Pub Date : 2023-09-01DOI: 10.1177/00202940231187922
Jianfan Wu, Zhengyu Xie, Yong Qin, L. Jia, Ling Guan
The normal operation of a integrated hub station is of great significance for the safe operation of the entire city’s transportation network. Accurately monitoring the passenger flow operation status of the station is the fundamental basis for achieving scientific management and control of passenger flow. In response to the urgent need for accurate and real-time detection of passenger flow in station passageways, a Yolov7-based improved Deep-Sort algorithm is proposed to detect and track bi-directional passenger flow in the passageways of integrated hub stations. Based on the Yolov7 detection algorithm, the SimAM attention mechanism was introduced to improve the accuracy of detecting passenger flow in the passageways. On the basis of the Deep-Sort tracking algorithm, the Kalman Filter (KF) method was optimized to make the tracking box of the target more accurate. Meanwhile, the Fast-ReID method was used to improve the long-term tracking of targets, thereby improving the value of IDF1. This algorithm can help to achieve real-time and accurate detection and tracking of bi-directional passenger flow in station passageways. In the event of an abnormal situation, the station staff can react rapidly to improve the station’s operational safety.
{"title":"Bi-directional passenger flow tracking and statistics analysis in station passageways based on an improved Deep-Sort algorithm","authors":"Jianfan Wu, Zhengyu Xie, Yong Qin, L. Jia, Ling Guan","doi":"10.1177/00202940231187922","DOIUrl":"https://doi.org/10.1177/00202940231187922","url":null,"abstract":"The normal operation of a integrated hub station is of great significance for the safe operation of the entire city’s transportation network. Accurately monitoring the passenger flow operation status of the station is the fundamental basis for achieving scientific management and control of passenger flow. In response to the urgent need for accurate and real-time detection of passenger flow in station passageways, a Yolov7-based improved Deep-Sort algorithm is proposed to detect and track bi-directional passenger flow in the passageways of integrated hub stations. Based on the Yolov7 detection algorithm, the SimAM attention mechanism was introduced to improve the accuracy of detecting passenger flow in the passageways. On the basis of the Deep-Sort tracking algorithm, the Kalman Filter (KF) method was optimized to make the tracking box of the target more accurate. Meanwhile, the Fast-ReID method was used to improve the long-term tracking of targets, thereby improving the value of IDF1. This algorithm can help to achieve real-time and accurate detection and tracking of bi-directional passenger flow in station passageways. In the event of an abnormal situation, the station staff can react rapidly to improve the station’s operational safety.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"21 1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76957202","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 : 2023-09-01DOI: 10.1177/00202940231196193
Marriam Liaqat, Turki Alsuwian, Dr. Arslan Ahmed Amin, Muhammad Adnan, Adil Zulfiqar
Multi-microgrids offer various benefits including the decreased overloading of a single microgrid, more options during faulty conditions, and more utilization of renewable energy resources. However, the implementation of a multi-microgrid brings the challenges such as power system complexity, interconnection issues, bidirectional power flow management, and power flow balancing. In the presence of these challenges, the power flow stability of the multi-microgrids is a challenging problem. In this context, this study evaluates a transient stability analysis model in multi-microgrids using solar photovoltaics, wind power, and a unified power flow controller (UPFC). UPFC offers a more robust power flow control strategy compared with other flexible alternating current transmission systems (FACTS) devices. First, a multi-microgrid structure consisting of the two microgrids was designed in DIgSILENT PowerFactory software. Second, the load flow calculation was performed in the absence and presence of UPFC, short circuit fault, and grid connection. Third, the electromagnetic transients (EMT) simulation was performed for all these situations. The results exhibited that the UPFC would offer significant power flow stability in the multi-microgrids. It was observed that the UPFC resulted in more transient stability in the microgrid where it was located. However, it improved the power flow quality at all the locations in the multi-microgrids. In addition, UPFC offered significant transient stability during the fault occurrence. The results offer various insights into power flow management in multi-microgrids.
