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42nd Chinese control Conference, CCC 2023

作者： Dou, Minghao Liu, Xuchen Huang, Dongyue Wang, Biao Cui, Jinqiang Ren, Qinyuan Dou, Lihua Chen, Jie Chen, Ben M. Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China The Chinese University of Hong Kong Department of Mechanical and Automation Engineering Shatin N.T. Hong Kong College of Automation Engineering Nanjing University of Aeronautics and Astronautics Jiangsu Nanjing China Peng Cheng Laboratory Guangdong Shenzhen China College of Control Science and Engineering Zhejiang University Zhejiang Hangzhou China Automation Beijing Institute of Technology Beijing China

ISBN: (纸本)9789887581543

Modeling of cross-medium vehicles with complex shapes still requires a thorough investigation. This paper proposes a multi-method combination modeling approach to tackle such a problem. First-principle model is derived to determinate a model structure. Experiments are then set up to estimate parameters related to its rigid-body model and propulsion system. Computational fluid dynamics (CFD) is performed to calculate and identify coefficients related to surrounding fluid. Base on the model obtained, we systematically investigate the possible steady motion of the cross-medium vehicle and analyze their related performance. Results are instrumental for designing controllers for the vehicle to perform autonoumous missions. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Computational fluid dynamics

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Improvement of the Predictive control Method for the High-Level controller 17

Improvement of the Predictive Control Method for the High-Le...

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17th IEEE International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer engineering, TCSET 2024

作者： Budashko, Vitalii Sandler, Albert Glazeva, Oksana Educational and Scientific Institute of Automation and Electrical Engineering National University 'Odessa Maritime Academy' NUOMA Odesa Ukraine National University 'Odessa Maritime Academy' NUOMA Department of the theory of automatic control and computer technology Odesa Ukraine National University 'Odessa Maritime Academy' NUOMA Department of electrical engineering and electronics Odesa Ukraine

ISBN: (纸本)9798331520564

automation of ship maneuvering in limited sailing conditions usually requires 100% redundancy of thrusters (THRs) of various modifications and their locations in accordance with the matrix. The hierarchy of the motion control system is branched by levels using high-level motion controllers and THRs control distribution algorithms, which allows for a modular design with software, where the high-level controller (HLC) can be designed without comprehensive information about the thruster motors, and the input signal branching and speed limits are handled by the motion controller. But, for certain THRs configurations, this branching leads to the decrease in control efficiency due to the limitation of data on the physical characteristics of the ships and the operation of the motion controller. This research examines different approaches to improving control efficiency using methods of nonlinear predictive control models as a basis for developing motion controllers with decision optimization based on relevant constraints. The implemented branched system is the result of solving two simple problems of ship's motion, which highlight the related problems. The use of different approaches to eliminate the identified shortcomings made it possible to develop the nonlinear controller that combines the motion controller with distributed control of the THRs and ensuring the certain level of system reliability. The modularity of the control system is provided by the expansion of the closed system, which made it possible to achieve an increase in efficiency during the combined mode of operation. The obtained solution of nonlinear control with time-varying constraints made it possible to increase the accuracy of the control with a decrease in the duration of the pause in response to the change of the disturbance within 10% © 2024 IEEE.

关键词： Predictive control systems

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Optimization for vibration analysis in rotating machines

Renewable Energy and Power Quality Journal

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Renewable Energy and Power Quality Journal 2022年 20卷 369-373页

作者： Calderón Ch, J. Alan Tafur Sotelo, Julio C. Gamarra, Benjamín Barriga Alencastre, Jorge Lozano, John Urbizagástegui, Rodrigo Solano, Gonzalo Menacho, Daniel Applied Nanophysics Institute for Physics Technical University of Ilmenau Ilmenau98693 Germany Control Engineering and Automation Master Program Mechatronic Engineering Master Program Engineering Department Pontificia Universidad Católica del Perú Peru Federal University named after MV Lomonosov Arkhangelsk Russia

A not stable mechanical movement transmission between systems produces equilibrium losses, such as a rotor of motors that are coupled in rotating machines. This can be studied as a disturbance "vibration" either as characteristic of the movement transmission due to controlled displacement over rotors, which transmits the movement. Therefore, in this research is presented an analysis for an optimal control of the rotor axis displacement that includes "vibration" as the part of the movement transmission. It implies mathematical modelling and specific sensors selections to correlate the vibration in this control task. Furthermore, in order to verify the proposed analysis, it was simulated and tested in a hybrid magnetic bearing system. © 2022, European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ). All rights reserved.

关键词： Vibration analysis

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An IMU Error Correction Method Based on Multithreshold ZV Detection and SRCKF

An IMU Error Correction Method Based on Multithreshold ZV De...

