Series elastic actuator (SEA) are widely used in exoskeleton robots. For its vibration suppression problem, this paper proposes a method of "planning and controlling" in the SEA system. First, according to the kinematics constraint equation of the connecting rod, the position of motor is planned based on the second-order low-pass filter, which used particle swarm algorithm to optimize the filter parameters in the process. Second, a position tracking controller is used to make the motor accurately track the desired trajectory according to dynamical model of the motor. The optimal filter is finally found to plan the motor trajectory by iterative simulation based on particle swarm algorithm. The experimental results show that this "planning and controlling" method can effectively suppress residual vibration while ensuring that the connecting rod reaches the desired position accurately.
{"title":"A Vibration Suppression Method of Series Elastic Actuator Based on Particle Swarm Algorithm","authors":"Yuanzhu Zhan, Zifeng Jiang, Wenduo Jia, Jinggang Wang, Yu Dai, Jianxun Zhang","doi":"10.1109/CAC57257.2022.10054733","DOIUrl":"https://doi.org/10.1109/CAC57257.2022.10054733","url":null,"abstract":"Series elastic actuator (SEA) are widely used in exoskeleton robots. For its vibration suppression problem, this paper proposes a method of \"planning and controlling\" in the SEA system. First, according to the kinematics constraint equation of the connecting rod, the position of motor is planned based on the second-order low-pass filter, which used particle swarm algorithm to optimize the filter parameters in the process. Second, a position tracking controller is used to make the motor accurately track the desired trajectory according to dynamical model of the motor. The optimal filter is finally found to plan the motor trajectory by iterative simulation based on particle swarm algorithm. The experimental results show that this \"planning and controlling\" method can effectively suppress residual vibration while ensuring that the connecting rod reaches the desired position accurately.","PeriodicalId":287137,"journal":{"name":"2022 China Automation Congress (CAC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121961393","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 : 2022-11-25DOI: 10.1109/CAC57257.2022.10054985
Ling-Yun Zhu, Chen-Yu Wang, Yue-Ying Zhao
Appling deep learning network models to train and detect defects on periodic texture background images requires a large number of standard datasets. However, in the field of texture fabric defect detection, there is lack of public standard datasets, and it is pretty time-consuming and laborious to prepare a high-quality training dataset. In this study, we propose a comprehensive method combining with the characteristics of periodic texture images, which uses multiple metrics and multiple mathematical models of an image to vote and score the splitted sub-images of the image, so as to detect the locations of defects on the periodic texture image. Central to our method is subimage segmentation, Zero-Slope-RANSac(ZS-RANSac) method, Multi-metric-Multi-model Image Voting strategy, which utilizes the local consistency of image metrics existing in periodic texture by cutting images into sub-images of the same size. To obtain the basic scoring matrix of each sub-image under each model, we take the difference of the standard value of the non-defect background calculated by ZS-RANSac and all measurements of sub-image, and then combine the matrix and multiple numeration model. According to the order of the scores, a certain proportion of polymer image points are considered as outer points, which are the defect sub-images. This method completely relies on statistical strategy to make use of the periodic texture characteristics of the image, and can detect the non-lattice texture image without training data. It has a wide application prospect for the textile industry, which requires real time and lacks high-quality training datasets.
