Pub Date : 2023-08-06DOI: 10.1109/ICMA57826.2023.10216169
Chenqi Li, Jian Guo, Shuxiang Guo, Qiang Fu
A path planning method based on a two-layer coordination system is proposed for the compatibility requirement of path planning global optimum and local coordination in a spherical multi-robot system. In the first layer of the algorithm, the global path quality is improved by proposing a nonlinear sine factor and a sparrow search algorithm with improved levy flight strategy to plan the global collision-free optimal path for each robot. In the second layer, a rolling window method is used to determine the possible collision positions of each robot in the system, and a priority-based conflict resolution strategy is proposed to complete the local coordination of the path near the corresponding position. The experimental results show that the path planning method enables the robots to drive along the global optimal path, but still can carry out flexible and orderly local path coordination, which effectively improves the path planning performance of the system.
{"title":"Study on a Two-layer Path Planning Method of Spherical Multi-robot","authors":"Chenqi Li, Jian Guo, Shuxiang Guo, Qiang Fu","doi":"10.1109/ICMA57826.2023.10216169","DOIUrl":"https://doi.org/10.1109/ICMA57826.2023.10216169","url":null,"abstract":"A path planning method based on a two-layer coordination system is proposed for the compatibility requirement of path planning global optimum and local coordination in a spherical multi-robot system. In the first layer of the algorithm, the global path quality is improved by proposing a nonlinear sine factor and a sparrow search algorithm with improved levy flight strategy to plan the global collision-free optimal path for each robot. In the second layer, a rolling window method is used to determine the possible collision positions of each robot in the system, and a priority-based conflict resolution strategy is proposed to complete the local coordination of the path near the corresponding position. The experimental results show that the path planning method enables the robots to drive along the global optimal path, but still can carry out flexible and orderly local path coordination, which effectively improves the path planning performance of the system.","PeriodicalId":151364,"journal":{"name":"2023 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131140106","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 : 2023-08-06DOI: 10.1109/ICMA57826.2023.10215783
Chunfang Liu, Changfeng Li, Jun Yu Li
In the field of force and position control for robots, impedance control is prevalently employed. However, in complex dynamic environments such as cleaning and grinding, constant impedance control has a large tracking error and may even damage the robot’s end tool. In order to solve these problems, an adaptive variable impedance control method is presented based on a nonlinear tracking differentiator in this paper. Specifically, we design the adaptive rate based on Proportional Integral (PI) control to perform the tracking of force and position in complex dynamic environments. Meanwhile, a nonlinear tracking differentiator is developed to lessen the impulse of contact force generated when the end-effector just contacts with environmental surface. The experiments show that the presented approaches effectively improve the safety and reliability of the contact operations.
{"title":"Adaptive Impedance Control in Dynamic Environment Based on Nonlinear Tracking Differentiator","authors":"Chunfang Liu, Changfeng Li, Jun Yu Li","doi":"10.1109/ICMA57826.2023.10215783","DOIUrl":"https://doi.org/10.1109/ICMA57826.2023.10215783","url":null,"abstract":"In the field of force and position control for robots, impedance control is prevalently employed. However, in complex dynamic environments such as cleaning and grinding, constant impedance control has a large tracking error and may even damage the robot’s end tool. In order to solve these problems, an adaptive variable impedance control method is presented based on a nonlinear tracking differentiator in this paper. Specifically, we design the adaptive rate based on Proportional Integral (PI) control to perform the tracking of force and position in complex dynamic environments. Meanwhile, a nonlinear tracking differentiator is developed to lessen the impulse of contact force generated when the end-effector just contacts with environmental surface. The experiments show that the presented approaches effectively improve the safety and reliability of the contact operations.","PeriodicalId":151364,"journal":{"name":"2023 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130689867","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 : 2023-08-06DOI: 10.1109/ICMA57826.2023.10215547
Shiyu Ding, Jin Li, Kuan Luan
When exploring the use of ultrasound to provide real-time, radiation-free 3D imaging for fracture surgery, A skeleton ultrasound image segmentation network based on the fusion of mixed multiple attention (MMA-SUISNet) was proposed to solve the problems of excessive noise, small skeleton features, and difficult boundary division in the ultrasound image. The model uses the Squeeze Exception (SE) module to complete the encoding function, constructs cross-layer connections, and improves the ability to identify small targets; By adding Convolutional Block Attention Module (CBAM) to the encoder, the model can adaptively adjust the weights of channels and positions to better extract features and reduce the impact of noise; By adding Attention Gates (AG) to the decoder, features are adaptively emphasized and transmitted, allowing the network to focus on skeleton boundary information. For the collected skeleton ultrasound images, this paper shows through segmentation, ablation, and generalization experiments that the proposed model has improved Dice, IoU, and F1-Score indicators by 13.87%, 10.01%, and 13.80% compared to the original U-Net model, respectively.
