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SSRN 2024年

作者： Li, Weipeng Chong, Yuting Guo, Xin Liu, Jun School of Automation and Information Engineering Xi’an University of Technology No. 5 Jinhua South Road Shaanxi Xi’an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing No. 5 Jinhua South Road Shaanxi Xi’an710048 China

Efficient and accurate wind power prediction is crucial for enhancing the reliability and safety of power system operation and management. The integration of advanced data-driven forecasting methods with precise and efficient data feature decomposition and extraction techniques is necessary to improve the accuracy of wind power generation prediction, due to the inherent randomness and nonlinearity of physical states impacting wind power output, as well as the abundance of redundant information in their original measurement data. This paper proposes a novel hybrid wind power prediction model based on seasonal feature decomposition of wind energy data and enhanced feature extraction. Its effectiveness and superiority are demonstrated through comprehensive multi-model comparisons. © 2024, The Authors. All rights reserved.

关键词： Wind power

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End-To-End Autonomous Exploration for Mobile Robots in Unknown Environments through Deep Reinforcement Learning

End-To-End Autonomous Exploration for Mobile Robots in Unkno...

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2022 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2022

作者： Li, Zhi Xin, Jinghao Li, Ning Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China Department of Automation Shanghai Jiao Tong University Shanghai200240 China

ISBN: (数字)9781665469838

ISBN: (纸本)9781665469838

Autonomous exploration in unknown environments is a significant capability for mobile robots. In this paper, we present an end-To-end autonomous exploration model based on deep reinforcement learning (DRL), which takes the sensor data and a novel exploration map as inputs, and directly outputs the motion control commands of the robot. In contrast to the existing DRL-based exploration methods, the proposed model has no requirements to be combined with the traditional exploration or navigation algorithms, resulting in lower computational complexity. We directly transfer the DRL-based model trained in the training map to four test maps with different sizes and layouts, and the results show that the robot can rapidly adapt to unknown scenes. Besides, a comparison study with RRT-exploration algorithm indicates that the proposed model can reach a higher map exploration rate within less distance and time. Furthermore, we also conduct experiments on the real physical robot to demonstrate the transferability of learned policy from simulation to reality. A video of our experiments in the Gazebo simulator and real world can be found here1 © 2022 IEEE.

关键词： Reinforcement learning

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Capture the Flag Based Assignment Algorithm for Tracking Task of Multi-UAVs 5

Capture the Flag Based Assignment Algorithm for Tracking Tas...

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5th International Symposium on Autonomous systems, ISAS 2022

作者： Dalei, Song Aoliang, Dai Xiaoqian, Wang Hongjun, Ma Donghui, Wei Shenyang University of Technology Shagnhai China School of Information Northeastern University Shagnhai China Beijing Research Institute of Mechanical Electrical Technology Key Laboratory of Complex System Control and Intelligent Collaboration Technology Beijing China

ISBN: (纸本)9781665487085

In order to solve the problem of real-time target allocation in the multi-UAVs task for cooperative tracking the moving targets on ground, based on the behavior model of capture the flag, this paper proposes a dynamic assignment algorithm, which has fast convergence performance, for cluster UAVs. Based on satisfaction and total flight distance, the proposed algorithm constructs the assignment target function, and the optimal value of the target function is achieved quickly and the uniform saturation tracking is realized for the target group through the behavior model of grabbing flags. Finally, compared with traditional genetic algorithm, the simulation results show that the algorithm has a significant improvement in convergence speed and single assignment imply operation speed with the increase of the number of assigned targets and cluster UAVs © 2022 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Genetic Algorithm for Block Relocation in Automated Warehouse 5

Genetic Algorithm for Block Relocation in Automated Warehous...