{"title":"Transient stability enhancement in renewable energy integrated multi-microgrids: A comprehensive and critical analysis","authors":"Marriam Liaqat, Turki Alsuwian, Dr. Arslan Ahmed Amin, Muhammad Adnan, Adil Zulfiqar","doi":"10.1177/00202940231196193","DOIUrl":"https://doi.org/10.1177/00202940231196193","url":null,"abstract":"Multi-microgrids offer various benefits including the decreased overloading of a single microgrid, more options during faulty conditions, and more utilization of renewable energy resources. However, the implementation of a multi-microgrid brings the challenges such as power system complexity, interconnection issues, bidirectional power flow management, and power flow balancing. In the presence of these challenges, the power flow stability of the multi-microgrids is a challenging problem. In this context, this study evaluates a transient stability analysis model in multi-microgrids using solar photovoltaics, wind power, and a unified power flow controller (UPFC). UPFC offers a more robust power flow control strategy compared with other flexible alternating current transmission systems (FACTS) devices. First, a multi-microgrid structure consisting of the two microgrids was designed in DIgSILENT PowerFactory software. Second, the load flow calculation was performed in the absence and presence of UPFC, short circuit fault, and grid connection. Third, the electromagnetic transients (EMT) simulation was performed for all these situations. The results exhibited that the UPFC would offer significant power flow stability in the multi-microgrids. It was observed that the UPFC resulted in more transient stability in the microgrid where it was located. However, it improved the power flow quality at all the locations in the multi-microgrids. In addition, UPFC offered significant transient stability during the fault occurrence. The results offer various insights into power flow management in multi-microgrids.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"173 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79546530","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 : 2023-08-31DOI: 10.1177/00202940231195129
Duo Yang, Hanwen Fu, Junjun Li, Siyu Wang
The proton exchange membrane fuel cell gas control has been one key point in fuel cell management systems. The complexity and coupling of the air management system make it difficult to achieve precise air intake adjustment. In this paper, an accurate joint control method for the air flow and pressure regulation is proposed. The nonlinear mathematical model of the air management system is developed to describe the output characteristic and state change. Based on this, the feedback linearization method is proposed to obtain the direct correspondence between control variables and controlled variables. In addition, to solve the problem that the controlled variables cannot be measured directly, an extended state observer is applied to estimate the stack cathode pressure. The sliding mode predictive control method is proposed to control the oxygen excess ratio and cathode pressure simultaneously. The relative order of the system is used to design the sliding mode surface, and the corresponding predictive model is proposed. The results obtained by simulation experiments show that pressure and mass flow have little effect on each other through decoupling. The proposed algorithm has been verified to have high precision, fast response, and robustness through comparative experiments.
{"title":"A multivariable sliding mode predictive control method for the air management system of automotive fuel cells","authors":"Duo Yang, Hanwen Fu, Junjun Li, Siyu Wang","doi":"10.1177/00202940231195129","DOIUrl":"https://doi.org/10.1177/00202940231195129","url":null,"abstract":"The proton exchange membrane fuel cell gas control has been one key point in fuel cell management systems. The complexity and coupling of the air management system make it difficult to achieve precise air intake adjustment. In this paper, an accurate joint control method for the air flow and pressure regulation is proposed. The nonlinear mathematical model of the air management system is developed to describe the output characteristic and state change. Based on this, the feedback linearization method is proposed to obtain the direct correspondence between control variables and controlled variables. In addition, to solve the problem that the controlled variables cannot be measured directly, an extended state observer is applied to estimate the stack cathode pressure. The sliding mode predictive control method is proposed to control the oxygen excess ratio and cathode pressure simultaneously. The relative order of the system is used to design the sliding mode surface, and the corresponding predictive model is proposed. The results obtained by simulation experiments show that pressure and mass flow have little effect on each other through decoupling. The proposed algorithm has been verified to have high precision, fast response, and robustness through comparative experiments.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"91 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78339412","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 : 2023-08-30DOI: 10.1177/00202940231194108
Duo Li, Xu Wang, Juanjuan Wang, Zhenxiong Zhou
The use of maximum power point tracking (MPPT) technology has significantly increased the conversion efficiency of PV modules. However, the presence of partial shading in PV arrays can lead to multi-peaked output curves, which traditional MPPT methods struggle to track due to falling into local maximum power points. The paper proposes a MPPT control algorithm based on the combination of differential flat control (DFBC) and adaptive particle swarm optimization (APSO) algorithm. The PSO output value is used as the feed-forward feedback input of differential flat, and a second-order controller is used to track the reference flat trajectory, achieving global MPPT through differential flat control. The algorithm can overcome the system oscillation caused by the randomness of the PSO algorithm with the initialized particle position and the existence of control lag misjudgment. Simulation and experimental results show that the algorithm not only solves the problem that the traditional MPPT algorithm cannot find the global maximum power point, but also solves the problems that the traditional particle swarm algorithm has large randomness, slow convergence speed, and easy to produce large oscillations. The algorithm has greatly improved the tracking accuracy, tracking speed and response speed, realizing fast and accurate response to external changes, reducing energy loss, and improving the dynamic tracking performance of the system.