{"title":"Segmentation of Skeleton Ultrasound Images Based on MMA-SUISNet","authors":"Shiyu Ding, Jin Li, Kuan Luan","doi":"10.1109/ICMA57826.2023.10215547","DOIUrl":"https://doi.org/10.1109/ICMA57826.2023.10215547","url":null,"abstract":"When exploring the use of ultrasound to provide real-time, radiation-free 3D imaging for fracture surgery, A skeleton ultrasound image segmentation network based on the fusion of mixed multiple attention (MMA-SUISNet) was proposed to solve the problems of excessive noise, small skeleton features, and difficult boundary division in the ultrasound image. The model uses the Squeeze Exception (SE) module to complete the encoding function, constructs cross-layer connections, and improves the ability to identify small targets; By adding Convolutional Block Attention Module (CBAM) to the encoder, the model can adaptively adjust the weights of channels and positions to better extract features and reduce the impact of noise; By adding Attention Gates (AG) to the decoder, features are adaptively emphasized and transmitted, allowing the network to focus on skeleton boundary information. For the collected skeleton ultrasound images, this paper shows through segmentation, ablation, and generalization experiments that the proposed model has improved Dice, IoU, and F1-Score indicators by 13.87%, 10.01%, and 13.80% compared to the original U-Net model, respectively.","PeriodicalId":151364,"journal":{"name":"2023 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133025913","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 : 2023-08-06DOI: 10.1109/ICMA57826.2023.10215644
Yuan Yang, Jin Guo, Feng Lyu, Shuxi Guo
Cardiovascular disease is a chronic disease with high incidence, high disability and high mortality, which poses a great threat to the life and health of people all over the world. At present, the incidence and mortality of cardiovascular disease are increasing year by year worldwide, so the prevention and treatment of cardiovascular disease has become a top priority. In recent years, with the development of computer technology in the field of auxiliary diagnosis and treatment, the research on automatic classification of Electrocardiogram (ECG) signals has ushered in new opportunities. In this study, ECG signals are taken as the research object, to analyze the auxiliary diagnosis needs of users such as patients and pathologists. This study mainly uses ECG data from MIT-BIH database, combined with relevant preprocessing knowledge and deep learning classification model, to achieve ECG reading, denoising, segmentation, classification and so on. It can effectively improve the efficiency of diagnosis. It has certain reference value for assisting users to diagnose arrhythmia.