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5th International Conference on Artificial Intelligence Technologies and Applications, ICAITA 2023

作者： Wang, Gang Lian, Mingchang Ding, Wei Chen, Songhang Chen, Hao Quanzhou Institute of Equipment Manufacturing Haixi Institutes Chinese Academy of Sciences Quanzhou362200 China College of Computer and Cyber Security Fujian Normal University Fujian Fuzhou350001 China Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China Fujian Fuzhou350108 China Fujian Provincial Key Laboratory of Intelligent Identification and Control of Complex Dynamic System Quanzhou362200 China

ISBN: (纸本)9781643684840

This paper is based on the research background of block relocation in the automated warehouse and proposes a solution utilizing AGV to relocate goods within the warehouse. Building upon the automated warehouse layout and block relocation process, we formulate a mathematical model to minimize the the number of AGV moving goods and the total travel distance of the AGV. To solve the model, we develop an enhanced genetic algorithm, which zones the block relocation process into multiple stages. Each stage integrates conventional heuristic algorithms to enhance the efficiency of the solution process. The improved genetic algorithm can effectively solve the problem, significantly enhancing the automation level of the warehouse. © 2024 The Authors.

关键词： Genetic algorithms

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An Integrated Smart Manufacturing Platform Powered by Microservices

An Integrated Smart Manufacturing Platform Powered by Micros...

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Asian control Conference

作者： Yuxiang Liu Mengqi Han Annan Xu Qi Liu Bo Yang Department of Automation Shanghai Jiao Tong University Shanghai China 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)9789887581598

ISBN: (纸本)9798331540845

With the rapid development of the manufacturing industry, traditional control systems can no longer meet the requirements of flexibility, efficiency, and intelligence for smart manufacturing. In order to fully utilize technologies such as microservices and enhance the flexibility of smart manufacturing, we propose a microservice-based architecture integrating sensing, communication, computation, and control, dedicated to achieving integrated management and configuration of the production process. In this architecture, each production stage is designed as an independent microservice, capable of being flexibly deployed in various edge controllers. Therefore, a universal edge controller can simultaneously act as a PLC, router, data acquisition device, and edge server, greatly simplifying the complexity of equipment deployment. The microservice-based integrated architecture not only improves the efficiency of data routing but also helps simplify the integration of new sensors and actuators, making adjustments of production lines more convenient, thereby enhancing the scalability and flexibility of the system. We implemented the proposed architecture based on a validation scenario, and the experimental results demonstrate the enormous development potential of this architecture.

关键词： Scalability Microservice architectures Restful API Computer architecture Production Routing Sensor systems

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CDP-GAN:Near-Infrared and Visible Image Fusion Via Color Distribution Preserved GAN

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1698-1701页

作者： Jun Chen Kangle Wu Yang Yu Linbo Luo the School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex SystemsEngineering Research Center of Intelligent Technology for Geo-ExplorationMinistry of EducationChina University of GeosciencesWuhan 430074China the Shanghai Institute of Technical Physics Key Laboratory of Infrared System Detecting and Imaging TechnologyChinese Academy of SciencesShanghai 200083China the School of Mechanical Engineering and Electronic Information China University of GeosciencesWuhan 430074China

Dear Editor,This letter is concerned with dealing with the great discrepancy between near-infrared(NIR)and visible(VS)image fusion via color distribution preserved generative adversarial network(CDP-GAN).Different from the global discriminator in prior GAN,conflict of preserving NIR details and VS color is resolved by introducing an attention guidance mechanism into the ***。

关键词： details dealing preserving

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Motor Fault Diagnosis Under complex Working Conditions Based on Signal Fusion and CA-CNN

Motor Fault Diagnosis Under Complex Working Conditions Based...

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Chinese Automation Congress (CAC)

作者： Mingxuan Cai Qi Liu Yuxiang Liu Bo Yang Department of Automation Shanghai Jiao Tong University shanghai China Key Laboratory of System Control and Information Processing Shanghai Engineering Research Center of Intelligent Control and Management Ministry of Education of China Shanghai China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Accurate fault diagnosis plays a key role in the safe and efficient operation of electrical motors. Aiming at multiclass motor fault diagnosis under complex working conditions, a signal fusion-based fault diagnosis framework is proposed. Measurement parameters from different sensors are first transformed by wavelet denoising and fast Fourier transform (FFT). Then, multiple parameters spectrum and working condition information are integrated and converted into high-dimension matrices. Finally, a channel-attention-based convolution neural network (CA-CNN) is proposed to extract fault patterns from a reconstructed matrix and output diagnosis results. Experiment results on both simulated and experimental datasets verify the effectiveness of the proposed method.