{"title":"Differential flat & PSO based photovoltaic maximum power point tracking control under partial shading condition","authors":"Duo Li, Xu Wang, Juanjuan Wang, Zhenxiong Zhou","doi":"10.1177/00202940231194108","DOIUrl":"https://doi.org/10.1177/00202940231194108","url":null,"abstract":"The use of maximum power point tracking (MPPT) technology has significantly increased the conversion efficiency of PV modules. However, the presence of partial shading in PV arrays can lead to multi-peaked output curves, which traditional MPPT methods struggle to track due to falling into local maximum power points. The paper proposes a MPPT control algorithm based on the combination of differential flat control (DFBC) and adaptive particle swarm optimization (APSO) algorithm. The PSO output value is used as the feed-forward feedback input of differential flat, and a second-order controller is used to track the reference flat trajectory, achieving global MPPT through differential flat control. The algorithm can overcome the system oscillation caused by the randomness of the PSO algorithm with the initialized particle position and the existence of control lag misjudgment. Simulation and experimental results show that the algorithm not only solves the problem that the traditional MPPT algorithm cannot find the global maximum power point, but also solves the problems that the traditional particle swarm algorithm has large randomness, slow convergence speed, and easy to produce large oscillations. The algorithm has greatly improved the tracking accuracy, tracking speed and response speed, realizing fast and accurate response to external changes, reducing energy loss, and improving the dynamic tracking performance of the system.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"61 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91446120","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 : 2023-08-30DOI: 10.1177/00202940231194116
Jianjun Zhang, Pengyang Han, Qunpo Liu, Shasha Li, Bin Li
The underwater tactile force measurement was prone to cross-sensitivity, causing the difficulty in distinguishing tactile force signal with the underwater complex environment of water pressure influence. For this problem, an underwater tactile force sensor whose sensing core was based on Microelectromechanical Systems (MEMS) was designed with differential pressure typed structure. The hollow hemispherical flexible contacts located at the upper and lower end, and the hollow cylindrical shell in the middle part composed the structure of the capsule-shaped sensor. The upper flexible contact could sense the compound signal composed of water pressure and tactile force, at the same time, the lower flexible contact could measure the water pressure information. The deformation signal of the upper and lower flexible contacts could be transformed to the force sensor core’s upper and lower surfaces with silicon oil filled in the inner hollow part of the sensor. The tactile force signal could be obtained with water pressure eliminated through vector superposition method under the influence of static pressure of water. The structure and manufacture technology were introduced, and the Backpropagation (BP) neural network data regression algorithm was designed for the cross sensitivity. The experiments are conducted to demonstrate the effectiveness of the differential pressure structure in eliminating the influence of water static pressure. The results indicated that the BP neural network data regression algorithm successfully produced real tactile force signals, which is highly beneficial for the intelligent operation of underwater dexterous hand. Additionally, the sensor has an accuracy of 5%.