{"title":"Defect Detection Algorithm of Periodic Texture by Multi-metric-Multi-module Image Voting Method","authors":"Ling-Yun Zhu, Chen-Yu Wang, Yue-Ying Zhao","doi":"10.1109/CAC57257.2022.10054985","DOIUrl":"https://doi.org/10.1109/CAC57257.2022.10054985","url":null,"abstract":"Appling deep learning network models to train and detect defects on periodic texture background images requires a large number of standard datasets. However, in the field of texture fabric defect detection, there is lack of public standard datasets, and it is pretty time-consuming and laborious to prepare a high-quality training dataset. In this study, we propose a comprehensive method combining with the characteristics of periodic texture images, which uses multiple metrics and multiple mathematical models of an image to vote and score the splitted sub-images of the image, so as to detect the locations of defects on the periodic texture image. Central to our method is subimage segmentation, Zero-Slope-RANSac(ZS-RANSac) method, Multi-metric-Multi-model Image Voting strategy, which utilizes the local consistency of image metrics existing in periodic texture by cutting images into sub-images of the same size. To obtain the basic scoring matrix of each sub-image under each model, we take the difference of the standard value of the non-defect background calculated by ZS-RANSac and all measurements of sub-image, and then combine the matrix and multiple numeration model. According to the order of the scores, a certain proportion of polymer image points are considered as outer points, which are the defect sub-images. This method completely relies on statistical strategy to make use of the periodic texture characteristics of the image, and can detect the non-lattice texture image without training data. It has a wide application prospect for the textile industry, which requires real time and lacks high-quality training datasets.","PeriodicalId":287137,"journal":{"name":"2022 China Automation Congress (CAC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127929139","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 : 2022-11-25DOI: 10.1109/CAC57257.2022.10054781
Zhengda Cheng, Fan Wu, Y. Geng
In this paper, a space manipulator with a magnetic capture device as the end-effector is designed, and it is used to capture a self-spin target. First of all, a kinematic equation and a dynamic equation are given, then a target approach strategy for the manipulator combined with fifth-order polynomial interpolation methods for trajectory planning is designed, and then an improved PD algorithm is adopted to achieve the trajectory tracking control. For the magnetic capture device, its suction model is established through experimental fitting, and a capture strategy is set according to its characteristics. Finally, a numerical simulation is designed to prove that the control strategy designed in this paper is reasonable and effective.
{"title":"Capture Strategy and Control of Non-cooperative Target Using Space Manipulator with Magnetic Capture Device","authors":"Zhengda Cheng, Fan Wu, Y. Geng","doi":"10.1109/CAC57257.2022.10054781","DOIUrl":"https://doi.org/10.1109/CAC57257.2022.10054781","url":null,"abstract":"In this paper, a space manipulator with a magnetic capture device as the end-effector is designed, and it is used to capture a self-spin target. First of all, a kinematic equation and a dynamic equation are given, then a target approach strategy for the manipulator combined with fifth-order polynomial interpolation methods for trajectory planning is designed, and then an improved PD algorithm is adopted to achieve the trajectory tracking control. For the magnetic capture device, its suction model is established through experimental fitting, and a capture strategy is set according to its characteristics. Finally, a numerical simulation is designed to prove that the control strategy designed in this paper is reasonable and effective.","PeriodicalId":287137,"journal":{"name":"2022 China Automation Congress (CAC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131387958","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 : 2022-11-25DOI: 10.1109/CAC57257.2022.10055845
Linguo Chai, Jinghui Zhang, W. Shangguan, Xiao Xiao, Xu Li, Min Nie
Aiming at the problem that the semantics of CBTC on-board equipment fault record text is not precise and the word redundancy, which makes it difficult to trace the cause of the fault, this paper proposes a CBTC on-board signal fault diagnosis method based on LightGBM classification. Firstly, the relationship between appearance and fault is analyzed by combining the knowledge graph search formed by manually combing the text; then, TF-IDF is used to extract the original text features, and Doc2vec is used to realize text vectorization. The actual fault text records are divided into training sets and testing sets. The LightGBM classifier is trained to obtain the classification and diagnosis model, and 1133 testing sets are tested and verified. The results show that the accuracy of classification diagnosis of the method proposed in this paper is 90.2%, which is 17.8% higher than that of SVM classification diagnosis and conforms to the manual graph fault analysis link.