{"title":"A Classification Method for ECG Signals Based on Convolutional Neural Network","authors":"Yuan Yang, Jin Guo, Feng Lyu, Shuxi Guo","doi":"10.1109/ICMA57826.2023.10215644","DOIUrl":"https://doi.org/10.1109/ICMA57826.2023.10215644","url":null,"abstract":"Cardiovascular disease is a chronic disease with high incidence, high disability and high mortality, which poses a great threat to the life and health of people all over the world. At present, the incidence and mortality of cardiovascular disease are increasing year by year worldwide, so the prevention and treatment of cardiovascular disease has become a top priority. In recent years, with the development of computer technology in the field of auxiliary diagnosis and treatment, the research on automatic classification of Electrocardiogram (ECG) signals has ushered in new opportunities. In this study, ECG signals are taken as the research object, to analyze the auxiliary diagnosis needs of users such as patients and pathologists. This study mainly uses ECG data from MIT-BIH database, combined with relevant preprocessing knowledge and deep learning classification model, to achieve ECG reading, denoising, segmentation, classification and so on. It can effectively improve the efficiency of diagnosis. It has certain reference value for assisting users to diagnose arrhythmia.","PeriodicalId":151364,"journal":{"name":"2023 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":"591 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133483447","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 : 2023-08-06DOI: 10.1109/ICMA57826.2023.10215616
Xiaofei Ji, He Xu, Zhuowen Zhao, Jiaqiang Zhou
With the rapid development of modern science and technology, especially with the emergence and widespread application of computer technology, it has become possible to use computers for predicting chaotic phenomena. There are still some problems in predicting chaotic time series, such as weak robustness, low accuracy, and poor generalization ability. Therefore, this article proposes a new chaos time series prediction algorithm based on the multi-dimensional transformer (DTM) algorithm. This algorithm mainly achieves chaos time series prediction through end-to-end data correlation prediction. Experimental results show that the accuracy of this algorithm reaches 93.227%, which is significantly higher than that of SVM, LSTM and ESN algorithms. Moreover, it has stronger robustness and better generalization performance.
{"title":"Chaotic Time Series Prediction of Multi-Dimensional Transformer Based on Bionic Reconfigurable Three-Dimensional Scanning Robot","authors":"Xiaofei Ji, He Xu, Zhuowen Zhao, Jiaqiang Zhou","doi":"10.1109/ICMA57826.2023.10215616","DOIUrl":"https://doi.org/10.1109/ICMA57826.2023.10215616","url":null,"abstract":"With the rapid development of modern science and technology, especially with the emergence and widespread application of computer technology, it has become possible to use computers for predicting chaotic phenomena. There are still some problems in predicting chaotic time series, such as weak robustness, low accuracy, and poor generalization ability. Therefore, this article proposes a new chaos time series prediction algorithm based on the multi-dimensional transformer (DTM) algorithm. This algorithm mainly achieves chaos time series prediction through end-to-end data correlation prediction. Experimental results show that the accuracy of this algorithm reaches 93.227%, which is significantly higher than that of SVM, LSTM and ESN algorithms. Moreover, it has stronger robustness and better generalization performance.","PeriodicalId":151364,"journal":{"name":"2023 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133683073","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 : 2023-08-06DOI: 10.1109/ICMA57826.2023.10216137
Xiaoke Guo, Niansong Zhang, Aiming Wang
In order to establish reasonable and applicable standards for process consumption, this paper proposes a GABCC method for solving the common weight vector and comprehensive efficiency vector. Based on the use of GA-BCC to obtain comprehensive efficiency vector, the method uses efficiency threshold to remove inefficient data and forms standard data. Finally, taking the average value is used to calculate the process consumption standard. The results of the experiment show that the comprehensive efficiency is basically the same as the original efficiency, thus proving the feasibility of the method. Meanwhile, the utilization of a common weighting method prevented the establishment of biased weight preferences, thus utilizing the shared weights method to calculate efficiency is more impartial.
{"title":"Research on GA-BCC Algorithm for Process Cost Consumption Standards Establishing","authors":"Xiaoke Guo, Niansong Zhang, Aiming Wang","doi":"10.1109/ICMA57826.2023.10216137","DOIUrl":"https://doi.org/10.1109/ICMA57826.2023.10216137","url":null,"abstract":"In order to establish reasonable and applicable standards for process consumption, this paper proposes a GABCC method for solving the common weight vector and comprehensive efficiency vector. Based on the use of GA-BCC to obtain comprehensive efficiency vector, the method uses efficiency threshold to remove inefficient data and forms standard data. Finally, taking the average value is used to calculate the process consumption standard. The results of the experiment show that the comprehensive efficiency is basically the same as the original efficiency, thus proving the feasibility of the method. Meanwhile, the utilization of a common weighting method prevented the establishment of biased weight preferences, thus utilizing the shared weights method to calculate efficiency is more impartial.","PeriodicalId":151364,"journal":{"name":"2023 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131418209","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 : 2023-08-06DOI: 10.1109/ICMA57826.2023.10215705
Hao Li, Niansong Zhang, Aiming Wang
Scratch defects on the surface of many tiny components are difficult to be solved by machine vision technology, and the algorithm needs to be constantly evolved. Therefore, based on image processing technology, a method of extracting scratch defects on the surface of components based on Gaussian filtering in frequency domain filtering is proposed. Firstly, in the early image preprocessing, the Gaussian filter is used to filter the image, and then the Hough transform algorithm is used to represent the contour, and the image morphology is analyzed. Finally, the Gabor filter is used to extract the scratch defects.
