Pub Date : 2022-10-28DOI: 10.1109/RCAE56054.2022.9995949
Xinran Zhang, Jun Xu, Haoyu Fu, Shenqi Hu
mechanical arms are being used more and more frequently to grab objects in real life like smart-garbage-removal robots. Aiming at the problem that the traditional mechanical arm grasping method lacks intelligence and the eye in hand manipulator is less researched, this paper proposes a mechanical arm grasping system based on computer vision, which uses Yolo object detection to narrow the detection range, reduce noise, use Canny edge detection and image expansion to corrode the center point of the extract body, use Hough to transform the slope of the main direction of the extract body, calculate the position of the object according to the center point and the main direction slope of the object, then use the ROS framework to control the robot arm for grasping. After experimental testing, this method can effectively grasp objects within a certain range, which is more concise than traditional methods, and has good real-time performance and intelligence.
{"title":"Research on Moving Arm Grasping Based on Computer Vision","authors":"Xinran Zhang, Jun Xu, Haoyu Fu, Shenqi Hu","doi":"10.1109/RCAE56054.2022.9995949","DOIUrl":"https://doi.org/10.1109/RCAE56054.2022.9995949","url":null,"abstract":"mechanical arms are being used more and more frequently to grab objects in real life like smart-garbage-removal robots. Aiming at the problem that the traditional mechanical arm grasping method lacks intelligence and the eye in hand manipulator is less researched, this paper proposes a mechanical arm grasping system based on computer vision, which uses Yolo object detection to narrow the detection range, reduce noise, use Canny edge detection and image expansion to corrode the center point of the extract body, use Hough to transform the slope of the main direction of the extract body, calculate the position of the object according to the center point and the main direction slope of the object, then use the ROS framework to control the robot arm for grasping. After experimental testing, this method can effectively grasp objects within a certain range, which is more concise than traditional methods, and has good real-time performance and intelligence.","PeriodicalId":165439,"journal":{"name":"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124264917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper proposes an adaptive recursive terminal sliding mode control (ARTSMC) using an improved fully tuned RBF neural network for Micro-Electro-Mechanical System (MEMS) gyroscopes. First, a mathematical model of a MEMS Z-axis vibrating gyroscope is introduced. Then, an ARTSMC is constructed with a recursive fast nonsingular terminal sliding surface to guarantee finite-time tracking error convergence. In addition, to release the dependence of the proposed controller on system parameters and to correctly estimate the angular velocity, an improved fully tuned RBF neural network is used to approximate gyroscope parameters. Simulation studies are conducted to verify the effectiveness of the proposed scheme.
{"title":"Improved Fully Adjusted Neural Network based Recursive Terminal Sliding Mode Control for MEMS Gyroscopes","authors":"Luoyu Zhang, Zhiwei Wen, Cheng Lu, Yunxiang Guo, Xinsong Zhang, Laiwu Luo","doi":"10.1109/RCAE56054.2022.9995783","DOIUrl":"https://doi.org/10.1109/RCAE56054.2022.9995783","url":null,"abstract":"This paper proposes an adaptive recursive terminal sliding mode control (ARTSMC) using an improved fully tuned RBF neural network for Micro-Electro-Mechanical System (MEMS) gyroscopes. First, a mathematical model of a MEMS Z-axis vibrating gyroscope is introduced. Then, an ARTSMC is constructed with a recursive fast nonsingular terminal sliding surface to guarantee finite-time tracking error convergence. In addition, to release the dependence of the proposed controller on system parameters and to correctly estimate the angular velocity, an improved fully tuned RBF neural network is used to approximate gyroscope parameters. Simulation studies are conducted to verify the effectiveness of the proposed scheme.","PeriodicalId":165439,"journal":{"name":"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122191318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-28DOI: 10.1109/RCAE56054.2022.9995911
Bingqiu Zhang, Weibin Xu, Jun Yang, Ruifeng Xing, Shunjie Han, Hong Jiang
To improve the observability of noise in distributed optical fiber perimeter security system, a denoising algorithm based on CEEMDAN and wavelet transform is proposed. The CEMMDAN is used to decompose the noise signal, and the noise signal and the intrusion signal are decomposed. The wavelet transform is used to denoise and remove the Gaussian noise component. Finally, the CEEMDAN and wavelet denoising are combined to remove the noise, and the denoising signal in line with the subsequent steps of demodulation is obtained. Experiments show that the proposed algorithm can effectively remove Gaussian noise and effectively reduce the interference noise and inherent electronic noise in the optical fiber perimeter security system.
