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IEEE International Conference on robotics and Biomimetics

作者： Shuai Yuan Boyu Wu Kaixuan Wang Peng Yu school of Information & Control Engineering Shenyang Jianzhu University Shenyang Liaoning Province China Shenyang Jianzhu University Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665481106

In this paper, through the noise analysis of the signal processing circuit of the photoelectric sensor, two noise reduction methods are proposed by reducing the feedback resistance of the transimpedance amplifier and integrating the overall signal processing circuit. These two noise reduction methods can reduce noise and improve the signal-to-noise ratio while ensuring that the topography signal of the item is unchanged. To verify the method in this paper, the scanning head design was optimized, the feasibility of the proposed scheme was verified by the thermal noise method and the 0-range scanning method, and finally, the roughness specification was analyzed.

关键词： Noise reduction Force Signal processing Robot sensing systems Thermal noise Thermal analysis Noise measurement

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Research and optimization of conflict search algorithm for multi-agent path planning based on incremental heuristic 2

Research and optimization of conflict search algorithm for m...

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2nd International Conference on Computer Vision and Data Mining, ICVDM 2021

作者： Li, Yang Wang, Jun Zhang, Hualiang School of Computer Science Shenyang University of Chemical Technology Shenyang110142 China 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

Conflict Based Search(CBS) is used for multi-agent Pathfinding (MAPF) to enable each Agent to reach the target node. The CBS algorithm uses the heuristic algorithm A* search to calculate the MAPF solution, and the path planning uses forward search, which cannot explore the path of the unknown region. On this basis, this paper proposes that, in the case of unknown map and changing environment at any time, when encountering new obstacles, the information obtained from previous search should be used without completely replanning the path. Because of the idea of incremental programming, the number of reprogramming times and the number of affected nodes can be reduced. The optimized algorithm consumes less time and memory, and improves the efficiency of path planning. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Motion planning

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Featherweight and high-precision closed-loop detection method

Featherweight and high-precision closed-loop detection metho...

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International Conference on Advanced Mechatronic Systems (ICAMechS)

作者： Tao Jiang Xianggui Tang Ping Li Linshuai Zhang Shuoxin Gu Lin Xu Qian Wang Enzhi Zhu School of Intelligent Medicine Chengdu University of Traditional Chinese Medicine Unmanned System Intelligent Perception Control Technology Engineering Laboratory of Sichuan Province Chengdu University of Information Technology Chengdu School of Automation Chengdu University of Information Technology Chengdu School of Automation Chengdu University of Information Technology Sichuan Province Chengdu School of Intelligent Medicine Chengdu University of Traditional Chinese Medicine School of Automation Chengdu University of Information Technology International Joint Research Center of Robotics and Intelligence System of Sichuan Province Chengdu School of Automation Chengdu University of Information Technology International Joint Research Center of Robotics and Intelligence System of Sichuan Province Chengdu School of Intelligent Medicine Chengdu University of Traditional Chinese Medicine Chengdu

One of the key technologies for autonomous driving is localization. Precise localization is inseparable from high-precision maps. Simultaneous Localization And Mapping (SLAM) is technologies for building maps and locating in unknown environments. One of the mainstream directions of current autonomous driving research is how to carry out efficient closed-loop processing over long periods of time, eliminating accumulated error in the odometer. Improving the accuracy of the map and ensuring the accuracy of localization is crucial for ensuring the safety of autonomous driving. Therefore, this paper proposes a featherweight and high-precision method for multi-sensor fusion of laser and GPS for loop detection. The closed-loop results are optimized together with IMU to improve the mapping accuracy.

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Fault Diagnosis Based on RseNet-LSTM for Industrial Process 5

Fault Diagnosis Based on RseNet-LSTM for Industrial Process

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5th IEEE Advanced Information Technology, Electronic and Automation control Conference, IAEAC 2021

作者： Yao, Peifu Yang, Shaojie Li, Peng China Copper Co.LTD Kunming China Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China

Aiming at the problems that conventional data-driven diagnosis methods are difficult to adaptively extract effective features from industrial process data, and do not make full use of the time series characteristics of process data, in this paper, a fault diagnosis method based on residual convolutional neural networks and long short-term memory networks (ResNet-LSTM) is developed. Firstly, the local spatial features of process data are captured by the deep residual convolution network. Then, the time series characteristics of process data are extracted by LSTM. Finally, the output of the fault category is performed through the softmax classifier. This method can extract features adaptively, more fully extract features in time series fault data, and effectively reduce the difficulty of deep neural network training. The benchmark Tennessee-Eastman (TE) process is used to validate performance of the proposed method. The ResNet-LSTM model is compared with the CNN, LSTM, ResNets, CNN-LSTM models, and the experiment results show that the ResNet-LSTM method achieves better performance. © 2021 IEEE.

