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第34届中国控制与决策会议

作者： Ziyao Wang Yiye Wang Kanjian Zhang Haikun Wei Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSchool of AutomationSoutheast University

Natural Locomotion interface(NLI) is critical to expanding the users' exploration of scenes in virtual reality and improving user *** on the 2D motion platform,users can achieve a natural locomotion experience in a limited physical *** a small-scale 2D motion platform,an ideal situation is that the velocity of the platform can always be synchronized with the user's actual intended velocity,so that the user's center of mass is kept at the center of the *** puts a brand new requirement on the performance of the platform *** paper designs an acceleration-level state feedback controller for the small-scale 2D motion *** the user's intended acceleration as an external disturbance,it is estimated by introducing a disturbance state observer;for the user' s velocity on the platform,a linear state observer is used to estimate it;then takes the estimated values as feedforward terms to compensate the *** with the HCMK1 2D motion platform,we implemented the controller and verified it to be *** recording the data of the user walking along the circle and the square trajectory,it was verified that the designed controller has good control performance for the user's motion and the state observers a great performance to quickly track the user's intended acceleration and the user's velocity on the platform.

关键词： Virtual Reality Nature Locomotion Interface State Observer 2D-Motion Platform

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Design of redundant control system for Antarctic unattended energy platform based on RS-485

Design of redundant control system for Antarctic unattended ...

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第34届中国控制与决策会议

作者： Chenwei Sun Kanjian Zhang Haikun Wei Jian Ge Shixiong Fang Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSchool of AutomationSoutheast University

The successful operation of the Antarctic unattended energy platform with data storage and other functions can provide electric energy for other scientific research ***,its performance needs further improvement due to the lack of experience and the special environmental constraints of *** on the above reasons,this paper proposes an optimized design of unattended energy control platform from the perspective of improving the reliability and safety of the *** to the actual project requirements,the engine control system of the unattended energy platform is designed and *** control system part is designed as a control mode with RS-485 control combined with hardware interface features to realize the direct communication between the upper computer and the generator set and the related hardware control *** redundant control is added to effectively avoid the loss of connection of key equipment of the whole device due to irreparable failure of PLC in the previous system,which improves the reliability of the platform system.

关键词： RS-485 communication Redundant control system Data acquisition and Reliability

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A Fast-trained and Generalized Spiking Neural Network for Robotic Gas Source Localization

A Fast-trained and Generalized Spiking Neural Network for Ro...

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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Chiyang Liu Xinxing Chen Jian Huang Hubei Key Laboratory of Brain-inspired Intelligent Systems and the Key Laboratory for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen China

ISBN: (数字)9798350385724

ISBN: (纸本)9798350385731

Mobile robots for Gas Source Localization (GSL) tasks are a safer alternative than human and animal rescuers in hazardous scenarios. Existing research primarily concentrates on rule-based algorithms or conventional artificial neural networks (ANNs). However, these approaches are either inapplicable in cluttered environments or undeployable due to their high energy consumption and the demand for substantial computational resources. This paper introduces the application of energy-efficient spiking neural networks (SNNs) to address robotic GSL tasks. A pipeline is proposed to train SNNs with deep Q learning and a pretrain-finetune paradigm. To facilitate the training process, a small dataset of gas dispersion is generated utilizing openFoam and GADEN, a high-fidelity simulator for gas dispersion. Data from a simplified plume model are leveraged to pretrain an ANN, the activation function of which gradually transitions from a bounded rectified linear unit (bReLU) to a step function. Subsequently, an SNN initialized with the ANN parameters undergoes finetuning on the GADEN-based dataset. The training pipeline significantly reduces training time compared to direct training of SNNs. The trained SNN is validated within the GADEN simulation environment and compared to three different models, demonstrating promising performance and superior generalization despite limited training data.

关键词： Training Location awareness Q-learning Mechatronics Pipelines Training data Spiking neural networks Data models Mobile robots Dispersion

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Hotspot detection of photovoltaic modules in infrared thermal image based on saliency analysis

Hotspot detection of photovoltaic modules in infrared therma...

