Pub Date : 2021-05-14DOI: 10.1109/DDCLS52934.2021.9455364
Yutai Wei, Zhijun Yang, Youdun Bai
High-precision rotary stages are applied in many fields, but the bearing friction has a negative impact on tracking performance. Rigid-flexible coupling rotary stage, a novel structure for rotary stage, can convert the friction disturbance into elastic force with flexure hinges. In order to avoid the effect of elastic force, active disturbance rejection control (ADRC) is adopted in this paper for its excellent disturbance rejection ability and independence of accurate modelling. In view of the resonance and high-frequency noise of the system, notch and lead filters are combined with ADRC, which is called modified ADRC. The experimental results show that the modified ADRC has a good effect on eliminating elastic force disturbance, and also has the ability to suppress resonance and high-frequency noise.
{"title":"Modified ADRC Design for Rigid-flexible Coupling Rotary Stage with Filters","authors":"Yutai Wei, Zhijun Yang, Youdun Bai","doi":"10.1109/DDCLS52934.2021.9455364","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455364","url":null,"abstract":"High-precision rotary stages are applied in many fields, but the bearing friction has a negative impact on tracking performance. Rigid-flexible coupling rotary stage, a novel structure for rotary stage, can convert the friction disturbance into elastic force with flexure hinges. In order to avoid the effect of elastic force, active disturbance rejection control (ADRC) is adopted in this paper for its excellent disturbance rejection ability and independence of accurate modelling. In view of the resonance and high-frequency noise of the system, notch and lead filters are combined with ADRC, which is called modified ADRC. The experimental results show that the modified ADRC has a good effect on eliminating elastic force disturbance, and also has the ability to suppress resonance and high-frequency noise.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125411762","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 : 2021-05-14DOI: 10.1109/DDCLS52934.2021.9455500
Xuan Yang, Xiaoe Ruan, Yan Geng
This paper focuses on the reliability of the iterative learning control strategy for a kind of repeatable discrete-time models subject to transmission attenuation and offset fault produced in actuator. The attenuation is a random multiplier with respect to both time and iteration index and the fault is an additive stochastic disturbance. So, the real control input is modelled by multiplying a stochastic variable with the original control signal and adding a random bounded-disturbance function. By resorting to the time-weighted norm technique, the tracking performance is analyzed in the statistical sense and the sufficiency of convergence is established. To illustrate the effectiveness and reliability of the proposed results, numerical experiments are carried out.
{"title":"Iterative Learning Reliable Control for A Kind of Discrete-time Nonlinear Systems with Stochastic Transmission Attenuation and Offset Fault in Actuator","authors":"Xuan Yang, Xiaoe Ruan, Yan Geng","doi":"10.1109/DDCLS52934.2021.9455500","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455500","url":null,"abstract":"This paper focuses on the reliability of the iterative learning control strategy for a kind of repeatable discrete-time models subject to transmission attenuation and offset fault produced in actuator. The attenuation is a random multiplier with respect to both time and iteration index and the fault is an additive stochastic disturbance. So, the real control input is modelled by multiplying a stochastic variable with the original control signal and adding a random bounded-disturbance function. By resorting to the time-weighted norm technique, the tracking performance is analyzed in the statistical sense and the sufficiency of convergence is established. To illustrate the effectiveness and reliability of the proposed results, numerical experiments are carried out.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122270990","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}
Fault diagnosis of satellite attitude control system is an important task to ensure the safe and reliable operation of on-orbit satellites. At present, most fault diagnosis methods are to diagnose independent identically distributed(i.i.d) task objects. However, even if the same device works under different working conditions, the distribution domain of the collected data almost always changes. At the same time, the training of fault diagnosis model under full working conditions can increase the model complexity and training time, and there may unknown working conditions. In view of the above situation, this paper proposed a domain adaptive adversarial deep neural network based fault diagnosis method. By combining the feature extractor, label classifier and domain classifier with the convolutional neural network and gradient inversion layer (GRL), the effective label classification can be achieved while the resolution of different domains can be reduced. We achieved feature extraction of the classification learning task in the source domain and transfer of the classification task between the two domains. The effectiveness of the diagnosis model is verified in the ground simulation data of a certain satellite under different conditions.