{"title":"Application of Ceemdan and Wavelet Threshold Denoising in Perimeter Security of Fiber Grating","authors":"Bingqiu Zhang, Weibin Xu, Jun Yang, Ruifeng Xing, Shunjie Han, Hong Jiang","doi":"10.1109/RCAE56054.2022.9995911","DOIUrl":"https://doi.org/10.1109/RCAE56054.2022.9995911","url":null,"abstract":"To improve the observability of noise in distributed optical fiber perimeter security system, a denoising algorithm based on CEEMDAN and wavelet transform is proposed. The CEMMDAN is used to decompose the noise signal, and the noise signal and the intrusion signal are decomposed. The wavelet transform is used to denoise and remove the Gaussian noise component. Finally, the CEEMDAN and wavelet denoising are combined to remove the noise, and the denoising signal in line with the subsequent steps of demodulation is obtained. Experiments show that the proposed algorithm can effectively remove Gaussian noise and effectively reduce the interference noise and inherent electronic noise in the optical fiber perimeter security system.","PeriodicalId":165439,"journal":{"name":"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)","volume":"149 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132539739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-28DOI: 10.1109/RCAE56054.2022.9996028
Jian Wang, Juan Nan, Zhiyan Han
Fire recognition and early prevention are of great significance to reduce the loss caused by fire. In this paper, an ensemble algorithm combining multi-models and proposed chaotic Harris hawks optimization (CHHO) is proposed for fire flame recognition. The combined multi-models include decision tree (DT), K-nearest neighbor (KNN), least squares support vector machine (LSSVM) and extreme learning machine (ELM). Aiming at the problem that improper parameter will seriously affect the classification performance of the combined models, a chaotic Harris hawks optimization (CHHO) is proposed to optimize the parameters of models. Tent mapping, improved exploration mode and improved exploitation mode are introduced into CHHO to improve the performance of Harris hawks optimization (HHO). Finally, the output of each optimized model are obtained, then the final output are obtained by weighted average method. Experiment on a set of flame images shows that the proposed model is effective and has good classification performance.
{"title":"An Ensemble Algorithm Combining Multi-models and Proposed Chaotic Harris Hawks Optimization for Fire Flame Recognition","authors":"Jian Wang, Juan Nan, Zhiyan Han","doi":"10.1109/RCAE56054.2022.9996028","DOIUrl":"https://doi.org/10.1109/RCAE56054.2022.9996028","url":null,"abstract":"Fire recognition and early prevention are of great significance to reduce the loss caused by fire. In this paper, an ensemble algorithm combining multi-models and proposed chaotic Harris hawks optimization (CHHO) is proposed for fire flame recognition. The combined multi-models include decision tree (DT), K-nearest neighbor (KNN), least squares support vector machine (LSSVM) and extreme learning machine (ELM). Aiming at the problem that improper parameter will seriously affect the classification performance of the combined models, a chaotic Harris hawks optimization (CHHO) is proposed to optimize the parameters of models. Tent mapping, improved exploration mode and improved exploitation mode are introduced into CHHO to improve the performance of Harris hawks optimization (HHO). Finally, the output of each optimized model are obtained, then the final output are obtained by weighted average method. Experiment on a set of flame images shows that the proposed model is effective and has good classification performance.","PeriodicalId":165439,"journal":{"name":"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131587723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-28DOI: 10.1109/RCAE56054.2022.9995770
Jing Zhao, Xijia Tao, Xuebo Luan, Lei Hou, Wenchao Ji, Wen Wang
With the rapid development of manufacturing automation, traditional bolt tightening methods are difficult to adapt to the fast and high quality requirements of modern industry for product assembly. Even electric tightening has been put forward higher requirements, especially for those products that require high axis force control after bolt tightening. Therefore, it is particularly important to control the bolt tightening process and results. In this paper, three tightening methods are compared by experiments, and the torque-angle twice tightening method is chosen as the best one, which has the least attenuation and the minimum discrete rate of the axis force after 24 hours. Aiming at the difficult problem of how to control the axis force after tightening, a set of automatic control method using electric tightening machine is put forward. This method can accurately control the tightening position even if the workpiece with variable. At the same time, it can control the tightening process effectively by monitoring the relative relationship between tightening angle and Torque, in order to effectively ensure the modern manufacturing industry on Bolt Tightening axis force requirements.
