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Multi-parameter load sensing pump model simulation and flow rate characteristics research

Chinese Journal of Aeronautics 2022年第12期35卷 296-308页

作者： ZongXia JIAO Zhenyu WANG Xiaochao LIU HuJiang WANG Pengyuan QI Weizhi QIAO School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100083China State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang UniversityHangzhou 310027China Research Institute for Frontier Science Beihang UniversityBeijing100083China Science and Technology on Aircraft Control Laboratory Beihang UniversityBeijing 100083China Science and Technology on Vehicle Transmission Laboratory China North Vehicle Research InstituteBeijing 100072China Ningbo Institute of Technology Beihang UniversityNingbo 315800China

Load sensing pumps have been widely used in diverse hydraulic *** show that structural parameters have undeniable impacts on the characteristics and efficiency of the load sensing *** main purpose of this article is to study the influence of load sensing pump structure parameters on flow *** the present study,a nonlinear multi-parameter model is proposed for this type of *** this model,different parameters,including spool clearance,spool covering amount,internal leakage are considered to reflect the displacement adjustment process of the load sensing ***,a frequency sweep method is proposed to analyze the frequency domain of the nonlinear mathematical *** experiment rig was built to study the influence of key structural parameters on the dynamic follow-up characteristics of the pump *** obtained results show that the diameter of the orifice d can significantly affect the working characteristics of the *** is found that a large diameter of the orifice d can improve the phase following ability of the system,while a small diameter of the orifice d can reduce the bypass flow rate and increase the amplitude following *** paper provides a new consideration to study the dynamic follow-up characteristics of the load sensing pump.

关键词： Flow rate characteristics Frequency analysis Hydraulic Load sensing pump Nonlinear

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An optimal design and fuzzy control method for a new flapping-wing robot 3

An optimal design and fuzzy control method for a new flappin...

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3rd International Conference on Electrical engineering and control science, IC2ECS 2023

作者： Zhang, Chunxiao Zhao, Yansen Zhang, Ting Liu, Qi Li, Bin Ma, Yue Suo, Mengze Li, Changrui School of Mechanical Engineering Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin300384 China Tianjin University of Technology National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin300384 China

ISBN: (纸本)9798350382426

Bionic flapping-wing robot has the advantages of good maneuverability, low noise and strong stealth performance. It is widely used in military intelligence collection, field rescue and investigation. In this paper, an optimal design method of bionic flapping-wing robot non-phase difference driving mechanism is proposed. By setting the constraints of flapping angle amplitude, fuselage height and slider stroke, the scale parameters of the mechanism are optimized by using the minimum transmission angle;on this basis, the effectiveness of fuzzy PD control in improving the tracking accuracy of the drive system is verified by means of ADAMS and MATLAB / Simulink electromechanical coupling simulation. This research has practical value for designing new flapping-wing robot and improving its control quality. © 2023 IEEE.

关键词： flapping-wing robot fuzzy PD control kinematics scale optimization

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Automated Creation of Topological Structure Models of Parallel Mechanisms for Kinematic Performance Evaluation 8

Automated Creation of Topological Structure Models of Parall...

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8th IEEE International Conference on Advanced Robotics and mechatronics, ICARM 2023

作者： Wu, Hongye Lin, Ping Ma, Yue Li, Bin Liu, Qi Li, Hongqing School of Mechanical Engineering Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin300384 China Tianjin University of Technology National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin300384 China

ISBN: (纸本)9798350300178

Considering the diversity of topological structures of parallel mechanisms (PMs), this paper presents an approach for the automated generation of topological structure models based on CAD technology. In this method, joints and links are treated as fundamental elements in the skeleton model of a mechanical system, leading to the development of a library of fundamental components readily available to compose a variety of limbs and PMs. A connection graph and its data structure are then developed for describing, in a hierarchical manner, the assembly information among the fundamental components. Equipped with the knowledge and information mentioned above, the limbs and PMs can finally be assembled automatically by identifying and imposing the geometrical constraints that have been already embedded in the models. The merit of this method lies in that 3D schematic diagrams (termed topological structure models) of various limbs and PMs can be created in an illustrative manner by properly selecting a set of fundamental components and then setting their connections, leading to the digitalized and visible topological structure models that are readily for kinematic performance evaluation. Combined with the CAD-CAE integration technology for the mechanical structure design and static/dynamic performance evaluation, a digital design and simulation framework can be formulated for the rapid design of parallel robotic equipment. © 2023 IEEE.