{"title":"Fault Diagnosis of Satellites under Variable Conditions based on Domain Adaptive Adversarial Deep Neural Network","authors":"Yuxing Gu, Zehui Mao, Xing-gang Yan, Hanyu Liang, Wenjing Liu, Chengrui Liu","doi":"10.1109/DDCLS52934.2021.9455711","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455711","url":null,"abstract":"Fault diagnosis of satellite attitude control system is an important task to ensure the safe and reliable operation of on-orbit satellites. At present, most fault diagnosis methods are to diagnose independent identically distributed(i.i.d) task objects. However, even if the same device works under different working conditions, the distribution domain of the collected data almost always changes. At the same time, the training of fault diagnosis model under full working conditions can increase the model complexity and training time, and there may unknown working conditions. In view of the above situation, this paper proposed a domain adaptive adversarial deep neural network based fault diagnosis method. By combining the feature extractor, label classifier and domain classifier with the convolutional neural network and gradient inversion layer (GRL), the effective label classification can be achieved while the resolution of different domains can be reduced. We achieved feature extraction of the classification learning task in the source domain and transfer of the classification task between the two domains. The effectiveness of the diagnosis model is verified in the ground simulation data of a certain satellite under different conditions.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127903395","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 study proposes a practical hybrid automatic transmission model for commercial vehicles based on the first-principle modelling approach. The developed plant model consists of three base elements, i.e. hydraulic circuit, multi-plate wet clutches and planetary gear sets. In today's intelligent transmission control system development framework, plant model plays an important role. It can be used to valid the control algorithm as well as control system in an early stage of the development process, thus shortening development process and improving software quality.
{"title":"A Practical Hybrid Automatic Transmission Model for Commercial Vehicles","authors":"Haiyang Hao, Haoxing Chen, Darong Huang, Zhenyuan Zhang","doi":"10.1109/DDCLS52934.2021.9455674","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455674","url":null,"abstract":"This study proposes a practical hybrid automatic transmission model for commercial vehicles based on the first-principle modelling approach. The developed plant model consists of three base elements, i.e. hydraulic circuit, multi-plate wet clutches and planetary gear sets. In today's intelligent transmission control system development framework, plant model plays an important role. It can be used to valid the control algorithm as well as control system in an early stage of the development process, thus shortening development process and improving software quality.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128189513","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 : 2021-05-14DOI: 10.1109/DDCLS52934.2021.9455709
Licheng Zhang, J. Xun, Wei Zhang, Xi Li, Yanlong Zhang
In the urban rail transit system, the traction energy consumption accounts for 40%-60% of the total energy consumption. There is a large amount of traction energy consumption data in time series format recorded by energy meters. Accurate analysis of traction energy consumption based on time series is in urgent demand for energy saving. In order to analyze the law of traction energy consumption, this paper proposes a pattern recognition method for traction energy consumption based on SAX (Symbolic Aggregate approXimation). The original time series of traction energy consumption is transformed by SAX and the sub-patterns are obtained. The traction energy consumption patterns are recognized by using K-means algorithm. To show the effectiveness and efficiency, we apply the proposed method to a data set from Beijing Subway, and find 3 representative patterns. We find that the recognized patterns of traction energy consumption appears coherence with the major services prescribed in the rolling stock scheduling plan. By calculating the similarity and comparing with these representative patterns, the days that differ from the typical patterns are judged as anomalies.
{"title":"Pattern Recognition of Traction Energy Consumption for Urban Rail Transit by Using Symbolic Aggregate Approximation","authors":"Licheng Zhang, J. Xun, Wei Zhang, Xi Li, Yanlong Zhang","doi":"10.1109/DDCLS52934.2021.9455709","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455709","url":null,"abstract":"In the urban rail transit system, the traction energy consumption accounts for 40%-60% of the total energy consumption. There is a large amount of traction energy consumption data in time series format recorded by energy meters. Accurate analysis of traction energy consumption based on time series is in urgent demand for energy saving. In order to analyze the law of traction energy consumption, this paper proposes a pattern recognition method for traction energy consumption based on SAX (Symbolic Aggregate approXimation). The original time series of traction energy consumption is transformed by SAX and the sub-patterns are obtained. The traction energy consumption patterns are recognized by using K-means algorithm. To show the effectiveness and efficiency, we apply the proposed method to a data set from Beijing Subway, and find 3 representative patterns. We find that the recognized patterns of traction energy consumption appears coherence with the major services prescribed in the rolling stock scheduling plan. By calculating the similarity and comparing with these representative patterns, the days that differ from the typical patterns are judged as anomalies.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128485527","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 : 2021-05-14DOI: 10.1109/DDCLS52934.2021.9455678
Yanjun Liang, Yuanxin Li
This article addresses the asymptotic tracking issues of a one-link manipulator system. To realize the exponentially asymptotic tracking performance, the exponential term has been introduced into the Lyapunov function and the bounds estimation method and the smooth modification function are used to guarantee the zero-error tracking. In addition, the neural networks (NNs) is devised to cope with the uncertain disturbance and unknown nonlinearlities. At last, a simulation example has been shown to verify the raised scheme.
