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Journal of Central South University 2023年第3期30卷 871-903页

作者：王鹏飞杨阳徐宏阳马辉韩清凯罗忠闻邦椿 School of Mechanical Engineering and Automation Northeastern UniversityShenyang 110819China China North Vehicle Research Institute Beijing 100072China Key Laboratory of Vibration and Control of Aero-Propulsion System of Ministry of Education(Northeastern University) Shenyang 110819China

在滚动轴承不对中问题的研究中,以往的研究中很少考虑轴承不对中对转子系统振动特性的影响。基于现有研究的局限性,首先,给出了一种考虑轴承不对中的5自由度非线性力模型,该模型综合考虑了轴承的平行和角不对中、静态与动态不对中、内... 详细信息

在滚动轴承不对中问题的研究中,以往的研究中很少考虑轴承不对中对转子系统振动特性的影响。基于现有研究的局限性,首先,给出了一种考虑轴承不对中的5自由度非线性力模型,该模型综合考虑了轴承的平行和角不对中、静态与动态不对中、内圈与外圈不对中等多种情况。其次,将该模型应用在转子有限元模型中,分析了不对中对轴承动态接触特性和转子系统振动特性的影响。然后,给出了衡量轴承不对中程度的评价指标。最后,对比分析了平行和角不对中、静态与动态不对中的异同点。结果表明,轴承不对中提高了转子的共振转速,在共振区出现了幅值跳跃现象,表现出硬式非线性特征。从频率特征上来看,滚动轴承动态平行不对中和动态角不对中分别导致转子旋转频率成分fr和2fr的幅值增大。动态不对中导致轴承的承载区随着轴承内圈的旋转而时刻变化。该研究可为转子-轴承系统的故障识别提供理论依据和有价值的参考。

关键词：滚动轴承-转子系统不对中非线性动力学分岔故障诊断

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Adaptive Prescribed-Time Distributed Nash Equilibrium Seeking for Networked Games with Heterogeneous Dynamics and Unknown Uncertainties

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IEEE Transactions on control of Network systems 2025年

作者： Chen, Yiyang Hua, Yongzhao Feng, Zhi Dong, Xiwang Beihang University School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Shenyuan Honors College Beijing100191 China Beihang University School of Artificial Intelligence Institute of Artificial Intelligence Beijing100191 China Beihang University School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beijing100191 China Beihang University Institute of Unmanned System School of Artificial Intelligence Institute of Artificial Intelligence School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beijing100191 China

This paper investigates the adaptive prescribed-time distributed Nash equilibrium (NE) seeking problems for networked games with heterogeneous dynamics and unknown uncertainties. The proposed algorithms are based on the two-layer structure, namely the NE seeking part and the tracking control part. For the players without uncertainties, the adaptive parameters are utilized in the seeking part to avoid the use of the global information. The auxiliary variables are constructed to seek for the NE point within the prescribed time and serve as the reference signals for the tracking control part. Then the state feedback control is designed to drive the strategies of all the players to the expected NE point in the prescribed time. Furthermore, the approximation theory is introduced to deal with the unknown nonlinear uncertainties. The exponential parameters are involved in the designed estimates to accelerate the convergence rate. The Lyapunov method is utilized to show the prescribed-time convergence property of the algorithms. Besides, although the time-varying piecewise function is involved in the algorithms, the uniform boundedness of the control input can be ensured by carefully selecting the initial values of the auxiliary parameters. Finally, the simulation is given to show the effectiveness of the proposed algorithms. © 2025 IEEE.

关键词： Lyapunov methods

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Explicit Predictive control of Forward DC-DC Converter Based on an Input-Mapping Method

Explicit Predictive Control of Forward DC-DC Converter Based...

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第43届中国控制会议

作者： Xiang Gu Dewei Li Aoyun Ma Yaru Yu Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In the practical application of model predictive control in power electronics, both online computational burden and model accuracy are crucial. This paper presents an explicit model predictive control method based on input-mapping *** address the issue of parameter drift in the forward DC-DC converter system, the input-mapping method is introduced to compensate for model deviations using historical data. Firstly, the average model of the forward DC-DC converter system is introduced. For the control objective of voltage tracking, an explicit predictive control using the incremental model is ***, input-mapping method is integrated with explicit predictive control. During offline computation, analytical forms of the input-mapping combination coefficients and the optimal solution function of explicit model predictive control are *** computation of combination coefficients is conducted to obtain the optimal solution rapidly. The effectiveness of the proposed method is verified through simulations in MATLAB.