关键词： Topology

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Micro-Newton scale variable thrust control technique and its noise problem for drag-free satellite platforms:a review

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Journal of Zhejiang University-science A(Applied Physics & engineering) 2023年第10期24卷 841-858页

作者： Changyi XU Wenya LI Xuhui LIU Yong LI Chao ZHANG School of Control Science and Engineering Dalian University of TechnologyDalian 116024China Beijing Institute of Control Engineering Beijing 100190China State Key Laboratory of Fluid Power&Mechatronic Systems School of Mechanical EngineeringZhejiang UniversityHangzhou 310058China

High-precision detection in fundamental space physics,such as space gravitational wave detection,high-precision earth gravity field measurement,and reference frame drag effect measurement,is the key to achieving important breakthroughs in the scientific study of fundamental space *** high-precision measurements requires high-performance satellite platforms to achieve“drag-free control”in a near“pure gravity”flight *** critical technology for drag-free control is variable thrust control at the micro-Newton *** noise is the most important technical indicator for achieving drag-free ***,there is no literature about the current status and future prospects of variable thrust control based on thrust ***,the micro-Newton variable thrust control technology and the thrust noise of the drag-free satellite platform are reviewed in this ***,the research status of micro-Newton scale variable thrust control technology and its applications to drag-free satellite platforms are ***,the noise problem is analyzed in detail and its solution is theoretically investigated in three aspects:“cross-basin flow problem,”“control problem,”and“system instability and multiple-coupled problem.”Finally,a systematic overview is presented and the corresponding suggested directions of research are *** work provides detailed understanding and support for realizing low-noise variable thrust control in the next generation of drag-free satellites.

关键词： Space physics detection Satellite platforms Drag-free control Micro-Newton scale variable thrust Thrust noise

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Trajectory Optimization and control Method Based on Multistage Nonlinear Model Predictive control 4

Trajectory Optimization and Control Method Based on Multista...

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4th International Seminar on Artificial Intelligence, Networking and Information technology, AINIT 2023

作者： Zheng, Qingchun Peng, Zhi Zhu, Peihao Zhai, Ran Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin China School of Mechanical Engineering Tianjin University of Technology Tianjin China Tianjin University of Technology National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin China

ISBN: (纸本)9798350314526

To improve the trajectory optimization efficiency of robot manipulators, this paper proposes a novel approach for trajectory optimization and control of manipulators based on multistage nonlinear model predictive control (msNLMPC). This approach is realized by using a neural state space model as the prediction model of nonlinear model predictive control (NLMPC). The simulation results show that the actual trajectory of the manipulator in our proposed scheme coincides with the desired trajectory. The manipulator achieves the control task of following the optimal trajectory. Our proposed method improves the trajectory optimization efficiency of the robot manipulator. © 2023 IEEE.

关键词： Model predictive control

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Multiagent Consensus over Time-Invariant and Time-Varying Signed Digraphs via Eventual Positivity

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IEEE Transactions on Automatic control 2023年第9期68卷 5429-5444页

作者： Fontan, Angela Wang, Lingfei Hong, Yiguang Shi, Guodong Altafini, Claudio Linköping University Division of Automatic Control Department of Electrical Engineering LinköpingSE-58183 Sweden KTH Royal Institute of Technology Division of Decision and Control Systems StockholmSE-10044 Sweden Chinese Academy of Sciences Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing100190 China University of Chinese Academy of Sciences Beijing100190 China Tongji University Department of Control Science and Engineering Shanghai201804 China University of Sydney Australian Center for Field Robotics School of Aerospace Mechanical and Mechatronic Engineering SydneyNSW2008 Australia