{"title":"The design of underwater tactile force sensor with differential pressure structure and backpropagation neural network calibration","authors":"Jianjun Zhang, Pengyang Han, Qunpo Liu, Shasha Li, Bin Li","doi":"10.1177/00202940231194116","DOIUrl":"https://doi.org/10.1177/00202940231194116","url":null,"abstract":"The underwater tactile force measurement was prone to cross-sensitivity, causing the difficulty in distinguishing tactile force signal with the underwater complex environment of water pressure influence. For this problem, an underwater tactile force sensor whose sensing core was based on Microelectromechanical Systems (MEMS) was designed with differential pressure typed structure. The hollow hemispherical flexible contacts located at the upper and lower end, and the hollow cylindrical shell in the middle part composed the structure of the capsule-shaped sensor. The upper flexible contact could sense the compound signal composed of water pressure and tactile force, at the same time, the lower flexible contact could measure the water pressure information. The deformation signal of the upper and lower flexible contacts could be transformed to the force sensor core’s upper and lower surfaces with silicon oil filled in the inner hollow part of the sensor. The tactile force signal could be obtained with water pressure eliminated through vector superposition method under the influence of static pressure of water. The structure and manufacture technology were introduced, and the Backpropagation (BP) neural network data regression algorithm was designed for the cross sensitivity. The experiments are conducted to demonstrate the effectiveness of the differential pressure structure in eliminating the influence of water static pressure. The results indicated that the BP neural network data regression algorithm successfully produced real tactile force signals, which is highly beneficial for the intelligent operation of underwater dexterous hand. Additionally, the sensor has an accuracy of 5%.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81373350","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 : 2023-08-26DOI: 10.1177/00202940231194115
Zhijie Duan, C. Sun, Jipeng Li, Yin Tan
According to the unstable and nonlinear performances of the servo valve-controlled hydraulic motor, classical control methods based on linear theory are gradually unable to meet the high-performance requirements of the system. Using the servo valve-controlled hydraulic motor based on the third-order active disturbance rejection control (ADRC) to improve the dynamic performance of the system is feasible. The mathematical model and the simulation model of the third-order ADRC for the servo valve-controlled hydraulic motor system are established respectively. For the phase lag caused by the third-order ADRC controller, the control performance of the ADRC controller is significantly improved using the advance forecast. The simulation experiment results show that the designed ADRC controller has good tracking performance and stronger robustness of the system than the traditional PID controller.
{"title":"Research on servo valve-controlled hydraulic motor system based on active disturbance rejection control","authors":"Zhijie Duan, C. Sun, Jipeng Li, Yin Tan","doi":"10.1177/00202940231194115","DOIUrl":"https://doi.org/10.1177/00202940231194115","url":null,"abstract":"According to the unstable and nonlinear performances of the servo valve-controlled hydraulic motor, classical control methods based on linear theory are gradually unable to meet the high-performance requirements of the system. Using the servo valve-controlled hydraulic motor based on the third-order active disturbance rejection control (ADRC) to improve the dynamic performance of the system is feasible. The mathematical model and the simulation model of the third-order ADRC for the servo valve-controlled hydraulic motor system are established respectively. For the phase lag caused by the third-order ADRC controller, the control performance of the ADRC controller is significantly improved using the advance forecast. The simulation experiment results show that the designed ADRC controller has good tracking performance and stronger robustness of the system than the traditional PID controller.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78700919","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 : 2023-08-23DOI: 10.1177/00202940231193022
W. Zhao, Dandan Zhang, Dan Li, Yao Zhang, Qiang Ling
For iterative closest point (ICP) algorithm, the initial position and the number of iterations are needed in registration. At the same time, the ICP algorithm is easy to fall into local convergence and convergence speed is slow. By constructing K-D tree to search neighborhood points and artificially set threshold, plane fitting is carried out, the on-time point cloud to be deployed is separated from the complex background, and statistical analysis is used to calculate the distance between the point cloud and the neighborhood point to quickly remove the invalid point cloud. The surface equation is set to calculate the tangent plane of point cloud normal vector and each normal vector, and the local coordinate system is constructed. The angle between adjacent vectors and the local coordinate system is calculated to determine the feature point set of edge contour. According to the covariance matrix of the feature points set, the principal feature component is obtained, the principal axis direction of the two sets of point clouds is found, and the rotation matrix and the displacement vector are obtained. Finally, GICP precise registration of point cloud is carried out according to initial pose parameters and rigid body transformation matrix obtained by maximum likelihood estimation method. The results show that the optimized algorithm can effectively avoid local convergence. Compared with the traditional ICP algorithm, when the algorithm achieves the same registration accuracy in the public dataset experiment, the registration speed is on average 44.82% faster and the overlap rate is on average 15.26% higher. In the real dataset experiment, the registration speed is on average 59.04% faster, the registration accuracy is on average 30.24% higher and the overlap rate is on average 10.61% higher. This shows that the optimization algorithm is superior to the traditional ICP algorithm in registration accuracy and convergence speed.
