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A fault detection method for AUV based on multi-scale spatiotemporal feature fusion 5

A fault detection method for AUV based on multi-scale spatio...

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5th International Conference on Computer Information Science and Artificial Intelligence, CISAI 2022

作者： Xia, Shaoxuan Zhou, Xiaofeng Shi, Haibo Li, Shuai Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781510662520

Autonomous underwater vehicles (AUVs) are important equipment for ocean development and exploration. To ensure the task implementation of AUV, faults shall be detected in time. We propose a fault detection method based on multi-scale spatiotemporal feature fusion (MSF) for the time-varying characteristics and multiple correlation characteristics of AUV monitoring data. First, we apply a variety of sampling and data processing methods to generate monitoring windows with different scales along the time axis. Then, a composite feature extraction method is proposed to obtain temporal and spatial features simultaneously, and a feature pyramid of temporal and spatial information is formed. We use bidirectional long short-term memory (BiLSTM) to obtain the time-series characteristics of a single monitoring variable, and convolutional neural networks (CNN) to obtain the implicit spatial relationship characteristics among multiple monitoring variables. Next, we use an adaptive feature fusion method to solve the inconsistency in different feature scales, which can adaptively suppress the possible conflict information of different scale features. Finally, we use a fully connected network to detect the fault of the fused features. The fault detection experiment of Haizhe AUV shows the effectiveness and superiority of the proposed method. © 2023 SPIE.

关键词： Autonomous underwater vehicles

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Synchronous control Method and Simulation Research of Multi-degree of Freedom Humanoid Space Manipulator

Synchronous Control Method and Simulation Research of Multi-...

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Service robotics (ICoSR), International Conference on

作者： Tao Yang Fang Xu Baosen Du Yongjian Ni Chao Yu Yan Shi State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China Laboratory of Aerospace Servo Actuation and Transmission Beijing Institute of Precision Mechatronics and Controls State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

The high-precision multi-joint synchronous control problem of the 7 DOF humanoid manipulator is studied. The control system uses a distributed control architecture based on EtherCAT. synchronization error causes tracking error between the end trajectory of the manipulator with theoretical trajectory. In order to achieve the purpose of high-precision synchronous control of manipulators, the kinematics model of manipulators is analyzed, and the method of network distributed clock control mode based on EtherCAT is proposed. Firstly, according to the source of synchronous error of the manipulator, the distributed network clock is used to calibrate the controller master station and the servo slave station to reduce the sampling and control synchronization error of each joint, and then improve the real-time performance of the main station Linux operating system. The station position command synchronization error is calibrated. Finally, the semi-physical simulation system of the joint and manipulator controller in the ring is designed. The simulation experiment analysis of the humanoid manipulator in the joint space and Cartesian space is carried out. The results show that the clock is distributed based on the EtherCAT network. The multi-joint synchronization control method can realize high-precision position control of the humanoid manipulator.

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Identification of PMSM Moment of Inertia based on Model Reference Adaptive Algorithm 4

Identification of PMSM Moment of Inertia based on Model Refe...

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4th IEEE International Conference on Power, intelligent Computing and Systems, ICPICS 2022

作者： Ding, Fan Zhang, Tao Jia, Danping Zhang, Hualiang Pei, Quanshen Huang, Haoran School of Information Science and Engineering Shenyang University of Technology Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences School of Electrical Engineering Dalian University of Technology Dalian China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (数字)9781665467735

ISBN: (纸本)9781665467735

A method that can identify the rotational inertia in a timely manner is proposed because the performance of a permanent magnet synchronous motor servo system is easily affected by the rotational inertia. Firstly, principles of model-referenced adaptive recognition algorithm is introduced, and the influence of the adaptive gain on the identification results is analyzed. Then, design a suitable range of adaptive gain value, use the set error value to compare the identification error with the set value, and then select the appropriate gain for identification. Finally, through simulation verification, this method has fast identification convergence speed, high precision and strong anti-disturbance. © 2022 IEEE.