{"title":"CBTC on-board signal fault diagnosis method based on LightGBM classification","authors":"Linguo Chai, Jinghui Zhang, W. Shangguan, Xiao Xiao, Xu Li, Min Nie","doi":"10.1109/CAC57257.2022.10055845","DOIUrl":"https://doi.org/10.1109/CAC57257.2022.10055845","url":null,"abstract":"Aiming at the problem that the semantics of CBTC on-board equipment fault record text is not precise and the word redundancy, which makes it difficult to trace the cause of the fault, this paper proposes a CBTC on-board signal fault diagnosis method based on LightGBM classification. Firstly, the relationship between appearance and fault is analyzed by combining the knowledge graph search formed by manually combing the text; then, TF-IDF is used to extract the original text features, and Doc2vec is used to realize text vectorization. The actual fault text records are divided into training sets and testing sets. The LightGBM classifier is trained to obtain the classification and diagnosis model, and 1133 testing sets are tested and verified. The results show that the accuracy of classification diagnosis of the method proposed in this paper is 90.2%, which is 17.8% higher than that of SVM classification diagnosis and conforms to the manual graph fault analysis link.","PeriodicalId":287137,"journal":{"name":"2022 China Automation Congress (CAC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131950666","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 : 2022-11-25DOI: 10.1109/CAC57257.2022.10055014
Yifan Hao, Kunli Guo, Fengyi Liu, Jiajun Lv, Bo Li, Peihao Yang
The droop control scheme is adopted in the energy storage converter to improve the voltage and frequency support capability of the energy storage converter to the regional power grid. The droop control strategy of active current frequency and reactive current voltage is specifically adopted. Aiming at the problem that the traditional current droop control can not suppress the grid side fluctuation, which leads to the poor transient characteristics of the output voltage of the energy storage converter, a method to characterize the droop coefficient according to the change rate of the effective value of the output voltage of the energy storage converter is proposed, and the droop coefficient is adaptively adjusted according to the voltage regulation to provide virtual inertial support for the system. Simulation is used to verify the proposed scheme. The results show that the new current droop control strategy can effectively improve the transient voltage performance of the energy storage converter.
{"title":"Research on improved current droop control scheme of energy storage converter","authors":"Yifan Hao, Kunli Guo, Fengyi Liu, Jiajun Lv, Bo Li, Peihao Yang","doi":"10.1109/CAC57257.2022.10055014","DOIUrl":"https://doi.org/10.1109/CAC57257.2022.10055014","url":null,"abstract":"The droop control scheme is adopted in the energy storage converter to improve the voltage and frequency support capability of the energy storage converter to the regional power grid. The droop control strategy of active current frequency and reactive current voltage is specifically adopted. Aiming at the problem that the traditional current droop control can not suppress the grid side fluctuation, which leads to the poor transient characteristics of the output voltage of the energy storage converter, a method to characterize the droop coefficient according to the change rate of the effective value of the output voltage of the energy storage converter is proposed, and the droop coefficient is adaptively adjusted according to the voltage regulation to provide virtual inertial support for the system. Simulation is used to verify the proposed scheme. The results show that the new current droop control strategy can effectively improve the transient voltage performance of the energy storage converter.","PeriodicalId":287137,"journal":{"name":"2022 China Automation Congress (CAC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130213966","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 : 2022-11-25DOI: 10.1109/CAC57257.2022.10056076
Zhiguo He, Jing Huang, Ruping Lin, Xiaosheng Huang, Binyi Chen, Yang Lin
The factory test and maintenance of the generator set are essential for ensuring that the generator runs smoothly. A generator test is frequently required to determine the generator set's rated capacity. A range of test loads must be varied to fulfil the test criteria during the test. Traditional load switching systems are inefficient, simple to misuse, and use load resources imbalanced. Because of these issues, this study provides a solution for load matching and balancing control of generator unit tests based on the knapsack algorithm. Combining the knapsack problem model with multiple combinatorial optimization algorithms allows for simulated comparison and analysis. In the actual test, the optimal control technique obtained is compared to the traditional approach. The results reveal that the knapsack algorithm, which is based on a combination of the knapsack problem model and the discrete binary particle swarm algorithm, can more accurately match and apply the test load, successfully overcoming the old technique's issues causes. Simultaneously, test efficiency is enhanced, and the whole test load's service life is extended.