{"title":"Research on Bolt Tightening Control Method Based on Electric Tightening Machine","authors":"Jing Zhao, Xijia Tao, Xuebo Luan, Lei Hou, Wenchao Ji, Wen Wang","doi":"10.1109/RCAE56054.2022.9995770","DOIUrl":"https://doi.org/10.1109/RCAE56054.2022.9995770","url":null,"abstract":"With the rapid development of manufacturing automation, traditional bolt tightening methods are difficult to adapt to the fast and high quality requirements of modern industry for product assembly. Even electric tightening has been put forward higher requirements, especially for those products that require high axis force control after bolt tightening. Therefore, it is particularly important to control the bolt tightening process and results. In this paper, three tightening methods are compared by experiments, and the torque-angle twice tightening method is chosen as the best one, which has the least attenuation and the minimum discrete rate of the axis force after 24 hours. Aiming at the difficult problem of how to control the axis force after tightening, a set of automatic control method using electric tightening machine is put forward. This method can accurately control the tightening position even if the workpiece with variable. At the same time, it can control the tightening process effectively by monitoring the relative relationship between tightening angle and Torque, in order to effectively ensure the modern manufacturing industry on Bolt Tightening axis force requirements.","PeriodicalId":165439,"journal":{"name":"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127648968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-28DOI: 10.1109/RCAE56054.2022.9995743
Rubisnol Felix Julian Daga, Kevin RicardoVilchez Becerra, Jhon Stalin Figueroa Bados, Edson Jeanpierre Perez Cardenas, Pablo José Hurtado Rengifo
In the present investigation of the design of a processing machine for hybrid compounds based on coconut and maguey fibers, using the non-experimental quantitative method, under the German VDI 2221 and 2225 methodology, using mathematical models of machine elements and mechanical design and selection. of electronic components, where the main objective was the design of the hybrid compound processing machine, which consists of four processes: material transport, crushing process, mixing and compacting process, to obtain boards agglomerated, with the purpose of reusing usable solid waste and transforming it into fibers, in order to avoid the use of wood and to reduce the logging that occurs in the central jungle of Peru, for which it is essential to know the mechanical characteristics of coconut and maguey fiber, coconut fiber has a tensile strength of 220 Mpa and fiber Maguey has a tensile strength of 305 Mpa, likewise the automated control is programmed in PLC S7 1200 and TIA Portal v15 for reading analog inputs and outputs, visualization and control are developed through the HMI that is accessible to data control.