关键词： Failure analysis

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Research on fault feature extraction of rotating machinery based on adaptive VMD and optimized CYCBD

Research on fault feature extraction of rotating machinery b...

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第34届中国控制与决策会议

作者： Ran Xie Ling Xiong Binbin Dan Zeyu Ren Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Key Laboratory of Metallurgical Equipment and Control of Ministry of Education School of Physics and Electronic Science Hunan Institute of Science and Technology

To solve the problem that early fault features of rotating machinery are difficult to extract,an adaptive k-value hierarchical variational mode decomposition(H-VMD) combined with optimized maximum second-order cyclostationarity blind deconvolution(CYCBD) fault feature extraction method is proposed in this *** decomposition of the vibration signal is performed with *** then the noise dominant component is denoised by wavelet threshold denoising(WTD).Furthermore,the improved autocorrelation-weighted correlated kurtosis(ACK)when CYCBD enhances the periodic shock component of the denoised signal is the fitness function of ChOA,and the envelope demodulation analysis of the feature-enhanced signal is performed using the teager energy operator(TEO).Simulation analysis and experimental results show that the interference of background noise can be effectively removed and the periodic shock component of the vibration signal be enhanced by the proposed method,which is a new feature extraction method for the fault diagnosis of rotating machinery.

关键词： Variational mode decomposition Maximum second-order cyclostationarity blind deconvolution Wavelet threshold denoising Teager energy operator Fault feature extraction

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Key Parameters Prediction for intelligent control and Energy Optimization Based on MIC-BWO-XGBoost

Key Parameters Prediction for Intelligent Control and Energy...

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Cyber-Energy Systems and intelligent Energy (ICCSIE), International Conference on

作者： Changyao Lv Yaqi Wang Yudong Chen Zhuo Yu Guoliang Hu Hongliang Wu Shuai Li Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Shanghai Aircraft Manufacturing Co. Ltd. Shanghai China College of Information Engineering Shenyang University of Chemical Technology Shenyang China

ISBN: (数字)9798350373318

ISBN: (纸本)9798350373325

In the aviation industry, anodic oxidation serves as a core process for surface modification of aluminum alloy components, albeit accompanied by high energy consumption. Accurate prediction of key parameters can offer decision support for the intelligent control and energy optimization of anodic oxidation. However, the limited sample size resulting from the high cost of data collection and the complex nonlinear patterns caused by the synergy of multiple factors pose a challenge in accurately predicting key parameters. Therefore, we propose a key parameters prediction method based on the Maximum Information Coefficient (MIC), Beluga Whale Optimization algorithm (BWO), and XGBoost algorithm. Considering the adverse impact of low correlation parameters on prediction accuracy, we first use MIC to extract features from the original data. Then, XGBoost is used to integrate multiple decision trees to ensure the strong fitting ability for nonlinear relationships. Compared to deep learning models, XGBoost performs well even in a limited sample size. In addition, considering XGBoost is prone to overfitting training data as an ensemble learning algorithm, we employ the BWO to optimize four key parameters of the model that are difficult to choose, thereby enhancing model's generalization. The model's performance is evaluated using Mean Squared Error (MSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE), with values of 0.04388, 0.09410, and 0.20730%, respectively. The experimental results demonstrate that the proposed method outperforms traditional approaches, enabling precise prediction of key parameters and holding significant value for the intelligent control and energy optimization of anode oxidation processes.

关键词： Microwave integrated circuits Accuracy Process control Prediction algorithms Feature extraction Data models Whale optimization algorithms Oxidation Optimization intelligent control

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Comparison of Vibration and Noise Characteristics between Radial Flux PMSMs And Axial Flux PMSMs

Comparison of Vibration and Noise Characteristics between Ra...

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International Conference on Electrical Machines and Systems (ICEMS)

作者： Mengfei Wei Chi Zhang Yunpeng Gao Yongzhou Qing Chinese Academy of Sciences Ningbo Institute of Materials Technology and Engineering Ningbo China University of Chinese Academy of Sciences Beijing China Zhejiang Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology Ningbo China Ningbo Jingwei Computer Numerical Control Company Limted

ISBN: (数字)9781665493024

ISBN: (纸本)9781665493031

Radial flux permanent synchronous machines (PMSM) and axial flux permanent magnet synchronous machines are two main types of rotating machines used in electric vehicles. The vibration and noise characteristics of the above two types of machines are seldom compared. In this paper, two radial flux PMSMs and two axial flux PMSMs with identical power and stator structure but different slot-pole combinations are proposed, and their electromagnetic vibration and noise performances are compared. Firstly, the performance of the four machines are introduced. Secondly, the time-space distribution of the electromagnetic force exerted on stator teeth are analyzed and compared. Finally, the electromagnetic vibration and noise analysis is conducted based on a multiphysics model. The difference of electromagnetic vibration and noise characteristics between radial flux PMSMs and axial flux PMSMs are revealed. In the meantime, the influence of slot-pole combinations on vibration and noise of PMSMs are also investigated.