Laplacian dynamics on signed digraphs have a richer behavior than those on nonnegative digraphs. In particular, for the so-called 'repelling' signed Laplacians, the marginal stability property (needed to achieve consensus) is not guaranteed a priori and, even when it holds, it does not automatically lead to consensus, as these signed Laplacians may lose rank even in strongly connected digraphs. Furthermore, in the time-varying case, instability can occur even when switching in a family of systems each of which corresponds to a marginally stable signed Laplacian with the correct corank. In this article, we present novel conditions for achieving consensus on signed digraphs based on the property of eventual positivity, a Perron-Frobenius (PF) type of property for signed matrices. The conditions we develop cover both time-invariant and time-varying cases. A particularly simple sufficient condition, valid in both cases, is that the Laplacians are normal matrices. Such condition can be relaxed in several ways. For instance, in the time-invariant case it is enough that the Laplacian has this PF property on the right side, but not on the left side (i.e., on the transpose). For the time-varying case, convergence to consensus can be guaranteed by the existence of a common Lyapunov function for all the signed Laplacians. All conditions can be easily extended to bipartite consensus. © 1963-2012 IEEE.

关键词： Lyapunov functions

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Neural-Network-Based Filtering with Encoding Mechanisms: Applications to Multiple Unmanned Aerial Vehicles

Neural-Network-Based Filtering with Encoding Mechanisms: App...

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2023 China Automation Congress, CAC 2023

作者： Zhu, Kaiqun Xu, Xinpeng Cao, Zhiru Sun, Ran Yang, Ya University of Macau State Key Laboratory of Internet of Things for Smart City Macau China Shanghai Electro-Mechanical Engineering Institute Shanghai China School of Mechatronic Engineering and Automation Shanghai University Shanghai China University of Shanghai for Science and Technology Department of Control Science and Engineering Shanghai China

ISBN: (纸本)9798350303759

In this paper, the neural-network-based filtering problem is investigated for multi-sensor systems with dynamic encoding mechanisms. The sensor nodes and the remote filter are connected through bandwidth-constrained communication networks. To alleviate the communication burden, a novel dynamic encoding-based data compression-decompression mechanism is proposed so as to encode the data into a limited number of bits. Then, with the aid of the neural network learning method, a neural-network-based set-membership filter is developed for estimating the system states. Sufficient conditions are obtained to ensure that the filtering error remains within the bounded ellipsoidal set. In addition, the neural network tuning parameters and the filter gains are calculated by solving constrained optimization problems. Finally, the effectiveness of the proposed filtering algorithm is verified through a scenario of maneuvering target tracking using multiple unmanned aerial vehicles. © 2023 IEEE.

关键词： Antennas

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MG6D: A Deep Fusion Approach for 6D Pose Estimation with Mamba and Graph Convolution Network

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IEEE Access 2025年 13卷 100433-100445页

作者： Zhu, Jiaqi Li, Bin Zhao, Xinhua Tianjin University of Technology School of Computer Science and Engineering Tianjin 300384 China Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin 300384 China

Accurate and efficient 6D pose estimation is a fundamental technology in many industrial applications. While existing dense correspondence methods have shown progress, they face challenges in multimodal feature fusion under complex scenarios involving occlusions, illumination variations, and sensor noise. This paper proposes a novel 6D pose estimation framework that addresses these limitations through a hybrid Mamba-Graph architecture. The algorithm first introduces a panoramic attention fusion Mamba module, leveraging state-space modeling to capture long-range dependencies in multi-modal data while establishing cross-dimensional interactions between channel and spatial features to emphasize critical information. A dynamic graph convolutional adaptive fusion module is then designed to enable cross-modal geometric consistency modeling via multi-modal feature integration. Finally, a texture-geometry co-driven keypoint selection mechanism is proposed to ensure keypoint distributions satisfy both spatial uniformity and discriminability requirements. Experimental results on three common datasets demonstrate that the proposed algorithm achieves ADD(-S) metrics of 99.82%, 80.26%, and 97.2%, respectively. Notably, it exhibits significant advantages in pose estimation for objects with repetitive textures and high symmetry. © 2013 IEEE.