{"title":"An Surface Defect Extraction of Component Scratches Algorithm Based on Gaussian Filter","authors":"Hao Li, Niansong Zhang, Aiming Wang","doi":"10.1109/ICMA57826.2023.10215705","DOIUrl":"https://doi.org/10.1109/ICMA57826.2023.10215705","url":null,"abstract":"Scratch defects on the surface of many tiny components are difficult to be solved by machine vision technology, and the algorithm needs to be constantly evolved. Therefore, based on image processing technology, a method of extracting scratch defects on the surface of components based on Gaussian filtering in frequency domain filtering is proposed. Firstly, in the early image preprocessing, the Gaussian filter is used to filter the image, and then the Hough transform algorithm is used to represent the contour, and the image morphology is analyzed. Finally, the Gabor filter is used to extract the scratch defects.","PeriodicalId":151364,"journal":{"name":"2023 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133722213","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 : 2023-08-06DOI: 10.1109/ICMA57826.2023.10215568
Yu Lu, Y. Yue, Guoqiang Li, Zhenpo Wang
This paper presents an adaptive fault tolerant control approach for autonomous vehicles (AV) under actuator or sensor faults to improve driving safety. A learning-based stochastic model predictive control (SMPC) strategy incorporating vehicle real dynamics characteristics is developed to realize accurate autonomous trajectory tracking. First, a vehicle dynamics model integrating typical actuator and sensor faults is established. Then, a model online learning strategy is designed to update the vehicle dynamics in real-time. Gaussian process (GP) is applied to identify and learn the real dynamic changes caused by faults which is hard to describe by standard models. Finally, the online learning vehicle dynamics is integrated into SMPC to optimize motion control for accurate trajectory tracking. Extensive simulations are studied to evaluate the model online learning performance and the safe tracking performance with adaptive fault tolerant control under various fault conditions.
{"title":"Adaptive Fault Tolerant Control for Safe Autonomous Driving using Learning-based Model Predictive Control","authors":"Yu Lu, Y. Yue, Guoqiang Li, Zhenpo Wang","doi":"10.1109/ICMA57826.2023.10215568","DOIUrl":"https://doi.org/10.1109/ICMA57826.2023.10215568","url":null,"abstract":"This paper presents an adaptive fault tolerant control approach for autonomous vehicles (AV) under actuator or sensor faults to improve driving safety. A learning-based stochastic model predictive control (SMPC) strategy incorporating vehicle real dynamics characteristics is developed to realize accurate autonomous trajectory tracking. First, a vehicle dynamics model integrating typical actuator and sensor faults is established. Then, a model online learning strategy is designed to update the vehicle dynamics in real-time. Gaussian process (GP) is applied to identify and learn the real dynamic changes caused by faults which is hard to describe by standard models. Finally, the online learning vehicle dynamics is integrated into SMPC to optimize motion control for accurate trajectory tracking. Extensive simulations are studied to evaluate the model online learning performance and the safe tracking performance with adaptive fault tolerant control under various fault conditions.","PeriodicalId":151364,"journal":{"name":"2023 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115396658","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 : 2023-08-06DOI: 10.1109/ICMA57826.2023.10215537
Guangjun Xie, Niansong Zhang, Aiming Wang, Kang Wang
Tool cutting as the core process of machine tool processing, cutting parameters, tool and parts material, processing procedures and other conditions will directly affect the cutting state of the tool, In order to solve the problem that the tool wear is too fast and the service life is too short, the cutting state of the tool can not be known in time during high-speed milling, a cutting state recognition technology based on spindle vibration signal and machining parameters of the machine tool was proposed. By analyzing the vibration signals and machining parameters of machine tool spindle under different conditions, combining with the methods of feature extraction and feature dimension reduction, the state recognition of cutting tool is completed. Finally, through experiments, the spindle vibration signal of vertical machining center machine tool was collected for feature vector extraction, and the comparison between the original feature vector and the actual value was obtained by dimensionality reduction to predict the cutting state of the tool. The results show that the proposed method has higher accuracy and recognition, and can recognize the cutting state of the cutting tool when cutting parts.