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2023 International Conference on Cyber-Physical Social Intelligence, ICCSI 2023

作者： Luo, Jialiang Chen, Shichao Lv, Yisheng Sun, Wenqiao Yang, Fan Xu, Ruijie Institute of Automation Chinese Academy of Sciences School of Information Engineering China University of Geosciences Beijing The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems China Institute of Automation Chinese Academy of Sciences The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited The State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Institute of Automation Chinese Academy of Sciences The State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Transportation and Economics Research Institute Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences College of Rail Transit Shan Dong JiaoTong University The State Key Laboratory for Management and Control of Complex System Jinan China The Hong Kong Polytechnic University Department of Aeronautical and Aviation Engineering Hong Kong Hong Kong

ISBN: (纸本)9798350312492

With the rapid development and widespread application of Inertial Measurement Units (IMUs), IMU-based human localization has become critically important in environments lacking Global Navigation Satellite systems (GNSS) signals. Methods such as UWB/WIFI and other anchor-based localization have been employed to enhance the positioning accuracy. However, these methods are susceptible to the environmental interference and increased costs. In contrast, SINS-based localization methods eliminate reliance on the external data. However, this method can suffer from drift errors due to cumulative integration errors. Inertial navigation error correction techniques like Zero Detection Update Technology (ZUPT) provide potential solutions to address drift errors. This paper proposes an error correction method based on the multithreshold zero-velocity detection and Square Root Cubature Kalman Filter (SRCKF) updates. Compared to the single fixed threshold detection, the multi-threshold zero-velocity detection reduces the likelihood of missed zero velocity detection and false alarms, providing accurate time intervals for error correction. Experimental results demonstrate that the SRCKF-based algorithm reduces position deviation to approximately 0.3146 meters, corresponding to an error ratio of1.14%. The proposed method enables cost-effective and accurate pedestrian localization, driving advancements in the field. © 2023 IEEE.

关键词： Cost effectiveness

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Recognizing knee pathologies by using gait dynamics via kernel principal component analysis and deterministic learning theory

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Journal of Ambient Intelligence and Humanized Computing 2023年第11期14卷 15535-15543页

作者： Deng, Muqing Feng, Xiaoreng Zeng, Wei Cao, Jiuwen Zhang, Yu Zheng, Tongjia Institute of Information and Control Hangzhou Dianzi University Hangzhou China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Shatin Hong Kong Department of Orthopaedics and Traumatology Queen Mary Hospital the University of Hong Kong Pok Fu Lam Hong Kong College of Mechanical and Electrical Engineering Longyan University Longyan China Department of Orthopaedic Surgery Guangzhou General Hospital of Guangzhou Military Command Guangzhou China College of Engineering University of Notre Dame Notre DameIN United States

This study concentrates on dynamical motion characteristics of knees during treadmill walking, and describes the application of kernel principal component analysis and deterministic learning theory to the detection of abnormal gait dynamics induced by knee pathologies. First, twelve-dimensional knee joint rotation and translation parameters are measured by a marker-based motion analysis system during treadmill walking. Second, the dimension of the gait parameter signal is reduced based on kernel principal component analysis. Third, gait dynamics underlying time-varying gait parameter signal is captured by using localized radial basis function neural networks through deterministic learning mechanism. This kind of dynamics information represents the frame-to-frame temporal change of kinematics and kinetics modifications during treadmill walking, which is shown to be sensitive to the variance during knee pathologies. Gait patterns are represented as the gait dynamics underlying time-varying gait parameters. The training patters under different knee pathologies further constitute a uniform training dataset, containing all kinds of gait dynamics under different knee pathologies. By comparing the training patterns with a test knee gait pattern to be recognized, a set of recognition errors are generated. The average L1 norms of the errors are taken as the classification measure between the dynamics of the training gait patterns and the dynamics of the test pattern. A rapid recognition scheme can be achieved according to the smallest error principle. Experimental results show that encouraging recognition accuracy can be achieved. The proposed method is sensitive for the detection of knee pathologies and is capable of discharge of patients without knee pathologies. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Errors

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Improving 2D-3D Dense Correspondences with Diffusion Models for 6D Object Pose Estimation

arXiv

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arXiv 2024年

作者： Hönig, Peter Thalhammer, Stefan Vincze, Markus Automation and Control Institute TU Wien Austria Department of Industrial Engineering UAS Technikum Vienna Austria

Estimating 2D-3D correspondences between RGB images and 3D space is a fundamental problem in 6D object pose estimation. Recent pose estimators use dense correspondence maps and Point-to-Point algorithms to estimate object poses. The accuracy of pose estimation depends heavily on the quality of the dense correspondence maps and their ability to withstand occlusion, clutter, and challenging material properties. Currently, dense correspondence maps are estimated using image-to-image translation models based on GANs, Autoencoders, or direct regression models. However, recent advancements in image-to-image translation have led to diffusion models being the superior choice when evaluated on benchmarking datasets. In this study, we compare image-to-image translation networks based on GANs and diffusion models for the downstream task of 6D object pose estimation. Our results demonstrate that the diffusion-based image-to-image translation model outperforms the GAN, revealing potential for further improvements in 6D object pose estimation models. © 2024, CC BY.