关键词： Adaptive algorithms

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Design, Kinematic and Variable Stiffness Analysis of a Tensegrity-Based Joint

Design, Kinematic and Variable Stiffness Analysis of a Tense...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Wu, Jinlong Liu, Gang Li, Ke Zhang, Niansong Yu, Zhiyuan Wu, Haiteng Liu, Yixiang Li, Yibin School of Control Science and Engineering Shandong University Jinan250061 China School of Mechanical Engineering Nanjing University of Science and Technology Nanjing210094 China School of Mechatronics Engineering and Automation Harbin Institute of Technology Shenzhen Shenzhen518055 China Beijing Institute of Precision Mechatronics and Controls Laboratory of Aerospace Servo Actuation and Transmission Beijing100076 China Hangzhou Shenhao Technology Co. Ltd Zhejiang Key Laboratory of Intelligent Operation and Maintenance Robot Hangzhou311121 China Jilin University Key Laboratory of Bionic Engineering Ministry of Education Jilin130022 China

ISBN: (纸本)9781665481090

In this paper, a new compact, low-inertia, and flexible tensegrity joint is proposed, which aims to overcome the shortcomings of traditional collaborative robots and tendon-driven robots. The joint is composed of two circular frames, and is connected by three surrounding pneumatic muscles and an intermediate spring. The stiffness of the joint is changed by inflating and releasing air to the pneumatic muscles, which is also the principle of the joint's variable stiffness. Firstly, a detailed kinematic analysis of the proposed tensegrity joint was carried out to explore its position change in multi-axis motion. Secondly, the stiffness analysis was carried out to evaluate the deformation response and stiffness characteristics of the joint under different loads, which provided an important reference for its design optimization. Finally, the performance of the model is verified by simulation analysis, and the reliability and practicability of the model in dynamic work are verified by comparison with actual data. This study provides a theoretical and experimental basis for the promotion of new tensegrity joints in robot applications, and provides new design ideas and methods for the development and innovation of future robotics technology. © 2024 IEEE.

关键词： Collaborative robots

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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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Full-state Physical Mirroring Method of Space Manipulator Based on the Multiple Decoupling Principles

Full-state Physical Mirroring Method of Space Manipulator Ba...

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Artificial Intelligence, Human-Computer Interaction and robotics (AIHCIR), International Conference on

作者： Tao Yang Shize Qin Fang Xu Songbo Deng Hao Zhang Yan Shi State Key Laboratory of Robotics Chinese Academy of Sciences Shenyang Institute of Automation Institutes for Robotics and Intelligent Manufacturing University of Chinese Academy of Sciences Beijing Institute of Precision Mechatronics and Controls Laboratory of Aerospace Servo Actuation and Transmission Beijing PR China Laboratory of Aerospace Servo Actuation and Transmission Beijing Institute of Precision Mechatronics and Controls Beijing PR China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang PR China

To achieve the goal of an efficient full-state ground test of a 7DOF space manipulator, the kinematic and dynamical coupling characteristics of space manipulator are investigated, and a mirror test method based on the principle of multiple decoupling is proposed to solve the problem of highly dynamic three-dimensional motion conditions of space manipulator that are difficult to verify by ground simulation. It firstly decouples the space manipulator into a 3dof unit,1dof unit and another 3dof unit combination. It achieves joint load reduction through inter-joint dynamics coupling. Afterwards, it designs an air-floating support device to realize the joint space 7DOF motion, and proposes a constant damping joint dynamics compensation control algorithm to eliminate the dynamics disturbances introduced by inter-joint decoupling. Then, an industrial mirror robot arm with consistent kinematic parameters and a highly dynamic mirror control algorithm are designed to map the joint motion states of the space manipulator to the ground robotic arm, and a ground simulation of the Cartesian space motion state of the space robot arm is realized by decoupling the joint space from the Cartesian space motion. Finally, the ground experiment of target grasping based on the physical mirroring method is designed to realize the high-speed full-state ground experiment verification of complex tasks of space manipulator.