{"title":"Generator Set Load Balancing Control Using the Knapsack Algorithm","authors":"Zhiguo He, Jing Huang, Ruping Lin, Xiaosheng Huang, Binyi Chen, Yang Lin","doi":"10.1109/CAC57257.2022.10056076","DOIUrl":"https://doi.org/10.1109/CAC57257.2022.10056076","url":null,"abstract":"The factory test and maintenance of the generator set are essential for ensuring that the generator runs smoothly. A generator test is frequently required to determine the generator set's rated capacity. A range of test loads must be varied to fulfil the test criteria during the test. Traditional load switching systems are inefficient, simple to misuse, and use load resources imbalanced. Because of these issues, this study provides a solution for load matching and balancing control of generator unit tests based on the knapsack algorithm. Combining the knapsack problem model with multiple combinatorial optimization algorithms allows for simulated comparison and analysis. In the actual test, the optimal control technique obtained is compared to the traditional approach. The results reveal that the knapsack algorithm, which is based on a combination of the knapsack problem model and the discrete binary particle swarm algorithm, can more accurately match and apply the test load, successfully overcoming the old technique's issues causes. Simultaneously, test efficiency is enhanced, and the whole test load's service life is extended.","PeriodicalId":287137,"journal":{"name":"2022 China Automation Congress (CAC)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130457488","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}
Graph convolution network (GCN) has recently played a positive role in improving the accuracy of skeleton-based action recognition. Many GCN methods have reached a high accuracy. However, the lightweight of network model has recently become a major concern. Pointing at the problem, this paper introduces a lightweight network, a Differential Learning and Parallel Convolutional Network (DL-PCN), which is based on Semantics-Guided Neural Networks (SGN). The network is mainly composed of Differential Learning Module (DLM) and Parallel Convolutional Network Module (PCN). DLM is characterized by the feedforward connection, which improves the experiment accuracy. PCN can learn the multi-dimensional information of original skeleton data by the parallel connection of GCN and convolutional neural network (CNN). Considering the test accuracy of action recognition and network parameters, our network achieves the comparable performance on the NTU RGB+D 60 dataset and the NTU RGB+D 120 dataset.
{"title":"Differential Learning and Parallel Convolutional Network for Skeleton-Based Action Recognition","authors":"Qinyang Zeng, Qin Fang, Chengjju Liu, Haozhe Zhu, Qi Chen","doi":"10.1109/CAC57257.2022.10056034","DOIUrl":"https://doi.org/10.1109/CAC57257.2022.10056034","url":null,"abstract":"Graph convolution network (GCN) has recently played a positive role in improving the accuracy of skeleton-based action recognition. Many GCN methods have reached a high accuracy. However, the lightweight of network model has recently become a major concern. Pointing at the problem, this paper introduces a lightweight network, a Differential Learning and Parallel Convolutional Network (DL-PCN), which is based on Semantics-Guided Neural Networks (SGN). The network is mainly composed of Differential Learning Module (DLM) and Parallel Convolutional Network Module (PCN). DLM is characterized by the feedforward connection, which improves the experiment accuracy. PCN can learn the multi-dimensional information of original skeleton data by the parallel connection of GCN and convolutional neural network (CNN). Considering the test accuracy of action recognition and network parameters, our network achieves the comparable performance on the NTU RGB+D 60 dataset and the NTU RGB+D 120 dataset.","PeriodicalId":287137,"journal":{"name":"2022 China Automation Congress (CAC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134009344","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 : 2022-11-25DOI: 10.1109/CAC57257.2022.10055988
Peng Dan, Tao Xi, Dan Wang
In order to solve the problem of the real-time reconstruction of the reentry trajectory with lift-to-drag controlling law during the spacecraft’s reentry flight, an adaptive UKF filtering algorithm was proposed by using external measurements and considering the actual engineering situations. The filter’s state model and observation model were given, and some adaptive processing methods were used, including the maneuver detection and model switching method, and the acceleration compensation method, which were used to deal with the real-time tracking of the maneuvering process of the return flight. The simulation results show that the proposed calculation method is feasible, and the proposed adaptive processing algorithm applying the acceleration compensation can do the robust estimation processing of the reentry trajectory. The research results have certain reference value for the real-time estimation of maneuvering reentry spacecraft.