关键词： 6D pose estimation Fusion Mamba Graph feature fusion Panoramic Attention

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The effect of different gravity fields on mass transfer in the rat bone lacunar-canalicular system

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Medicine in Novel technology and Devices 2023年第1期17卷 141-149页

作者： Hao Wang Jiaming Wang Kangning Li Lilan Gao Aiguo Wang Shuping Wei Linwei Lyu Chunqiu Zhang Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control National Demonstration Center for Experimental Mechanical and Electrical Engineering EducationSchool of Mechanical EngineeringTianjin University of TechnologyTianjin300384PR China Tianjin Academy of Traditional Chinese Medicine Affiliated Hosptial PR China

The bone lacunar-canalicular system(LCS)is an important microscopic infrastructure for signaling and solute transport in bone tissue,which guarantees normal physiological processes of the tissue,but the mass transfer laws in the LCS under different gravity fields have not yet been *** rats were injected intraperitoneally with different concentrations of sodium fluorescein tracer and subjected to mass transfer experiments in the LCS under normal gravity and *** fluorescence distribution in the osteon was observed using laser scanning confocal *** hypergravity environment was provided by a self-designed high-G loading *** fluorescence intensity of the Haversian canal in the osteon was the *** fluorescence intensity of lacunae farther away from the Haversian canal was lower,and the fitted curve was *** the increasing distance from the Haversian canal,the curve first rapidly decreased,and then the decreasing trend gradually became *** promoted mass transfer in the LCS,and the 10 G hypergravity showed varying degrees of fluorescence intensity in each layer of the osteon relative to normal gravity,with intensity enhancements in the range of 132.7–249.0%.The fluorescence intensity was also significantly increased when the tracer concentration was halved and the gravity field magnitude was increased to *** conclusion,hypergravity promoted the transport of solute molecules,nutrients,and signaling molecules within the *** effect of hypergravity on mass transfer in the LCS was greater than that of tracer *** may help to understand bone diseases from a mass transfer perspective.

关键词： Bone Lacunar-canalicular system Mass transfer Hypergravity

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Target-background feature blocks and aberrance repressed correlation filters for real-time UAV tracking

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Signal, Image and Video Processing 2025年第7期19卷 1-11页

作者： Jia, Yunwei Liu, Bo Liu, Zhenzhong Wang, Tianyang Yv, Kaiying Wang, Shuo Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300384 China

In recent years, Unmanned Aerial Vehicle (UAV) tracking technology has been widely applied in fields such as agriculture and aviation. However, due to limitations in UAV computational resources and battery life, deep learning-based tracking algorithms are difficult to deploy directly. Therefore, efficient and robust tracking methods based on Discriminative Correlation Filters (DCF) have become the mainstream for UAV tracking. The traditional DCF method updates the model with a fixed step size, making it prone to contamination, while the boundary effect further limits its tracking capability. To address the issue of model contamination, an appearance model update and masking mechanism was designed, introducing feature confidence and overall confidence thresholds to evaluate the quality of features and images. Features and images with poor quality are masked, and the learning rate is reduced to prevent model contamination. This paper proposes the Target-Background Feature Block and Aberrance Repressed Correlation Filter (TBFBARCF), which introduces target and background regularization terms into the spatial filter to mitigate boundary effects and incorporates an aberrance repression regularization term into the temporal aberrance repressed filter to reduce response map aberrance. The two filters mutually constrain each other and are jointly trained. Experiments conducted on three challenging datasets, OTB100, UAV123, and UAVDT, demonstrate that the TBFBARCF tracker outperforms 11 other DCF-based trackers. Its average precision and average success rate reach 0.756 and 0.62, respectively, and it operates at a speed of 36.6 frames per second (FPS) on a CPU platform. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Drones

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