{"title":"Tool cutting state recognition technology based on machining data characteristics","authors":"Guangjun Xie, Niansong Zhang, Aiming Wang, Kang Wang","doi":"10.1109/ICMA57826.2023.10215537","DOIUrl":"https://doi.org/10.1109/ICMA57826.2023.10215537","url":null,"abstract":"Tool cutting as the core process of machine tool processing, cutting parameters, tool and parts material, processing procedures and other conditions will directly affect the cutting state of the tool, In order to solve the problem that the tool wear is too fast and the service life is too short, the cutting state of the tool can not be known in time during high-speed milling, a cutting state recognition technology based on spindle vibration signal and machining parameters of the machine tool was proposed. By analyzing the vibration signals and machining parameters of machine tool spindle under different conditions, combining with the methods of feature extraction and feature dimension reduction, the state recognition of cutting tool is completed. Finally, through experiments, the spindle vibration signal of vertical machining center machine tool was collected for feature vector extraction, and the comparison between the original feature vector and the actual value was obtained by dimensionality reduction to predict the cutting state of the tool. The results show that the proposed method has higher accuracy and recognition, and can recognize the cutting state of the cutting tool when cutting parts.","PeriodicalId":151364,"journal":{"name":"2023 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":"474 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115947602","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 : 2023-08-06DOI: 10.1109/ICMA57826.2023.10215974
Huixuan Fu, Wenjing Yao, Chao Peng, Yuchao Wang
In order to work out the matter of long calculation time and poor real-time performance of trajectory tracking controller designed by Model Predictive Control (MPC), a model predictive control trajectory tracking based on variable step size in control horizon is proposed by means of move blocking. Firstly, changing of control horizon step size through move blocking. Then, integrating it into the solution process of quadratic programming and reconstructing objective function form. So as to cut the amount of variables to be solved in the solution process and reduce the solution calculation time. Finally, the comparison experiments of MPC with move blocking for trajectory tracking control of Unmanned Surface Vehicle (USV) and MPC without move blocking for trajectory tracking control of USV are designed. The results show that compared with MPC without move blocking, the average calculation time is reduced by 15.79%.
{"title":"Model Predictive Control with Block Matrix for Unmanned Surface Vehicles Trajectory Tracking","authors":"Huixuan Fu, Wenjing Yao, Chao Peng, Yuchao Wang","doi":"10.1109/ICMA57826.2023.10215974","DOIUrl":"https://doi.org/10.1109/ICMA57826.2023.10215974","url":null,"abstract":"In order to work out the matter of long calculation time and poor real-time performance of trajectory tracking controller designed by Model Predictive Control (MPC), a model predictive control trajectory tracking based on variable step size in control horizon is proposed by means of move blocking. Firstly, changing of control horizon step size through move blocking. Then, integrating it into the solution process of quadratic programming and reconstructing objective function form. So as to cut the amount of variables to be solved in the solution process and reduce the solution calculation time. Finally, the comparison experiments of MPC with move blocking for trajectory tracking control of Unmanned Surface Vehicle (USV) and MPC without move blocking for trajectory tracking control of USV are designed. The results show that compared with MPC without move blocking, the average calculation time is reduced by 15.79%.","PeriodicalId":151364,"journal":{"name":"2023 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":"47 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124293323","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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