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System Class Extensions of the Modulating Function based State Reconstruction for the Advection-Diffusion-Reaction Equation

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IEEE Transactions on Automatic control 2025年

作者： Friedrich, Folke Fokken, Nils Noack, Matti Reger, Johann Institute for Automation and Systems Engineering Technische Universität Ilmenau Control Engineering Group Ilmenau98693 Germany

In this paper, the state estimation of distributed parameter systems (PDEs) using the Modulating Function Method is extended to systems of two or higher spatial dimensions with spatially varying coefficients and general boundary conditions. At the center of the PDE observer approach lies the construction and solvability analysis of systematically obtained kernel equations determining the modulating functions. Additionally, a method for the state estimation of a class of parabolic systems with time-varying and nonlinear parameters based on Volterra integral transformations is presented. Furthermore, a linearization based strategy to deal with nonlinear reaction terms is presented. The stability of the resulting iterative feedback algorithm is proven. Numerical simulations show the validity and robustness of the methodology in two simulated examples. © 1963-2012 IEEE.

关键词： Iterative methods

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H∞ Loop-shaping for Power Tracking control of Wind Turbines

arXiv

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arXiv 2025年

作者： Grapentin, Aaron Hans, Christian A. Raisch, Jörg Control Systems Group Technische Universität Berlin Germany Automation and Sensorics in Networked Systems Group University of Kassel Germany Research Cluster of Excellence Berlin Germany

In this paper, we present an advanced wind turbine control scheme for power maximization as well as for active power control, which is designed using H∞ loop-shaping. Our approach involves the synthesis of two separate controllers for two different operating modes. To ensure smooth transitions between these modes, we implement a bumpless transfer strategy that reduces transient effects. A comprehensive case study demonstrates the efficacy of our control scheme, showing significant improvements in power tracking accuracy and a reduction in mechanical wear. Moreover, our control strategy comes with robust stability guarantees. Copyright © 2025, The Authors. All rights reserved.

关键词： Wind turbines

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Dynamic modeling and simulation of blade-casing system with rubbing considering time-varying stiffness and mass of casing

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Applied Mathematics and Mechanics(English Edition) 2025年第5期46卷 849-868页

作者： Hui MA Hong GUAN Lin QU Xumin GUO Qinqin MU Yao ZENG Yanyan CHEN School of Mechanical Engineering and Automation Northeastern UniversityShenyang 110819China Key Laboratory of Vibration and Control of Aero-Propulsion Systems Ministry of Education of ChinaNortheastern UniversityShenyang 110819China Sunny Optical Technology(Group)Co.Ltd. Ningbo 315400Zhejiang ProvinceChina Aircraft Strength Institute of China Xi’an 710065China AECC Sichuan Gas Turbine Research Institute Chengdu 610500China

As a common fault of the aero-engine,the blade-casing rubbing(BCR)has the potential to cause catastrophic *** this paper,to investigate the dynamic responses and wear characteristics of the system,the laminated shell element is used to establish the finite element model(FEM)of a flexibly coated casing *** the shell element,the blade is modeled,and the surface stress of the blade is *** stress-solving method of the blade is validated through comparisons with the measured time-domain waveform of the ***,a dynamic model of a blade-flexibly coated casing system with rubbing is proposed,accounting for the time-varying mass and stiffness of the casing caused by coating *** effects of the proposed flexible casing model are compared with those of a rigid casing model,and the stress changes induced by rubbing are *** results show that the natural characteristics of the coated casing decrease due to the coating *** flexibly coated casing model is found to be more suitable for studying casing ***,the stress changes caused by rubbing are slight,and the change in the stress maximum is approximately 5%under the influence of the abrasive coating.

关键词： dynamic modeling flexibly coated casing rubbing coating wear nonlinear vibration

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Estimation of Metro Passenger Capacity Based on Passenger-Train Matching Model 3rd

Estimation of Metro Passenger Capacity Based on Passenger-Tr...

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3rd International Conference on Information control, Electrical Engineering, and Rail Transit, ICEERT 2023

作者： Mei, Zhenkun Chen, Beijia Liu, Jiajun Shao, Jiayu Zhang, Ning Suzhou Rail Transit Group Co. Ltd. Jiangsu Suzhou215004 China School of Automation Southeast University Jiangsu Nanjing210096 China Key Laboratory of Measurement and Control of Complex Engineering Systems Ministry of Education Southeast University Jiangsu Nanjing210096 China ITS Engineering Research Center Ministry of Education Southeast University Jiangsu Nanjing211189 China