{"title":"Adaptive exponentially asymptotic tracking control for a one-link manipulator","authors":"Yanjun Liang, Yuanxin Li","doi":"10.1109/DDCLS52934.2021.9455678","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455678","url":null,"abstract":"This article addresses the asymptotic tracking issues of a one-link manipulator system. To realize the exponentially asymptotic tracking performance, the exponential term has been introduced into the Lyapunov function and the bounds estimation method and the smooth modification function are used to guarantee the zero-error tracking. In addition, the neural networks (NNs) is devised to cope with the uncertain disturbance and unknown nonlinearlities. At last, a simulation example has been shown to verify the raised scheme.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130281542","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 : 2021-05-14DOI: 10.1109/DDCLS52934.2021.9455504
Zeyu Li, Peng Chang, Kai Wang, Pu Wang
In the industrial batch process monitoring domain, the conventional multivariate monitoring methods may not always function well in monitoring faults that have both Non-Linear and Non-Gaussian properties. To enhance the monitoring capability, the adversarial auto-encoder (AAE) was introduced to increase the sensitivity to Non-Gaussian anomalies by projecting non-Gaussian information into a given Gaussian distribution feature space. At the same time, low-dimensional feature space can avoid the problem of “Concentration of measure” and improve the ability to distinguish minor small abnormalities. Therefore, A novel statistic index was constructed in the feature space based on the k-nearest neighbor rule (KNN) to improve the ability of minor fault monitoring. The proposed model is compared with the traditional multivariate statistical process monitoring methods in numerical examples and penicillin fermentation platform, which proves that it has better monitoring ability for minor magnitude and non-Gaussian faults.
{"title":"The Batch Process Fault Monitoring Using Adversarial Auto-encoder and K-Nearest Neighbor Rule","authors":"Zeyu Li, Peng Chang, Kai Wang, Pu Wang","doi":"10.1109/DDCLS52934.2021.9455504","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455504","url":null,"abstract":"In the industrial batch process monitoring domain, the conventional multivariate monitoring methods may not always function well in monitoring faults that have both Non-Linear and Non-Gaussian properties. To enhance the monitoring capability, the adversarial auto-encoder (AAE) was introduced to increase the sensitivity to Non-Gaussian anomalies by projecting non-Gaussian information into a given Gaussian distribution feature space. At the same time, low-dimensional feature space can avoid the problem of “Concentration of measure” and improve the ability to distinguish minor small abnormalities. Therefore, A novel statistic index was constructed in the feature space based on the k-nearest neighbor rule (KNN) to improve the ability of minor fault monitoring. The proposed model is compared with the traditional multivariate statistical process monitoring methods in numerical examples and penicillin fermentation platform, which proves that it has better monitoring ability for minor magnitude and non-Gaussian faults.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129239389","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 : 2021-05-14DOI: 10.1109/DDCLS52934.2021.9455367
Bin Lu, Zunshui Cheng
We study the dynamic behavior of a new type of hyper-chaotic system and use the method of time delay control to achieve the purpose of the control system. This paper analyzes the stability and existence of the equilibrium point and discusses the cross-sectional conditions under which the balance point has Hopf bifurcation. Then we give the time delay value of the periodic solution generated by the system equilibrium point. Numerical examples are given to verify the theoretical results.
{"title":"Time Delayed Feedback Control for a Class of Hyper-chaotic Systems","authors":"Bin Lu, Zunshui Cheng","doi":"10.1109/DDCLS52934.2021.9455367","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455367","url":null,"abstract":"We study the dynamic behavior of a new type of hyper-chaotic system and use the method of time delay control to achieve the purpose of the control system. This paper analyzes the stability and existence of the equilibrium point and discusses the cross-sectional conditions under which the balance point has Hopf bifurcation. Then we give the time delay value of the periodic solution generated by the system equilibrium point. Numerical examples are given to verify the theoretical results.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"215 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130807251","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 : 2021-05-14DOI: 10.1109/DDCLS52934.2021.9455584
Yuan Xu, Kaiduo Cong, Yang Zhang, Qunxiong Zhu, Yanlin He
In the modern industrial process, the likelihood of the occurrence of multiple faults is higher than that of a single fault Comparing with single faults, the multi-faults problem has higher coupling and complexity, thus it is quite important to establish an effective multi-faults recognition model to ensure process safety. In this paper, a multi-fault recognition model based on reconstructed principal component analysis (RPCA) algorithm and support vector machine ensemble (SVME) classifier is proposed to satisfy the needs. First, obtain the principal component information from the original high-dimensional data space. Second, to solve the loss of local feature information, reconstruct the local structural error of the feature space through the inverse mapping matrix, and then align the error to obtain the reconstructed coordinates. Third, based on the One vs. One (OvO) ensemble strategy, an SVME classifier is constructed for multiple faults recognition. Finally, to verify the performance of the proposed RPCA-SVME model, the simulation experiments are made on a Circle dataset and the Tennessee Eastman process (TEP). The comparison results show that the proposed method can guarantee higher diagnostic accuracy and macro F1 score.