{"title":"A Real-time Adaptive Filtering Algorithm for Reentry Maneuvering","authors":"Peng Dan, Tao Xi, Dan Wang","doi":"10.1109/CAC57257.2022.10055988","DOIUrl":"https://doi.org/10.1109/CAC57257.2022.10055988","url":null,"abstract":"In order to solve the problem of the real-time reconstruction of the reentry trajectory with lift-to-drag controlling law during the spacecraft’s reentry flight, an adaptive UKF filtering algorithm was proposed by using external measurements and considering the actual engineering situations. The filter’s state model and observation model were given, and some adaptive processing methods were used, including the maneuver detection and model switching method, and the acceleration compensation method, which were used to deal with the real-time tracking of the maneuvering process of the return flight. The simulation results show that the proposed calculation method is feasible, and the proposed adaptive processing algorithm applying the acceleration compensation can do the robust estimation processing of the reentry trajectory. The research results have certain reference value for the real-time estimation of maneuvering reentry spacecraft.","PeriodicalId":287137,"journal":{"name":"2022 China Automation Congress (CAC)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133991930","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 : 2022-11-25DOI: 10.1109/CAC57257.2022.10055446
Yifei Zhang, Hui Yang
Terrain matching navigation cannot be implemented effectively for the cruise missile in the flat terrain area, which is very disadvantage for the selection of terrain matching area. In this paper, a new terrain navigation technology for the cruise missile based on laser echo waveform matching is studied. By extracting the characteristics of the laser echo waveform from the ground target and matching with the waveform data in the database, the attribute and location of the ground target are determined. The flight route of the missile can be further corrected according to the position of the target in the map. This technology can expand the selection range of terrain matching area, lower the requirement on the height fluctuation of the terrain and reduce the difficulty of planning terrain matching area for the cruise missile, and has a good military application value for improving the performance of cruise missile.
{"title":"Study on Terrain Navigation Technology for Cruise Missile Based on Laser Echo Waveform Matching","authors":"Yifei Zhang, Hui Yang","doi":"10.1109/CAC57257.2022.10055446","DOIUrl":"https://doi.org/10.1109/CAC57257.2022.10055446","url":null,"abstract":"Terrain matching navigation cannot be implemented effectively for the cruise missile in the flat terrain area, which is very disadvantage for the selection of terrain matching area. In this paper, a new terrain navigation technology for the cruise missile based on laser echo waveform matching is studied. By extracting the characteristics of the laser echo waveform from the ground target and matching with the waveform data in the database, the attribute and location of the ground target are determined. The flight route of the missile can be further corrected according to the position of the target in the map. This technology can expand the selection range of terrain matching area, lower the requirement on the height fluctuation of the terrain and reduce the difficulty of planning terrain matching area for the cruise missile, and has a good military application value for improving the performance of cruise missile.","PeriodicalId":287137,"journal":{"name":"2022 China Automation Congress (CAC)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134310390","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 : 2022-11-25DOI: 10.1109/CAC57257.2022.10055788
Li Meng, Qiang Zhang, Shuaishuai Yan
To solve the problem of mill current fluctuations caused by sudden input changes in the cement combined grinding system, this paper built a mathematical model of the ball mill load and designed a sliding mode control for ball mill load based on prescribed performance. The prescribed performance formula is introduced into the controller to guarantee the error of mill current can quickly astrict according to the preset curve. Next, the sliding mode surface of mill current error is defined and controller is solved. Through simulation, and by comparing with model-free adaptive sliding control strategy, the designed control strategy can stabilize mill current, reduce adjustment time, and the effectiveness and robustness are verified.
{"title":"Sliding mode control for ball mill load based on prescribed performance","authors":"Li Meng, Qiang Zhang, Shuaishuai Yan","doi":"10.1109/CAC57257.2022.10055788","DOIUrl":"https://doi.org/10.1109/CAC57257.2022.10055788","url":null,"abstract":"To solve the problem of mill current fluctuations caused by sudden input changes in the cement combined grinding system, this paper built a mathematical model of the ball mill load and designed a sliding mode control for ball mill load based on prescribed performance. The prescribed performance formula is introduced into the controller to guarantee the error of mill current can quickly astrict according to the preset curve. Next, the sliding mode surface of mill current error is defined and controller is solved. Through simulation, and by comparing with model-free adaptive sliding control strategy, the designed control strategy can stabilize mill current, reduce adjustment time, and the effectiveness and robustness are verified.","PeriodicalId":287137,"journal":{"name":"2022 China Automation Congress (CAC)","volume":"1168 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134348876","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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