ISBN: (纸本)9789819788903

In the present scenario of the ‘one-tapin-one-tapout’ operation mode in urban rail transportation, determining passenger travel trajectories is challenging, thereby decreasing the effective counting of passengers on trains. In order to address this issue, a method for calculating passenger capacity on trains was developed by analyzing passenger travel information extracted from AFC data and train timetables. First, this research estimated the components of journey time to infer and reconstruct the passenger's specific spatiotemporal travel trajectory. The passenger-train matching model was then used to assign passengers to specific trains and calculate the passenger load of different trains at each station. At last, it took Suzhou Metro Line 3 as an example and analyzed the spatiotemporal distribution of urban rail transit passenger flow on a single line based on the proposed passenger-train model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Urban transportation

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Trajectory Tracking for Directional Drilling in Underground Coal Mine Using Robust Model Predictive control 26

Trajectory Tracking for Directional Drilling in Underground ...

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26th International Conference on Industrial Technology, ICIT 2025

作者： Wu, Jiajun Lu, Chengda Li, Hao Wei, Hongchao Wu, Min School of Future Technology China University of Geosciences Wuhan430074 China School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Xi'an Research Institute Co. Ltd. China Coal Technology and Engineering Group Xi'an710077 China China Coal Research Institute Beijing100013 China

ISBN: (纸本)9798331521950

This paper studies the problem of trajectory tracking control for directional drilling in underground coal mine by devising a robust model predictive control method. First, a directional drilling trajectory extension model is obtained by the linearization of a drilling tool kinematic model through the Taylor series expansion in the borehole depth domain. Then, in view of the influence of the uncertainty of the drilling tool slope and external interference, a robust model predictive control method is introduced in the form of an optimal control problem. A sufficient condition is obtained to calculate the corresponding controller gain matrix on the premise of satisfying the stability of the closedloop control system and the H∞ performance index. At last, the effectiveness of our method is illustrated through simulation analysis. Compared with model predictive control, robust model predictive control directly incorporates the uncertainty of the drilling tool slope and external interference into the control design, enabling it to better adapt to the complex and variable underground coal mine environment. © 2025 IEEE.

关键词： Predictive control systems

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Determining the Initial In-Cylinder Gas State Based on Semi-Physical Models

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IFAC-PapersOnLine 2016年第11期49卷 454-460页

作者： Zydek, S. Casper, D. Isermann, R. Weber, A. Research Group Control Systems and Process Automation Technical University of Darmstadt Germany

Two methodologies are presented for modeling the initial in-cylinder gas state prior to the combustion. The first method is based on measured in-cylinder pressure data and allows the cylinder individual calculation of the gas mass and temperature. A physical equation for the online calculation of the polytropic exponent during the compression stroke is derived in order to receive accurate absolute pressure data from piezo based in-cylinder pressure sensors. In order to model the in-cylinder temperature an additional semi physical model is proposed to account for the heat input during the intake stroke. From the first methodology a second semi-physical model for the average in-cylinder gas mass and temperature is derived which will only need cylinder pressure data for the calibration process of the experimental model. © 2016

关键词： Engine cylinders Cylinders (shapes) Engines Gases Models Temperature Cylinder pressure data Cylinder temperatures Experimental modeling Gas mass In cylinder pressures Online calculations Polytropic exponent semi physical

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Trajectory Tracking for Directional Drilling in Underground Coal Mine Using Robust Model Predictive control

Trajectory Tracking for Directional Drilling in Underground ...

引用

IEEE International Conference on Industrial Technology (ICIT)

作者： Jiajun Wu Chengda Lu Hao Li Hongchao Wei Min Wu School of Future Technology China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan China School of Automation China University of Geosciences Wuhan China Xi'an Research Institute Co. Ltd. China Coal Technology and Engineering Group Xi'an China China Coal Research Institute Beijing China

ISBN: (数字)9798331521950

ISBN: (纸本)9798331521967

This paper studies the problem of trajectory tracking control for directional drilling in underground coal mine by devising a robust model predictive control method. First, a directional drilling trajectory extension model is obtained by the linearization of a drilling tool kinematic model through the Taylor series expansion in the borehole depth domain. Then, in view of the influence of the uncertainty of the drilling tool slope and external interference, a robust model predictive control method is introduced in the form of an optimal control problem. A sufficient condition is obtained to calculate the corresponding controller gain matrix on the premise of satisfying the stability of the closedloop control system and the $H_{\infty}$ performance index. At last, the effectiveness of our method is illustrated through simulation analysis. Compared with model predictive control, robust model predictive control directly incorporates the uncertainty of the drilling tool slope and external interference into the control design, enabling it to better adapt to the complex and variable underground coal mine environment.