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第34届中国控制与决策会议

作者： Yiye Wang Yu Shen Chenxi Li Kanjian Zhang Haikun Wei Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSchool of AutomationSoutheast University

With the increasing awareness of environmental protection,the solar photovoltaic(PV) industry has been developing dramatically in recent *** module is an important part of PV power generation *** all the defect types of PV modules,hotspots occur more frequently and cause more serious ***,it is necessary to detect *** approach is proposed using saliency analysis method for hotspot detection,combing the cognitive property about visual saliency and the temperature property of *** only does this approach not require manual threshold setting,but also it does not require a large number of learning *** approach can also achieve the defect diagnosis and hotspot location when compared with the electrical characterization *** infrared thermal(IRT)images trained in experiments are obtained using the thermographic camera FLIR Vue Pro with the unmanned aerial vehicle from a PV plant in Jiangsu,*** 135 IRT images are collected and 1020 PV modules are extracted from these *** have proved great accuracy and robustness when using the proposed method to detect hotspots.

关键词： Hotspot PV module IRT image Saliency analysis Graph

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Automatic Reading System of Pointer Meters in Gas Gathering Stations

Automatic Reading System of Pointer Meters in Gas Gathering ...

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第34届中国控制与决策会议

作者： Yaqing Chang Kanjian Zhang Haikun Wei Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSchool of AutomationSoutheast University

In gas gathering stations,pointer meters are usually read by workers,which takes high labor costs and has low *** solve these problems and build intelligent gas gathering stations,this paper proposes an automatic reading system for real-time and accurate pointer meter reading.A new dataset is first constructed,which consists of700 pointer meter images with different angles,illumination and *** on the dataset,the deep learning model YOLOv5 is trained for dial and pointer *** the pointer mask output by YOLOv5,image preproces sing is used to separate the pointer from the background and generate the pure *** improved skeleton extraction algorithm and the Hough line detection algorithm are combined to extract the pointer center *** the dial image output by YOLOv5,feature matching and perspective transformation are adopted for position ***,pointer reading is obtained by applying the angle method to the corrected dial and the pointer center *** experiments demonstrate the high accuracy and efficiency of the proposed *** strong robustness to various interference factors in complex environments are also validated.

关键词： Pointer Meter Automatic Reading YOLOv5 Object Detection Skeleton Extraction

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A CNN-ELM Compound Fault Diagnosis Method Based on Joint Distribution Modification 7

A CNN-ELM Compound Fault Diagnosis Method Based on Joint Dis...

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7th International Conference on Information, Cybernetics, and Computational Social systems, ICCSS 2020

作者： Dong, Jiechao Yan, Liping Xia, Yuanqing Zhang, Jinhui Wang, Xianghua Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Shandong Key Laboratory of Big-data Driven Safety Control Technology for Complex Systems Shandong266590 China

ISBN: (纸本)9781728162461

In the industrial field, compound faults often occur on rolling bearings and it's difficult to diagnose them correctly. To solve this problem, this article proposes a CNN-ELM compound fault diagnosis method based on joint distribution modification. Firstly, considering the complementarity and coupling of data from multiple sensors, a data input trick of multi-sensor data connected in parallel is designed. Secondly, due to the discrepancy of distribution between the compound fault data features and the single fault data features, the marginal distribution matrix and the posterior distribution matrix are used to modify the CNN-ELM network, so that the network can extract more reliable data features for fault diagnosis. Finally, referring to the categories and criteria of bearing damage proposed by Paderborn University, the label code is defined. The corresponding data set is used to verify the proposed algorithm. Experimental results show that the algorithm can accurately obtain detailed fault information such as fault location, fault type, and fault severity. © 2020 IEEE.

关键词： Roller bearings

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Dynamics Modeling Method of Offshore Drilling Experimental System Based on Double-Layer Stewart Parallel Mechanism

Dynamics Modeling Method of Offshore Drilling Experimental S...

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Chinese control Conference (CCC)

作者： Chenxuan Wang Zhejiaqi Ma Chengda Lu Sheng Du Min Wu 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

Establishing the dynamics model of the offshore drilling experimental system can better complete the offshore drilling test in the laboratory environment and reduce the cost of testing. A dynamical modeling method for the offshore drilling experimental system built on the double-layer Stewart parallel mechanism is proposed. Firstly, the kinematic and dynamical characteristics of the double-layer Stewart parallel mechanism are combined with the Lagrange method and the virtual work method to establish the dynamics model of the mechanism. Then a parameter identification scheme is designed using a nonlinear gray system estimation method based on the trust-domain reflection algorithm, and the model parameters are identified. The model is downscaled to improve the feasibility of the identification scheme and the accuracy of the identified parameters. The actual experimental system data verify this model's correctness and the model parameters' accuracy.