关键词： Vibrations Permanent magnet machines Time-frequency analysis Modal analysis Electromagnetic forces Stators Power capacitors

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Position Sensorless control of Permanent Magnet Synchronous Motor Based on Adaptive Filtering Sliding Mode Observer

Position Sensorless Control of Permanent Magnet Synchronous ...

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第34届中国控制与决策会议

作者： Anna Wang Yingjie Xiong Tao Zhang College Of Information Science and Engineering Northeastern University School of Electrical Engineering Dalian University of Technology Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Key Laboratory of Networked Control Systems Chinese Academy of Sciences

In the position sensorless control strategy of permanent magnet synchronous motor(PMSM),the back-EMF method based on sliding mode observer(SMO) is favored because of its *** this paper,a SMO based on the piecewise sigmoid function is *** on the back-EMF observation error,the gain adaptation of the SMO is realized,which effectively reduces the high-frequency chattering problem of the conventional *** low-pass filter of the conventional SMO is improved,and an adaptive filter based on the back-EMF low-pass filter is *** to the back-EMF observation error,the cut-off frequency of the low-pass filter is changed in real-time,and the estimation of rotor position is *** Matlab/Simulink simulation verification,the control strategy is feasible and achieves a better control effect.

关键词： Sensorless control SMO Adaptive gain and Adaptive filter

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Joint Routing and Charging Problem of Electric Vehicles with Incentive-Aware Customers Considering Spatio-Temporal Charging Prices

SSRN

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SSRN 2022年

作者： Yao, Canqi Chen, Shibo Salazar, Mauro Yang, Zaiyue School of Mechatronics Engineering Harbin Institute of Technology Harbin150000 China Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering The Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen518055 China Control Systems Technology Group Department of Mechanical Engineering Eindhoven University of Technology EindhovenMB 5600 Netherlands

This paper investigates the scheduling problem of a fleet of electric vehicles, providing mobility as a service to a set of time-specified customers, where the operator needs to solve the routing and charging problem jointly for each EV. Hereby we consider incentive-aware customers and propose that the operator offers monetary incentives to customers in exchange for time flexibility. In this way, the fleet operator can achieve a routing and charging schedule with lower costs, whilst the customers receive monetary compensation for their flexibility. Specifically, we first propose a bi-level optimization model whereby the fleet operator optimizes the routing and charging schedule accounting for the spatio-temporal varying charging price, jointly with a monetary incentive to reimburse the delivery time flexibility experienced by the customers. Concurrently the customers choose their own time flexibility by minimizing their own cost. Second, we cope with the computational burden coming from this nonlinear bi-level optimization model with an accurate reformulation approach consisting of the KKT optimality conditions, a Big-M-based linearization method, and the zero duality gap of convex optimization problems. This way, we convert the proposed problem into a single-level optimization problem, which can be solved by a strengthened generalized Benders decomposition method holding a faster convergence rate than the generalized Benders decomposition method. To evaluate the effectiveness of the proposed mathematical model, we carry out numerous simulation experiments by using the VRP-REP data of Belgium. The numerical results showcase that the proposed mathematical model can reduce the delivery fees for the customers together with the cost of operation incurred by the fleet operator. © 2022, The Authors. All rights reserved.

关键词： Sales

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Implementation of CAPI and Traditional PCIe and Delay of Comparison 5

Implementation of CAPI and Traditional PCIe and Delay of Com...

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5th IEEE International Conference on Cloud Computing and Big Data Analytics, ICCCBDA 2020

作者： Wang, Fudong Zhang, Tao Zhao, Bingjie Yang, Fan Li, Qingxin Li, Ziyang Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Key Laboratory of Networked Control Systemsm Chinese Academy of Sciences Liaoning Shenyang China

ISBN: (纸本)9781728160245

With the development of artificial intelligence technology and heterogeneous computing, heterogeneous communication speed is becoming more and more important. The latency of transmitting data determines whether a heterogeneous computing architecture is available. Current acceleration cards usually use PCIe interface. IBM developed the CAPI communication architecture for heterogeneous computing. This paper compares the technical principles and delays of the Power CAPI architecture and a high speed PCIe communication method. © 2020 IEEE.

关键词： Computer architecture

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