检索结果-内蒙古大学图书馆

第34届中国控制与决策会议

作者： Ranjiang Wang Jiangbo Zhao Junzheng Wang Key Laboratory of Complex System Intelligent Control and Decision School of AutomationBeijing Institute of Technology Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information TechnologySchool of AutomationBeijing Institute of Technology

In this paper,according to the different dynamic models of the support phase and the swing phase,the joint torque compensation of the support phase and the swing phase are given to compensate the joint torque of the hydraulic quadruped robot controlled by the virtual model control(VMC).This compensation can increase the tracking effect of the foot end on the swing trajectory,reduce the elasticity and damping coefficient of the virtual model method,and increase the flexibility of the *** this paper establishes the touchdown detection function based on the joint torque obtained by the Lagrange dynamics equation and the joint torque obtained by the force sensor to determine the touch state of the foot of the quadruped robot to switch the phase of the *** the end of this paper,simulation and experiment prove that the compensation model and touchdown detection function model have feasibility and correctness.

关键词： Quadruped robot Torque compensation Touchdown detection Virtual model control

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Nonlinear Underwater Robot System Environmental Disturbance Suppression Based on Feedback Linearization and EID Method

Nonlinear Underwater Robot System Environmental Disturbance ...

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Asian control Conference

作者： Chengyu Li Xin Chen Yang Zhou Wei Tan Wenpeng He School of Future Technology China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Automation China University of Geosciences Wuhan China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

A disturbance suppression approach combining feedback linearization and equivalent input disturbance (EID) method is proposed to control nonlinear underwater robots' position. Firstly, the complex nonlinear model of the underwater robot is transformed into a linear model by feedback linearization. Then, to enhance the system's ability to reject unknown disturbances in the marine environment, the EID method is utilized for estimation and compensation. This helps improve the system's ability to handle disruptions. Additionally, a linear quadratic regulator (LQR) is employed to ensure system stability and achieve rapid convergence. Finally, the proposed approach is validated by demonstrating its effectiveness through simulation results.

关键词： Autonomous underwater vehicles Regulators Simulation Position control Mathematical models Stability analysis Feedback linearization

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A Novel Rate of Penetration Optimization Method for Vertical Wells Based on an Improved Particle Swarm Optimization Algorithm

A Novel Rate of Penetration Optimization Method for Vertical...

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Asian control Conference

作者： Yang Zhou Peng Zhang Xiao Wu Xin Chen Min Wu School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Future Technology China University of Geosciences Wuhan China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

The rate of penetration serves as a crucial indica-tor reflecting drilling rig efficiency. Maintaining high drilling speed is crucial in reducing drilling costs and non-drilling time. However, due to the complex nonlinearity inherent in the drilling process, optimizing and adjusting drilling speed faces high-dimensional variations and intricate constraints. This complex nonlinearity makes it challenging to obtain a suitable set of operating parameter values. To overcome these difficulties in rate of penetration optimization, we propose a novel rate of penetration optimization method aimed at addressing high-dimensional changes and complex constraints. First, the support vector regression method is introduced to formulate the drilling rate optimization problem. Then, an improved particle swarm optimization algorithm (IPSO) is developed to address the chal-lenge of high-dimensional variation in drilling rate optimization. Moreover, a method for analyzing vertical well longitudinal force is introduced to handle constraints. IPSO demonstrates superior global search capabilities compared to other algorithms in the IEEE CEC2015 benchmark functions. The developed drilling optimization method is validated using actual data. Results from two groups of experiments indicate that compared to manual adjustment, the developed method improved by 15.31 % and 15.38 %, respectively.

关键词： Drilling Support vector machines Simulation Optimization methods Process control Manuals Benchmark testing

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Modeling the Kinematics and Dynamics of the Pedaling Lower-Limb Rehabilitation Robot

Modeling the Kinematics and Dynamics of the Pedaling Lower-L...