关键词： Drilling Uncertainty Trajectory tracking Stability criteria Predictive models Taylor series Coal mining Trajectory Thermal stability Predictive control

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AI Enabled Automatic Mobile Robot Intelligent Navigation in Construction with Obstacle Awareness

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IEEE Transactions on automation Science and Engineering 2025年

作者： Zhang, Yinlong Liu, Yuanhao Cui, Yunge Zeng, Ziming Liang, Wei Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang Institute of Automation Shenyang110016 China Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang110016 China University of Chinese Academy of Sciences Beijing101408 China Zeekr Group Zeekr Intelligent Driving Department Shanghai110078 China Shenzhen Polytechnic University School of Automotive and Transportation Engineering Shenzhen518055 China

In the construction industry, the integration of artificial intelligence (AI) and robotics has led to significant advancements in automating various tasks. One critical aspect is the intelligent navigation of automatic mobile robot (AMR) within construction sites, where dynamic environments pose challenges such as inaccurate robot state estimation, irregular and textureless obstacle detection. To solve these issues, this paper designs an AI enabled obstacle-aware AMR intelligent navigation approach while ensuring robot safety and efficiency. Specifically, the robot is equipped with the complementary RGB camera, inertial measurement unit (IMU) and wheel encoder to estimate the states (i.e., positions, orientations and velocities), which have been tightly fused in the optimization framework. Furthermore, the RGB-Depth images are jointly fed into the AI model. It combines of Mask-RCNN and multi-scale attention network, to detect and segment the obstacles, and estimate the corresponding relative depth. It should be noted that the system incorporates obstacle awareness mechanisms to dynamically switch the robot's velocities in response to obstacles in the environment, ensuring smooth and collision-free movement. Experimental results demonstrate the effectiveness and robustness of the proposed AI-enabled navigation system in real-world construction scenarios, showcasing its potential to enhance productivity and safety in construction automation. © 2004-2012 IEEE.

关键词： Construction industry

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Fault Detection and Fault-Tolerant control Based on Bi-LSTM Network and SPRT for Aircraft Braking System

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Chinese Journal of Mechanical Engineering (English Edition) 2025年第1期38卷 1-17页

作者： Li, Renjie Shang, Yaoxing Cai, Jinglin Liu, Xiaochao Geng, Lingdong Qi, Pengyuan Jiao, Zongxia School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Key Laboratory of Advanced Aircraft Systems Beihang University Beijing100191 China Ningbo Institute of Technology Beihang University Ningbo315800 China Tianmushan Laboratory Hangzhou310023 China China Space Sanjiang Group Co. Ltd. Wuhan430040 China Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Aerospace Information Research Institute of QiLu Jinan250001 China

The aircraft braking system is critical to ensure the safe take-off and landing of the aircraft. However, the braking system is often exposed to high temperatures and strong vibration working environments, which makes the sensor prone to failure. Sensor failure has the potential to compromise aircraft safety. In order to improve the safety of the aircraft braking system, a fault detection and fault-tolerant control (FDFTC) strategy for the aircraft brake pressure sensor is designed. Firstly, a model based on a bidirectional long short-term memory (Bi-LSTM) network is constructed to estimate the brake pressure. Then, the residual sequence is obtained by comparing the measured pressure with the estimated pressure. On this basis, the improved sequential probability ratio test (SPRT) method based on mathematical statistics is applied to analyze the residual sequence to detect the fault. Finally, simulation and hardware-in-the-loop (HIL) testing results indicate that the proposed FDFTC strategy can detect sensor faults in time and efficiently complete braking when faults occur. Hence, the proposed FDFTC strategy can effectively deal with the faults of the aircraft brake pressure sensor, which is of great significance to improve the reliability and safety of the aircraft. © The Author(s) 2025.

关键词： Pressure sensors

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Verification of monocular and binocular pose estimation algorithms in vision-based UAVs autonomous aerial refueling system

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Science China(Technological Sciences) 2016年第11期59卷 1730-1738页

作者： LI Han DUAN HaiBin Bio-inspired Autonomous Flight Systems (BAFS) Research Group Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical Engineering Beihang University

With the high focus on autonomous aerial refueling(AAR), it becomes increasingly urgent to design efficient methods or algorithms for solving the AAR problems in complicated aerial environments. A vision-based technology for AAR is developed in this paper, and five monocular and binocular visual algorithms for pose estimation of the unmanned aerial vehicles(UAVs) are adopted and verified in this AAR system. The real-time on-board vision system is also designed for precise navigation in the UAVs docking phase. A series of out-door comparative experiments for different pose estimation algorithms are conducted to verify the feasibility and accuracy of the vision algorithms in AAR.

关键词： unmanned aerial vehicles（UAVs） autonomous aerial refueling（AAR） pose estimation monocular vision binocular vision

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