{"title":"Design of A Processing Machine for Hybrid Composites Based on Coconut and Maguey Fibers for the Production of Chipboard in the Junin-Peru Region","authors":"Rubisnol Felix Julian Daga, Kevin RicardoVilchez Becerra, Jhon Stalin Figueroa Bados, Edson Jeanpierre Perez Cardenas, Pablo José Hurtado Rengifo","doi":"10.1109/RCAE56054.2022.9995743","DOIUrl":"https://doi.org/10.1109/RCAE56054.2022.9995743","url":null,"abstract":"In the present investigation of the design of a processing machine for hybrid compounds based on coconut and maguey fibers, using the non-experimental quantitative method, under the German VDI 2221 and 2225 methodology, using mathematical models of machine elements and mechanical design and selection. of electronic components, where the main objective was the design of the hybrid compound processing machine, which consists of four processes: material transport, crushing process, mixing and compacting process, to obtain boards agglomerated, with the purpose of reusing usable solid waste and transforming it into fibers, in order to avoid the use of wood and to reduce the logging that occurs in the central jungle of Peru, for which it is essential to know the mechanical characteristics of coconut and maguey fiber, coconut fiber has a tensile strength of 220 Mpa and fiber Maguey has a tensile strength of 305 Mpa, likewise the automated control is programmed in PLC S7 1200 and TIA Portal v15 for reading analog inputs and outputs, visualization and control are developed through the HMI that is accessible to data control.","PeriodicalId":165439,"journal":{"name":"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124617864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-28DOI: 10.1109/RCAE56054.2022.9995946
Jizhi Mao, Zhijia Yang, Shusheng Zhang
The model design and basic principle of liquid level control system are described. In order to improve the dynamic response of liquid level control, the overshoot and steady-state error accuracy of the system are improved. In this paper, we apply the conventional PID controller to the single-loop system and the cascade system respectively, and introduce the fuzzy control algorithm based on the conventional PID control algorithm to design a cascade parameter self-adjusting fuzzy PID controller, Then use genetic algorithm to optimize fuzzy control rules to generate genetic fuzzy PID controller. The MATLAB/Simulink simulation results show that, compared with the traditional PID control, the genetic fuzzy PID control has better control effect and anti-interference ability, and has good control performance.
{"title":"Simulation of Liquid Level Cascade Control System Based on Genetic Fuzzy PID","authors":"Jizhi Mao, Zhijia Yang, Shusheng Zhang","doi":"10.1109/RCAE56054.2022.9995946","DOIUrl":"https://doi.org/10.1109/RCAE56054.2022.9995946","url":null,"abstract":"The model design and basic principle of liquid level control system are described. In order to improve the dynamic response of liquid level control, the overshoot and steady-state error accuracy of the system are improved. In this paper, we apply the conventional PID controller to the single-loop system and the cascade system respectively, and introduce the fuzzy control algorithm based on the conventional PID control algorithm to design a cascade parameter self-adjusting fuzzy PID controller, Then use genetic algorithm to optimize fuzzy control rules to generate genetic fuzzy PID controller. The MATLAB/Simulink simulation results show that, compared with the traditional PID control, the genetic fuzzy PID control has better control effect and anti-interference ability, and has good control performance.","PeriodicalId":165439,"journal":{"name":"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129443016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-28DOI: 10.1109/RCAE56054.2022.9995872
Chunxia Pan, Ye Zhang, Haolin Li, Niaona Zhang
In view of the problems of slow acquisition speed, few elements, and low accuracy of traditional ground detection methods currently used in our country. At the same time, in view of the long and short-term memory network (LSTM) in deep learning, it has the advantages of automatic feature extraction and integration of classification and recognition. Based on the research foundation of transient electromagnetic method (TEM), this paper proposes a deep recognition method of underground power cables based on self-attention mechanism and LSTM network. First, the induced voltage at different time points is normalized, and the TEM apparent resistivity is quickly obtained through the LSTM-Self-Attention network. Among them, the LSTM-Self-Attention network weights are optimized by self-attention mechanism to improve the accuracy of power cable depth recognition. Finally, the power cable depth identification method proposed in this paper is simulated, and the experimental results verify the effectiveness of the proposed method.
