed-time unknown input observer (PTUIO) has been designed. PTUIO is designed to be robust against unknown inputs and parameter uncertainty. The PTUIO employs periodic time-delayed output to estimate system states and FDIAs within a predefined time. Afterward, a two-layer robust and resilient LFC system was developed. The first layer ensures the rejection of unknown inputs, including load/generation disturbances and FDIAs based on PTUIO estimations. The second layer incorporates robust state feedback control, which stabilizes the microgrid and accurately tracks the frequency reference. The effectiveness of the proposed control system is confirmed through multiple scenarios by simulations and Hardware-in-the-loop (HIL), demonstrating its robustness and reliability in addressing challenges associated with internal disturbances, and FDIAs within the microgrid. © 2010-2012 IEEE.

关键词： Hardware-in-the-loop simulation

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Event-Triggered Neural Asynchronous control of Nonhomogeneous Markov Jump Power Systems with Hybrid Cyberattacks and Unknown States

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IEEE Transactions on Power Systems 2025年

作者： Luo, Wende Chen, Haiyang Zong, Guangdeng Zhao, Xudong Qufu Normal University School of Engineering Rizhao276826 China Tiangong University School of Control Science and Engineering Tianjin300387 China Nanjing Institute of Technology School of Automation Nanjing211167 China Dalian University of Technology Faculty of Electronic Information and Electrical Engineering Dalian116024 China

This paper studies the observer-based eventtriggered neural asynchronous control problem of nonhomogeneous Markov jump power systems (MJPSs) under hybrid cyberattacks. Both periodic denial-of-service attacks and deception attacks (DAs) are involved because of the openness of networks. An event-triggered mechanism is established to ease the network load. Besides, neural network (NN) approaches are adopted to suppress the adverse effects of DAs on nonhomogeneous MJPSs, and the hidden Markov model (HMM) is employed to capture the asynchronous phenomenon between the system mode and the controller mode. With NN approaches and HMM, an observer-based NN asynchronous controller is designed. By constructing the mode- and parameter-dependent Lyapunov function, sufficient criteria ensuring boundedness in probability for nonhomogeneous MJPSs are obtained. Then, a design algorithm is shown to simultaneously obtain the controller gains, observer gains, and event-triggering weight matrices based on the established conditions. Finally, the single-machine infinitebus power system and 3-machine 6-bus power system are applied to justify the validity of the proposed algorithm. © 1969-2012 IEEE.

关键词： Lyapunov functions

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Formation control and Obstacle Avoidance Design for Networked USV Swarm With Exogenous Disturbance Under Intermittent Communication

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IEEE Transactions on Network Science and engineering 2025年

作者： Chang, Zhenyu Zong, Guangdeng Wang, Wencheng Yue, Ming Zhao, Xudong Tiangong University School of Control Science and Engineering Tianjin300387 China Weifang University College of Machinery and Automation Weifang261061 China Dalian University of Technology School of Automotive Engineering Dalian116024 China Dalian University of Technology Faculty of Electronic Information and Electrical Engineering Dalian116024 China

This study addresses the formation control problem of under-actuated unmanned surface vehicle (USV) swarm systems and designs an obstacle avoidance strategy for navigating in obstacle environments. The intermittent communication scheme, consisting of the working period and the rest period, is introduced to reduce the communication burden and the consumption of control resources. A distributed formation control strategy is designed to guarantee the realization of the desired formation configuration. Considering the potential impact of obstacles in the operating environment, the artificial potential field repulsion obstacle avoidance method is embedded into the formation control strategy. To eliminate the impact of exogenous disturbances, a disturbance observer is established using the partially known disturbance information. Sufficient conditions are provided to ensure the uniformly ultimate boundedness of the formation error and disturbance observation error. In addition, an energy function related to the obstacle position information is designed to verify that the desired obstacle avoidance behavior can be achieved. The feasibility of theoretical analysis is validated by applying the developed control strategy to surface formation cruise missions. © 2013 IEEE.

关键词： Unmanned surface vehicles

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Machine Learning in Predicting the Impact of Filter Parameters on the Accuracy of Biosignal Measurement

Machine Learning in Predicting the Impact of Filter Paramete...

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Digital Signal Processing and its Applications (DSPA), International Conference on

作者： Yeldos A. Altay Raisa K. Uskenbayeva Abu-Alim E. Ayazbay Alexey V. Fedorov Department of Robotics and Technical Means of Automation Satbayev University Almaty Kazakhstan Institute of Automation and Information Technologies Vice-Rector Satbayev University Almaty Kazakhstan Electronic engineering Almaty University of Power Engineering and Telecomunications Almaty Kazakhstan Faculty of Control Systems and Robotics ITMO University Saint-Petersburg Russian Federation

ISBN: (数字)9798331518752

ISBN: (纸本)9798331518769

In this scientific article under consideration, a machine learning model has been developed that allows predicting the impact of filter parameters on the accuracy of measuring a biosignal - an ECG (electrocardiography) signal. For the first time, quantitative results have shown the degree of influence and the error introduced into the measured biosignal and described through dependence. The results of assessing the obtained relationship of indicators demonstrate an inverse correlation relationship that characterizes a decrease in the accuracy of measurement at the output of a high-order digital filtering system. The machine learning model is based on the linear regression method the dependence of which is approximated by the method based on least squares and visualized using a scattergram. The adequacy of the developed machine learning model was confirmed by calculating the coefficient of determination and checking its statistical significance. The developed model can be used to create new or improve existing biomedical data processing systems to increase the reliability of the results.

关键词： Accuracy Shape Filtering Biological system modeling Machine learning Biomedical measurement Electrocardiography Distortion Distortion measurement Digital filters

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