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intelligent systems, International Workshop on

作者： Hao Zhang Juan Zhao Feng Wang Seiichi Kawata Jinhua She School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo- Exploration Ministry of Education Wuhan China School of Engineering Tokyo University of Technology Hachioji Tokyo Japan

ISBN: (数字)9798350353303

ISBN: (纸本)9798350353310

Lower-limb rehabilitation robots are becoming increasingly prevalent in rehabilitation training. Accurate modeling helps to develop an effective rehabilitation program. This paper analyzes the physiological structure and joint motion characteristics of the human lower limbs using a pedaling lower-limb rehabilitation robot. We establish a simplified three-link model of the human lower limbs and apply the Denavit-Hartenberg (D-H) parametric method to analyze the joint range of motion, determining geometric parameters and boundary conditions. The forward kinematics analysis derives the expression for the end position of the three-link model, and inverse kinematics calculates joint angles, velocities, and accelerations. Using Lagrange's dynamical equations, we compute the torque required by each joint for different motion states, establishing the foundation for subsequent controller design. Finally, joint angles and torques were simulated in MATLAB. The results verified the feasibility of the model.

关键词： Training Analytical models Torque Computational modeling Dynamics Kinematics Assistive robots Robot sensing systems Mathematical models Optimization

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Field-Free Current-Induced Switching of L10-FePt Using Interlayer Exchange Coupling for Neuromorphic Computing

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Physical Review Applied 2023年第2期19卷 024034-024034页

作者： Kaifeng Dong Zhe Guo YiYi Jiao Ruofan Li Chao Sun Ying Tao Shuai Zhang Jeongmin Hong Long You School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan 430074 China School of Optical and Electronic Information and Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Wuhan 430074 China

L10-phase FePt is well known for its unusually robust perpendicular magnetic anisotropy (PMA) properties arising from strong conduction-electron spin-orbit coupling (SOC) with the Fe orbital moment. The strong PMA enables stable magnetic storage and memory devices with ultrahigh capacity. Meanwhile, SOC is also the premise of the recently discovered spin-orbit-torque (SOT) effect, which opens avenues for possible electrical manipulation of magnetization for L10-FePt. The bulk SOT of the L10-FePt single layer was discovered recently; this leads to the magnetization of L10-FePt reversibly switching on itself. However, deterministic SOT switching of bulk perpendicularly magnetized FePt magnets relies on an external magnetic field to break the symmetry. Here, the symmetry-breaking issue is resolved by interlayer exchange coupling, where the FePt layer is coupled with an in-plane magnetized NiFe layer through a TiN spacer layer. Furthermore, our device also presents memristive or gradual switching behaviors, even without an external field, offering the potential for constructing spin synapses and spin neurons for neuromorphic computing. An artificial neural network with high accuracy (∼91.17%) is realized based on the constructed synapses and neurons. Our work paves the way for field-free SOT switching of single bulk PMA magnets and their potential applications in neuromorphic computing.

关键词： Exchange interaction Magnetic anisotropy Magnetization switching Spin-orbit torque Spintronics

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That-Net: Two-Layer Hidden State Aggregation Based Two-Stream Network for Traffic Accident Prediction

SSRN

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SSRN 2023年

作者： Liu, Wei Zhang, Tao Lu, Yisheng Chen, Jun Wei, Longsheng School of Automation China University of Geosciences Wuhan430074 China Key Laboratory of Geological Survey and Evaluation Ministry of Education Wuhan430074 China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

With the bursting of autonomous and assistant driving systems, traffic accident prediction has attracted increasing attention during the past few years. However, predicting traffic accidents is extremely challenging due to the complexity of traffic scenarios and the variability of traffic object's motion states. Existing algorithms contain all traffic objects and all video frames indiscriminately in the prediction model, which correspondingly reduces the prediction accuracy. To solve this problem, we propose a two-layer hidden state aggregation based two-stream network (THAT-Net) to construct a more accurate prediction model. The proposed model fuses two streams to achieve complementary spatio-temporal information, in which optical flow features are introduced to 'remove' irrelevant objects of accident. Furthermore, two-layer hidden state aggregation structure is adopted to reintegrate the hidden state weights of gated recurrent units to reduce the influence of irrelevant frames. Comprehensive experimental results on both benchmark datasets demonstrate state-of-the-art performance of THAT-Net, especially on the challenging Dashcam Accident dataset. Our code is available at: https://***/redeyezt/THAT-Net. © 2023, The Authors. All rights reserved.