关键词： Fault diagnosis Employee welfare Wavelet transforms Accuracy Fast Fourier transforms Motors Sensors Numerical models Velocity measurement Matrix converters

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Anti-occlusion Object Tracking Algorithm using Response Template Fusion and Combined Features

Anti-occlusion Object Tracking Algorithm using Response Temp...

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Chinese control and Decision Conference, CCDC

作者： Jing Wang Yuan Wei Yisong Liu Weichao Huang Ming Hu Faculty of Printing Packaging Engineerring And Digital Media Technology Xi’an University of Technology Xi’an China Shannxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China

The kernel correlation filtering algorithm cannot judge the occlusion by itself when the object is occluded by foreign objects, and the tracking performance is greatly affected. Aiming at this problem, this paper proposes an anti-occlusion object tracking algorithm that fuses response templates and combined features. The peak sidelobe ratio (PSR) is used to determine whether the object is occluded. When the object is partially occluded, a combined feature representation object model is introduced to enhance robustness, and a multi-response template with anti-occlusion performance is constructed to improve the performance of the object when it is occluded by foreign objects. The problem of reducing the available information, thereby improving algorithm performance. Experiments in the OTB-100 data set can prove that the success rate and accuracy of the algorithm have competitive results compared with the comparison algorithms.

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Robust Platoon control of Industrial Heavy-Load Autonomous Vehicles 12

Robust Platoon Control of Industrial Heavy-Load Autonomous V...

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12th International Conference on CYBER Technology in Automation, control, and intelligent systems, CYBER 2022

作者： Liu, Zhe Li, Xiang Wang, Hesheng MoE Key Lab of Artificial Intelligence Ai Institute Shanghai Jiao Tong University China School of Mechanical Engineering and Electronic Information China University of Geosciences China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

Platoon control of autonomous industrial vehicles contributes to improving the safety and reliability of cargo transportation in complex industrial scenarios, increasing traffic efficiency and saving energy. The platoon control of autonomous heavy-load industrial vehicles is much harder, as the high robustness requirements, low hardware ability and complex un-structural environments. This paper considers the platoon control task from the view-point of practical industrial applications. Firstly, the longitudinal dynamic model of the heavy-load industrial vehicle is transferred into a first-order damping acceleration response model by introducing the low-level feedback linearization control and compensations. Secondly, the synchronization control concept is introduced and a fully distributed control law is presented, which only requires the coupling information of the two nearest neighbors. In particular, in order to ensure the practical applicability, the information processing delays, data samplings and external control disturbances are explicitly modelled and the global stability analysis approach is presented. Finally, we provide real experiments using full-scale industrial heavy-load vehicles to demonstrate our effectiveness and robustness. © 2022 IEEE.

关键词： Accident prevention

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Research and Application of Composite Stochastic Resonance In Enhancement Detection

SSRN

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SSRN 2023年

作者： Gao, Rui Jiao, Shangbin Xue, Qiongjie Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi’an710048 China School of Electronic and Electrical Engineering Baoji University of Arts and Sciences Baoji721016 China

Aiming at the problem that the intermediate potential part of the traditional tristable method cannot be adjusted independently, a new composite stochastic resonance (NCSR) model is proposed by combining the Woods Saxon (WS) model and the improved piecewise bistable model. All the parameters in the new model have no coupling characteristics. Moreover, the model retains the characteristics of the independent parameters of WS model and the improved piecewise model has no output saturation. Understable noise environment, the new model is used to detect periodic signal and aperiodic signal, the detection results indicate that the new model has better noise utilization and better detection effect. Finally, through image denoising experiments, the output signal-to-noise ratio (SNR) and correlation number of NCSR method is higher than that of other commonly used linear denoising methods and classical SR methods under the same conditions, the effectiveness of the new model is verified. © 2023, The Authors. All rights reserved.

关键词： Image denoising

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