关键词： Forward DC-DC converter explicit model predictive control input-mapping method

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A transferable energy management strategy for hybrid electric vehicles via dueling deep deterministic policy gradient

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Green Energy and Intelligent Transportation 2022年第2期1卷 75-87页

作者： Jingyi Xu Zirui Li Guodong Du Qi Liu Li Gao Yanan Zhao School of Mechanical Engineering Beijing Institute of Technology100081BeijingChina Department of Transport and Planning Delft University of TechnologyDelft2628 CDthe Netherlands Institute of Dynamic System and Control ETH ZurichSonneggstrasse 38092ZurichSwitzerland

Due to the high mileage and heavy load capabilities of hybrid electric vehicles(HEVs),energy management becomes crucial in improving energy *** avoid the over-dependence on the hard-crafted models,deep reinforcement learning(DRL)is utilized to learn more precise energy management strategies(EMSs),but cannot generalize well to different driving situations in most *** driving cycles are changed,the neural network needs to be retrained,which is a time-consuming and laborious task.A more efficient transferable way is to combine DRL algorithms with transfer learning,which can utilize the knowledge of the driving cycles in other new driving situations,leading to better initial performance and a faster training process to *** this paper,we propose a novel transferable EMS by incorporating the DRL method and dueling network architecture for *** results indicate that the proposed method can generalize well to new driving cycles,with comparably initial performance and faster convergence in the training process.

关键词： Energy management strategies Deep reinforcement learning Dueling network architecture Transfer learning

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A Novel Three-Phase Passive Auxiliary Resonant Pole Soft-Switching Inverter With Symmetrical Auxiliary Networks and Electric Energy Feedback Function

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International Journal of Circuit Theory and Applications 2025年第0期

作者： Wang, Shuyu Liu, Hongchen Gao, Fei Wheeler, Patrick School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China Department of Engineering Science Shanghai Jiao Tong University Shanghai China Power Electronics Machines and Control Research Institute University of Nottingham Santiago Chile

To solve the problems of high cost, large additional component size, large circulating loss, and complex control in existing auxiliary resonant soft-switching inverters, a three-phase passive auxiliary resonant pole inverter (ARPI) with symmetrical auxiliary networks and electric energy feedback function is proposed. On each phase bridge arm of the inverter, a set of passive auxiliary networks (PANs) without large electrolytic capacitors, transformers, and other devices is provided, which is capable of enhancing the power density of the inverter. Additionally, as the auxiliary commutation circuit does not employ auxiliary switches, it not only lowers the hardware cost but also simplifies the control complexity and enhances the reliability of the soft-switching inverter operation. The proposed topology is capable of enhancing the utilization ratio of DC voltage and reducing the harmonic content of the output waveform. According to the equivalent circuit diagrams in different operating modes, the soft-switching operating principle and realization conditions of soft-switching for the proposed ARPI are analyzed. The parameters of passive components are designed with the aim of minimizing the PAN loss. A 3-kW experimental prototype is constructed. The experimental results indicate that the switching tubes can realize the soft-switching action and suppress the rate of change of voltage and current. The efficiency of the prototype can reach 98.30% at the rated output power, which is a remarkable improvement compared with the same type of ARPIs. © 2025 John Wiley & Sons Ltd.

关键词： Poles

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Depth-Aware Multi-Modal Fusion for Generalized Zero-Shot Learning 22

Depth-Aware Multi-Modal Fusion for Generalized Zero-Shot Lea...

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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Cao, Weipeng Yao, Xuyang Xu, Zhiwu Pan, Yinghui Sun, Yixuan Li, Dachuan Qiu, Bohua Wei, Muheng Shenzhen China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China College of Computer Science and Software Engineering Shenzhen University Shenzhen China Stony Brook University New York United States Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China ZhenDui Industry Artificial Intelligence Co. Ltd Shenzhen China Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

ISBN: (纸本)9798331527471

Realizing Generalized Zero-Shot Learning (GZSL) based on large models is emerging as a prevailing trend. However, most existing methods merely regard large models as black boxes, solely leveraging the features output by the final layer while disregarding potential performance enhancements from other layers. Indeed, numerous researchers have visually depicted variations in the features learned across different layers of neural networks. Motivated by this observation, we propose a Vision Transformer (ViT)-based GZSL method named Depth-Aware Multi-Modal ViT (DAM2ViT), which exploits multi-level features of ViT. DAM2ViT incorporates a multi-modal interaction block to align semantic information of categories across multiple layers, thereby augmenting the model’s capacity to learn associations between visual and semantic spaces. Extensive experiments conducted on three benchmark datasets (i.e., CUB, SUN, AWA2) have showcased that DAM2ViT achieves competitive results compared to state-of-the-art methods. © 2024 IEEE.

关键词： Zero-shot learning

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A Real-time Local Planner Design for Smart Wheelchairs Based on Koopman Bilinear Model Predictive control

A Real-time Local Planner Design for Smart Wheelchairs Based...

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IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Guanfeng Yu Han Zhang Zehao Wang Jingchuan Wang Department of Automation Institute of Medical Robotics Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (数字)9798350372601

ISBN: (纸本)9798350372618

The paper introduces a Koopman bilinear model predictive control (KBMPC) as a local planner for smart wheelchair systems. This approach leverages the Koopman Operator to streamline the nonlinear terms in MPC, aiming to achieve superior real-time performance. In particular, we employ the Extended Dynamic Mode Decomposition (EDMD) method to approximate the infinite dimensional Koopman operator. To tackle the challenge of designing lifting functions, we systematically utilize the derivatives of known nonlinear structures to methodically derive lifting functions. This systematic approach facilitates the identification of a precise bilinear model. Next, we formulate the corresponding Koopman bilinear MPC problem. Finally, an iterative algorithm is employed to efficiently solve the KBMPC problem. This method linearizes the bilinear model around estimations and iteratively solves the resulting quadratic programming problem to refine estimations. This allows KBMPC to function as a real-time local planner for smart wheelchairs. The prediction of nonlinear terms shows that the identified Koopman bilinear model increases the prediction accuracy. Furthermore, experiments demonstrate the advantages of the designed KBMPC local planner, highlighting its superior real-time performance and predictive capabilities.