关键词： Image enhancement

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Anti-disturbance control for Aerial-Recovery Drogue with Flexible Prescribed Performance

Anti-disturbance Control for Aerial-Recovery Drogue with Fle...

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International Conference on Guidance, Navigation and control, ICGNC 2024

作者： Zhu, Junfan Wang, Honglun Wang, Yanxiang Liu, Yiheng School of Automation Science and Electrical Engineering Beihang University Beijing100191 China The Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Shenyuan Honors College Beihang University Beijing100191 China Beijing Institute of Astronautical System Engineering Beijing100076 China

ISBN: (纸本)9789819622115

The control of towed-cable-drogue system (TCDS) is important to achieving aerial recovery. In this paper, an adaptive prescribed performance control (APPC) based drogue controller is proposed to control drogue’s position while docking. First, the kinematic and dynamic models of controllable TCDS under multiple airflow disturbances are constructed. Second, the impact of command mutations and sudden disturbances may cause sudden increase of position tracking error and traditional PPC may encounter control singularity. To address the fragility of traditional PPC, an adaptive PPC is proposed. Combined with backstepping controller, the position controller is designed. Finally, the simulation results validate the effectiveness of the proposed method in addressing the control challenges of TCDS under command mutations and sudden disturbances. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Backstepping

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Dual-Class Leader-Following Modeling for Collective Motion of Multi-Agent systems 43

Dual-Class Leader-Following Modeling for Collective Motion o...

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43rd Chinese control Conference, CCC 2024

作者： Zhang, Bo Li, Haoqi Meng, Bin Hu, Jiangping Ghosh, Bijoy Kumar Beijing Institute of Control Engineering Beijing100080 China University of Electronic Science and Technology of China School of Automation Engineering Chengdu611731 China University of Electronic Science and Technology of China Huzhou313000 China Texas Tech University Department of Mathematics and Statistics LubbockTX79409 United States

ISBN: (纸本)9789887581581

Leader-follower collective motion is a key multi-agent network application. However, conventional methods struggle with high dynamics or communication interferences and fail to maintain consistent motion. To address this issue, a resilient dual-class cooperative following (DCCF) model is proposed. This model uses two movement strategies for the different follower categories. Leader-connected followers use a single-tracking control based on velocity or direction, whereas leader-disjoint followers employ a modified relative speed for single tracking. The DCCF model may be more suitable for practical use than existing ones. Simulations under degraded conditions demonstrate its superior tracking performance and robustness over traditional methods. © 2024 Technical Committee on control Theory, Chinese Association of automation.

关键词： collective motion dual-class cooperative following leader-follower tracking Multi-agent network

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Finite-time asynchronous dissipative filtering of conic-type nonlinear Markov jump systems

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Science China(Information Sciences) 2021年第5期64卷 151-162页

作者： Xiang ZHANG Shuping HE Vladimir STOJANOVIC Xiaoli LUAN Fei LIU Key Laboratory of Intelligent Computing and Signal Processing (Ministry of Education) School of Electrical Engineering and Automation Anhui University Department of Automatic Control Robotics and Fluid Technique Faculty of Mechanical and Civil EngineeringUniversity of Kragujevac Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of AutomationJiangnan University

In the present study, the finite-time asynchronous dissipative filter design problem for the Markov jump systems with conic-type nonlinearity is studied. The hidden Markov model can describe the asynchronism embodied in the system modes and the filter modes reasonably. Moreover, a suitable LyapunovKrasovskii function is utilized and linear matrix inequalities are applied to obtain adequate conditions. These techniques guarantee the finite-time boundedness and strict dissipativity of the filtering error dynamic system. Furthermore, the design problems of the passive filter and the H∞ filter are studied by adjusting the three parameters U, G and V. Finally, the filter gains and the optimal index α*are obtained and the correctness and feasibility of the designed approach are verified by a simulation example.

关键词： dissipative filtering hidden Markov model finite-time boundedness Markov jump systems conic-type nonlinearity

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A data-driven disturbance estimation algorithm based on adaptive observer for MIMO linear systems

A data-driven disturbance estimation algorithm based on adap...

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第34届中国过程控制会议

作者： Xiaoyi Xu Hao Luo Xiao Zhang Department of Control Science and Engineering Harbin Institute of Technology Department of Automation Science and Electrical Engineering Beihang University

The adaptive observer is a well-developed datadriven algorithm for co-estimation of system parameters and ***,inevitable disturbances can affect the systems and lead to deterioration of the algorithm *** disturbance estimation methods require prior knowledge about model parameters and disturbance *** paper presents a robust adaptive observer method for multiple-inputmultiple-output linear systems subject to *** proposed method can perform joint estimation of unknown parameters,states and disturbances without any prior information about the model parameters and *** stability and convergence of the algorithm are rigorously proved to ensure that the estimation errors converge exponentially to *** results of a numerical example demonstrate the effectiveness of the algorithm.

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