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A Cell Potential and Motion Pattern Driven Multi-robot Coverage Path Planning Algorithm 14th

A Cell Potential and Motion Pattern Driven Multi-robot Cover...

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14th International Conference on Bio-inspired Computing: Theories and Applications, BIC-TA 2019

作者： Xu, Meng Xin, Bin Dou, Lihua Gao, Guanqiang School of Automation State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9789811534249

This paper proposes an intelligent "Cell Potential and Motion Pattern driven Coverage (CPMPC)" algorithm to solve a cooperative coverage path planning problem for multiple robots in two-dimensional target environment. The target environment is divided into cell areas according to the detection range of robot, and the cell matrix is given correspondingly. The values in the cell matrix are defined as cell potential, which represents the number of times each cell is detected by robots. The priority of the robot’s neighbor cell is called the motion pattern. At different moments, robots can choose within different motion patterns. Genetic algorithm (GA) is used to optimize the combination of motion patterns. By taking account obstacle avoidance and collision avoidance into consideration, the CPMPC algorithm adopts a double-layer choice strategy driven by cell potential and motion pattern to generate the next waypoint. Furthermore, this algorithm contains two optimal strategies: avoiding collision and jumping out of the detected area. Compared with the pattern-based genetic algorithm, the results obtained by us show that the CPMPC algorithm could solve the multi-robot coverage path planning (MCPP) problem effectively with guarantee of complete coverage, and improved makespan. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Multipurpose robots

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A fuzzy control and neural network based rotor speed controller for maximum power point tracking in permanent magnet synchronous wind power generation system

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Global Energy Interconnection 2023年第5期6卷 554-566页

作者： Min Ding Zili Tao Bo Hu Meng Ye Yingxiong Ou Ryuichi Yokoyama School of Automation China University of GeosciencesWuhan 430074P.R.China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074P.R.China Global Energy Interconnection Group Co. LtdSTATE GRID Corporation of ChinaBeijing 100032P.R.China School of Environment and Energy Engineering Waseda UniversityTokyo169-8050Japan

When the wind speed changes significantly in a permanent magnet synchronous wind power generation system,the maximum power point cannot be easily determined in a timely *** study proposes a maximum power reference signal search method based on fuzzy control,which is an improvement to the climbing search method.A neural network-based parameter regulator is proposed to address external wind speed fluctuations,where the parameters of a proportional-integral controller is adjusted to accurately monitor the maximum power point under different wind speed ***,the effectiveness of this method is verified via Simulink simulation.

关键词： Maximum wind power tracking Fuzzy control Neural network

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A Novel Agricultural Data Sharing Mode Based on Rice Disease Identification

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Plant Diseases and Pests 2024年第2期15卷 9-16页

作者： Mengmeng ZHANG Xiujuan WANG Mengzhen KANG Jing HUA Haoyu WANG Feiyue WANG State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of AutomationChinese Academy of SciencesBeijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China State Key Laboratory for Management and Control of Complex System Institute of AutomationChinese Academy of SciencesBeijing 100190China

In this paper,a variety of classical convolutional neural networks are trained on two different datasets using transfer learning *** demonstrated that the training dataset has a significant impact on the training results,in addition to the optimization achieved through the model ***,the lack of open-source agricultural data,combined with the absence of a comprehensive open-source data sharing platform,remains a substantial *** issue is closely related to the difficulty and high cost of obtaining high-quality agricultural data,the low level of education of most employees,underdeveloped distributed training systems and unsecured data *** address these challenges,this paper proposes a novel idea of constructing an agricultural data sharing platform based on a federated learning(FL)framework,aiming to overcome the deficiency of high-quality data in agricultural field training.

关键词： Rice disease and pest identification Convolutional neural networks Distributed training Federated learning(FL) Open-source data sharing platform

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