在现代工业过程中，与单一故障相比，多故障问题具有更高的耦合性和复杂性，因此建立有效的多故障识别模型对于保证过程安全具有重要意义。本文提出了一种基于重构主成分分析(RPCA)算法和支持向量机集成(SVME)分类器的多故障识别模型。首先，从原始高维数据空间中获取主成分信息;其次，为了解决局部特征信息的丢失问题，通过逆映射矩阵重构特征空间的局部结构误差，并对误差进行对齐，得到重构的坐标。第三，基于One vs. One (OvO)集成策略，构建了支持向量机多故障识别分类器。最后，为了验证RPCA-SVME模型的性能，在Circle数据集和田纳西伊士曼过程(Tennessee Eastman process, TEP)上进行了仿真实验。对比结果表明，该方法能够保证较高的诊断准确率和宏观F1分数。
{"title":"Research and Application of a Novel RPCA-SVME based Multiple Faults Recognition","authors":"Yuan Xu, Kaiduo Cong, Yang Zhang, Qunxiong Zhu, Yanlin He","doi":"10.1109/DDCLS52934.2021.9455584","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455584","url":null,"abstract":"In the modern industrial process, the likelihood of the occurrence of multiple faults is higher than that of a single fault Comparing with single faults, the multi-faults problem has higher coupling and complexity, thus it is quite important to establish an effective multi-faults recognition model to ensure process safety. In this paper, a multi-fault recognition model based on reconstructed principal component analysis (RPCA) algorithm and support vector machine ensemble (SVME) classifier is proposed to satisfy the needs. First, obtain the principal component information from the original high-dimensional data space. Second, to solve the loss of local feature information, reconstruct the local structural error of the feature space through the inverse mapping matrix, and then align the error to obtain the reconstructed coordinates. Third, based on the One vs. One (OvO) ensemble strategy, an SVME classifier is constructed for multiple faults recognition. Finally, to verify the performance of the proposed RPCA-SVME model, the simulation experiments are made on a Circle dataset and the Tennessee Eastman process (TEP). The comparison results show that the proposed method can guarantee higher diagnostic accuracy and macro F1 score.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130959258","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 : 2021-05-14DOI: 10.1109/DDCLS52934.2021.9455502
Jin Ma, Yu Wang, Rui Wang, Shuo Wang
This paper aims to investigate a smooth teleoperation method for the underwater vehicle-manipulator system. First, a coordinated mapping control method for the vehicle is presented. The haptic force is considered to help assist the operation. Then, two mapping modes are used to teleoperate the manipulator: when the end-effector needs to move in a large area, two virtual points and a spring-damping system are implemented to filter the operator's hand jitter and limit the manipulator's speed; when the end-effector needs to move in a small area, a position increment control method with a small proportional coefficient is used to improve the precision. Finally, the simulation demonstrates the effectiveness of the proposed teleoperation method.
{"title":"Remote Operation with Haptic Force and Virtual Proxy for an Underwater Vehicle-Manipulator System","authors":"Jin Ma, Yu Wang, Rui Wang, Shuo Wang","doi":"10.1109/DDCLS52934.2021.9455502","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455502","url":null,"abstract":"This paper aims to investigate a smooth teleoperation method for the underwater vehicle-manipulator system. First, a coordinated mapping control method for the vehicle is presented. The haptic force is considered to help assist the operation. Then, two mapping modes are used to teleoperate the manipulator: when the end-effector needs to move in a large area, two virtual points and a spring-damping system are implemented to filter the operator's hand jitter and limit the manipulator's speed; when the end-effector needs to move in a small area, a position increment control method with a small proportional coefficient is used to improve the precision. Finally, the simulation demonstrates the effectiveness of the proposed teleoperation method.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"43 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127990478","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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