{"title":"Depth Recognition of Underground Power Cables Based on Self-attention Mechanism and LSTM Network","authors":"Chunxia Pan, Ye Zhang, Haolin Li, Niaona Zhang","doi":"10.1109/RCAE56054.2022.9995872","DOIUrl":"https://doi.org/10.1109/RCAE56054.2022.9995872","url":null,"abstract":"In view of the problems of slow acquisition speed, few elements, and low accuracy of traditional ground detection methods currently used in our country. At the same time, in view of the long and short-term memory network (LSTM) in deep learning, it has the advantages of automatic feature extraction and integration of classification and recognition. Based on the research foundation of transient electromagnetic method (TEM), this paper proposes a deep recognition method of underground power cables based on self-attention mechanism and LSTM network. First, the induced voltage at different time points is normalized, and the TEM apparent resistivity is quickly obtained through the LSTM-Self-Attention network. Among them, the LSTM-Self-Attention network weights are optimized by self-attention mechanism to improve the accuracy of power cable depth recognition. Finally, the power cable depth identification method proposed in this paper is simulated, and the experimental results verify the effectiveness of the proposed method.","PeriodicalId":165439,"journal":{"name":"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127088450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-28DOI: 10.1109/RCAE56054.2022.9995900
Xuewen Qiu, Huawei Liang, Jie Wang, Junsen Jing
The vehicle-mounted cameras provide video streaming information for the post-processing phase of the intelligent vehicle, such as control and decision making. According to the characteristics of in-vehicle videos, this paper studies a video stabilization algorithm considering different depths of field. On the motion estimation stage, for the problem of inaccurate estimation inter-frame motion vectors caused by different depths of field of feature points, this paper proposes a method to repair inter-frame motion vectors. The method can correct the feature point position of the current frame and improve the estimation accuracy of the global motion vector. In the motion smoothing phase, a real-time online optimization framework and adaptive weights are used to balance the relationship between motion smoothing and motion following. Experiments prove that the accuracy of motion estimation of the algorithm in this paper is better than other improved algorithm, and the average value of PSNR after video stabilization is increased by more than 3dB compared with the original videos.
{"title":"Research on Multi-depth-of-field Electronic Image Stabilization Algorithm for In-Vehicle Videos","authors":"Xuewen Qiu, Huawei Liang, Jie Wang, Junsen Jing","doi":"10.1109/RCAE56054.2022.9995900","DOIUrl":"https://doi.org/10.1109/RCAE56054.2022.9995900","url":null,"abstract":"The vehicle-mounted cameras provide video streaming information for the post-processing phase of the intelligent vehicle, such as control and decision making. According to the characteristics of in-vehicle videos, this paper studies a video stabilization algorithm considering different depths of field. On the motion estimation stage, for the problem of inaccurate estimation inter-frame motion vectors caused by different depths of field of feature points, this paper proposes a method to repair inter-frame motion vectors. The method can correct the feature point position of the current frame and improve the estimation accuracy of the global motion vector. In the motion smoothing phase, a real-time online optimization framework and adaptive weights are used to balance the relationship between motion smoothing and motion following. Experiments prove that the accuracy of motion estimation of the algorithm in this paper is better than other improved algorithm, and the average value of PSNR after video stabilization is increased by more than 3dB compared with the original videos.","PeriodicalId":165439,"journal":{"name":"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125375756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-28DOI: 10.1109/rcae56054.2022.9996020
Kevin RicardoVilchez Becerra, Jhon Stalin Figueroa Bados, Jesus Miguel Condor, Fabian, Katy Fiorela Vilchez Becerra
Feedback Control and Fault Detection Based on Reduced-Order Observer
基于降阶观测器的反馈控制与故障检测
{"title":"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE 2022)","authors":"Kevin RicardoVilchez Becerra, Jhon Stalin Figueroa Bados, Jesus Miguel Condor, Fabian, Katy Fiorela Vilchez Becerra","doi":"10.1109/rcae56054.2022.9996020","DOIUrl":"https://doi.org/10.1109/rcae56054.2022.9996020","url":null,"abstract":"Feedback Control and Fault Detection Based on Reduced-Order Observer","PeriodicalId":165439,"journal":{"name":"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126458459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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