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RESIDUAL LIFE PREDICTION OF LITHIUM BATTERY BASED ON IMPROVED MULTI-OPTIMIZATION ALGORITHM AND SUPPORT VECTOR REGRESSION 14

RESIDUAL LIFE PREDICTION OF LITHIUM BATTERY BASED ON IMPROVE...

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14th International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering, QR2MSE 2024

作者： Tao, Yulong Wang, Jun Wang, Kai School of Computer Science and Technology Shenyang University of Chemical Technology Shenyang China Key Laboratory of Intelligent Technology for Chemical Process Industry Liaoning Province Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Robotics and Artificial Intelligence Manufacturing Innovation Institute Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9781837242672

The lithium-ion battery is increasingly critical in the fields of electric vehicles and sustainable energy. Accurate prediction of the Remaining Useful Life (RUL) of lithium-ion batteries is essential to mitigate risks and minimize potential losses. This paper introduces a novel fusion algorithm, FPSOGWO, which combines Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) with an enhanced Circle chaos strategy and a random adaptive weighting strategy. The FPSOGWO algorithm, integrated with Support Vector Regression (FPSOGWO-SVR), was utilized to predict the RUL of health factors in lithium batteries. Compared to other optimization algorithms, FPSOGWO exhibits superior optimization speed and value, effectively overcoming issues of local optimality. Specifically, when benchmarked against the Whale Optimization Algorithm-SVR (WOA-SVR), the R-Square values of FPSOGWO-SVR showed improvements of 15.62%, 1.28%, 5.67%, and 10.65% across four different types of batteries. Experimental results demonstrate that FPSOGWO-SVR provides more accurate RUL predictions for lithium batteries, highlighting its potential for broader application in battery health management systems. © The Institution of Engineering & Technology 2024.

关键词： Support vector regression

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intelligent electricity consumption forecasting and electricity-theft analysis method based on deep learning 2

Intelligent electricity consumption forecasting and electric...

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2nd International Conference on Electronic Information Engineering and Computer Technology, EIECT 2022

作者： Yu, Shimao Song, Chunhe Gao, Pengpei Zheng, Haiyang Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang Institute of Automation Shenyang China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798350399561

Residential electricity consumption data have great mining value for electricity-theft analysis and electricity consumption forecasting. This paper designs an intelligent electricity consumption forecasting and electricity-theft analysis method based on deep learning. Firstly, the power consumption data of a single user is converted into multi-period data through preprocessing, and the data forecasting is realized by designing a deep neural network model. The electricity-theft data are first amplified through user's power data and electricity-theft labels. And then the time series are converted into two-dimensional tensors for classification and recognition by deep CNN. The classification accuracy of electricity-theft reaches 92.2% compared with RNN method. © 2022 IEEE.

关键词： Forecasting

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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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Research and Implementation of Industrial Real-Time Ethernet Scheduling Method Based on Time Slot Reuse

Research and Implementation of Industrial Real-Time Ethernet...

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Artificial Intelligence, Networking and Information Technology (AINIT), International Seminar on

作者： Mingxu Gang Bingjun Yan Bo Hu Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798350385557

ISBN: (纸本)9798350385564

To improve the operation efficiency and real-time scheduling capability of existing industrial control network systems, based on the existing industrial real-time Ethernet communication protocol technology, an industrial real-time Ethernet scheduling method based on time slot reuse is proposed. This method adopts the time-division multiplexing strategy, decomposes the continuous time into different time slots, configures the data of different types of nodes to be transmitted in their respective time slots, uses the peak shift clock synchronization method and timer trigger task mechanism to improve the real-time communication, and uses the time slot multiplexing mechanism to improve the data transmission efficiency; Finally, a test platform is built to verify the proposed method. The experimental results show that the proposed method has high clock synchronization accuracy and real-time scheduling capability.

关键词： Multiplexing Job shop scheduling Protocols Accuracy Industrial control Ethernet Real-time systems

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