关键词： Pedestrians Accuracy systematics Wheelchairs Estimation Predictive models Real-time systems

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Path Planning Using Improved Hybrid A* Algorithm for Mobile Robots

Path Planning Using Improved Hybrid A* Algorithm for Mobile ...

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system Simulation Technology and its Application (CCSSTA), IEEE China Conference on

作者： Zikang Cheng Jingbo Xue Bo Wang Guangzhong Dong Jingwen Wei Chunlin Chen Department of Control Science and Intelligence Engineering Nanjing University Naning China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen Shenzhen China

ISBN: (数字)9798350366600

ISBN: (纸本)9798350366617

The Hybrid A* algorithm is suitable for Ackermann-type mobile robots with nonholonomic constraints. However, in practical path planning, such issues as long search times, inefficient search efficiency, and excessive planning path changes causing unstable robot motion still exist. To improve the effectiveness of path planning, this paper optimizes the Hybrid A* algorithm by using variable search step size and designing a path evaluation function during node expansion. Path planning experiments are conducted based on simulation and physical experimental platforms. The results show that the improved algorithm reduces the search nodes and planning time, effectively enhancing the algorithm’s search performance and efficiency. In addition, it avoids pose errors caused by reverse driving, ensuring the priority and smoothness of forward driving, and achieves efficient and stable path planning for Ackermann-type mobile robots.

关键词： Robot motion Path planning Planning systems simulation Mobile robots

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loTs and Loop-Mediated Isothermal Amplification- Based Biosensing using Cloud-Enabled Features

loTs and Loop-Mediated Isothermal Amplification- Based Biose...

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2022 Medical Technologies Congress, TIPTEKNO 2022

作者： Bayindir, Taha Degirmenci, Mehmet Ergenc, Ali Fuat Elitas, Meltem Sabanci University Faculty of Engineering and Natural Sciences Istanbul Turkey Izmir Institute of Technology Department of Bioengineering Izmir Turkey Istanbul Technical University Faculty of Control and Automation Engineering Istanbul Turkey

ISBN: (纸本)9781665454322

Internet-of-Things technology (IoTs) have accelerated biosensor applications in all fields. Loop-mediated isothermal amplification (LAMP)-based biosensor technologies in conjunction with smartphone detection have been adequate to cover the demands of mobile diagnostics. The ease of use, affordability, portability, high sensitivity, flexibility, and specificity demands of point-of-care detection can be achieved by low-cost electronic components, 3-dimensional printing technologies, capturing images of calorimetrically detected readouts made our system a promising approach for real-time point-of-detection in the field. In this study, we implemented a cloud service to our LAMP-based biosensor. We previously performed bacteria detection using colony-based LAMP device and now distributed the optical readouts of the assay using smartphones. We transferred the obtained image and results of the assays through cloud. Our user-friendly interface simplifies the data processing, it directly digitized the readouts and eliminates the need of data interpretation. © 2022 IEEE.

关键词： Biosensors

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K-BMPC: Derivative-based Koopman Bilinear Model Predictive control For Tractor-trailer Trajectory Tracking With Unknown Parameters

K-BMPC: Derivative-based Koopman Bilinear Model Predictive C...

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IEEE International Conference on Robotics and automation (ICRA)

作者： Zehao Wang Han Zhang Jingchuan Wang Department of Automation Institute of Medical Robotics Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China and Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Nonlinear dynamics bring difficulties to controller design for control-affine systems such as tractor-trailer vehicles, especially when the parameters in the dynamics are unknown. To address this constraint, we propose a derivative-based lifting function construction method, show that the corresponding infinite dimensional Koopman bilinear model over the lifting function is equivalent to the original control-affine system. Further, we analyze the propagation and bounds of state prediction errors caused by the truncation in derivative order. The identified finite dimensional Koopman bilinear model would serve as predictive model in the next step. Koopman Bilinear Model Predictive control (K-BMPC) is proposed to solve the trajectory tracking problem. We linearize the bilinear model around the estimation of the lifted state and control input. Then the bilinear Model Predictive control problem is approximated by a quadratic programming problem. Further, the estimation is updated at each iteration until the convergence is reached. Moreover, we implement our algorithm on a tractor-trailer system, taking into account the longitudinal and side slip effects. The open-loop simulation shows the proposed Koopman bilinear model captures the dynamics with unknown parameters and has good prediction performance. Closed-loop tracking results show the proposed K-BMPC exhibits elevated tracking precision with the commendable computational efficiency. The experimental results demonstrate the feasibility of K-BMPC.

关键词： Trajectory tracking Computational modeling Estimation Predictive models control systems Data models Nonlinear dynamical systems

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