关键词： Benchmarking

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Energy-Aware Coverage control of Multi-Agent systems with control Barrier Function

Energy-Aware Coverage Control of Multi-Agent Systems with Co...

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Chinese control Conference (CCC)

作者： Chengkai Qu Chao Zhai School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

Geo-hazards have become one of the main disasters endangering the safety of people's lives and property in the world. In order to improve the early warning of disasters, a persistent monitoring method of multi-agent systems is proposed in this work. To ensure that the agent's energy is never exhausted, the set invariance constraint is included in the optimization problem. The goal is to minimize the difference between the actual control input of the robot and the nominal control input corresponding to the task to be performed. Moreover, the control barrier function (CBF) is used to transform the forward invariance of a subset of the robot state space into a control input constraint. The coverage control method in an uncertain environment is verified by numerical simulation. This work provides new insights into effective monitoring and early warning of geo-hazards.

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Template Matching and Trend Feature Analysis-Based Data Pre-Processing Method for Seismic Wave Detection

Template Matching and Trend Feature Analysis-Based Data Pre-...

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Chinese automation Congress (CAC)

作者： Zheng Xu Chao Gan Weihua Cao School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

In this paper, a template matching and trend feature analysis-based data pre-processing method for seismic wave detection is proposed with two stages. In the first stage, it involves extracting the rock physical parameters from seismic wave detection results using OCR (Optical Character Recognition) method, and extracting the original rock physical parameters from the raw rock property table using keyword matching method. Using the rock physical parameters as a template, a template matching approach is employed to eliminate abnormal values from the original rock physical parameters. In the next stage, a technique is proposed to extract trend features of rock physical parameters for conducting advanced geological forecasting, which considered the expertise of experts in interpreting seismic wave detection data. Finally, the effectiveness of the proposed method is verified by the compared simulation results.

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Prediction of Silicon Content in Molten Iron of Blast Furnace Based on Multi-dimensional Sequential Characteristic Reconstruction

Prediction of Silicon Content in Molten Iron of Blast Furnac...

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Industrial Cyber-Physical systems (ICPS)

作者： Zhuofu Zhang Weihua Cao Jie Hu Qifu Chen Min Wu School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

Molten iron is the primary output of blast furnace production. The content of silicon in molten iron clearly correlates with blast furnace temperature. However, due to the intricate conditions of blast furnace production, the silicon content in molten iron is nonlinear and unstable. Therefore, this paper adopts variational mode decomposition (VMD) to decompose and extract the feature information of the real silicon content data of LY Steel in March 2022, then uses Grey Wolf optimization (GWO) algorithm to optimize the parameters of the support vector regression (SVR) prediction model, and takes the decomposed data as model input for experimental verification. By comparing the predicted results with the real historical data of blast furnace production, it is found that the degree of fit is about 94.2%, which offers a new idea for the prediction of silicon content.

关键词： Support vector machines Production Predictive models Blast furnaces Prediction algorithms Feature extraction Silicon

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A StyleGAN3-Based Data Augmentation Method for Ceramic Defect Detection

A StyleGAN3-Based Data Augmentation Method for Ceramic Defec...

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Industrial Cyber-Physical systems (ICPS)

作者： Huimin Ou Jianqi An Xing-ao Wang Jianru Xiong Xin Chen Qingyi Wang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

Deep learning is currently the mainstream method for ceramic defect detection, and it requires a large number of defect samples to train the network. However, collecting these defect samples is very time-consuming and deep learning suffers from few-shot learning problems. In this study, a StyleGAN3-based data augmentation method for ceramic defect detection was proposed which can generate ceramic defect samples and thus reduce the data collection work. Experiments show that our method uses less training time, has a more stable training process, and can improve the accuracy of the detection network.

关键词： Training Deep learning Image synthesis Data collection Cyber-physical systems Data models Ceramics

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