{"title":"Optimized GICP registration algorithm based on principal component analysis for point cloud edge extraction","authors":"W. Zhao, Dandan Zhang, Dan Li, Yao Zhang, Qiang Ling","doi":"10.1177/00202940231193022","DOIUrl":"https://doi.org/10.1177/00202940231193022","url":null,"abstract":"For iterative closest point (ICP) algorithm, the initial position and the number of iterations are needed in registration. At the same time, the ICP algorithm is easy to fall into local convergence and convergence speed is slow. By constructing K-D tree to search neighborhood points and artificially set threshold, plane fitting is carried out, the on-time point cloud to be deployed is separated from the complex background, and statistical analysis is used to calculate the distance between the point cloud and the neighborhood point to quickly remove the invalid point cloud. The surface equation is set to calculate the tangent plane of point cloud normal vector and each normal vector, and the local coordinate system is constructed. The angle between adjacent vectors and the local coordinate system is calculated to determine the feature point set of edge contour. According to the covariance matrix of the feature points set, the principal feature component is obtained, the principal axis direction of the two sets of point clouds is found, and the rotation matrix and the displacement vector are obtained. Finally, GICP precise registration of point cloud is carried out according to initial pose parameters and rigid body transformation matrix obtained by maximum likelihood estimation method. The results show that the optimized algorithm can effectively avoid local convergence. Compared with the traditional ICP algorithm, when the algorithm achieves the same registration accuracy in the public dataset experiment, the registration speed is on average 44.82% faster and the overlap rate is on average 15.26% higher. In the real dataset experiment, the registration speed is on average 59.04% faster, the registration accuracy is on average 30.24% higher and the overlap rate is on average 10.61% higher. This shows that the optimization algorithm is superior to the traditional ICP algorithm in registration accuracy and convergence speed.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"21 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87266196","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 : 2023-08-18DOI: 10.1177/00202940231192986
Zhuan Zheng, JinCheng Wei
In response to the influence of motor interference, damping, friction, and other uncertain factors on the operation of electric power steering systems under extreme working conditions, this study proposes a control strategy for electric power steering systems based on an active disturbance rejection algorithm. In ADRC, the fastest tracking differentiator is used to arrange the transition process for the target signal, and the extended state observer compensates for the total disturbance in the system. Phase compensation has been performed on the monitoring torque by using the torque differentiation method. The Simulink/Carsim simulation results show that ADRC has significantly improved anti-disturbance performance compared to PID and fuzzy PID. When using ADRC, the tracking accuracy of the assisted current is enhanced by 45.8%–75.8%, and the current adjustment time is reduced by 35.6%–61.7%. After phase compensation, the monitoring torque overshoot is reduced by 83.3%. Therefore, the proposed control strategy improves EPS’s robustness and steering feel.
{"title":"Research on active disturbance rejection control strategy of electric power steering system under extreme working conditions","authors":"Zhuan Zheng, JinCheng Wei","doi":"10.1177/00202940231192986","DOIUrl":"https://doi.org/10.1177/00202940231192986","url":null,"abstract":"In response to the influence of motor interference, damping, friction, and other uncertain factors on the operation of electric power steering systems under extreme working conditions, this study proposes a control strategy for electric power steering systems based on an active disturbance rejection algorithm. In ADRC, the fastest tracking differentiator is used to arrange the transition process for the target signal, and the extended state observer compensates for the total disturbance in the system. Phase compensation has been performed on the monitoring torque by using the torque differentiation method. The Simulink/Carsim simulation results show that ADRC has significantly improved anti-disturbance performance compared to PID and fuzzy PID. When using ADRC, the tracking accuracy of the assisted current is enhanced by 45.8%–75.8%, and the current adjustment time is reduced by 35.6%–61.7%. After phase compensation, the monitoring torque overshoot is reduced by 83.3%. Therefore, the proposed control strategy improves EPS’s robustness and steering feel.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75233649","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 : 2023-08-16DOI: 10.1177/00202940221105857
Hanwen Zhang, Qiong Liu, Yao Mao
In this paper, we formulate high-type intelligent control as a multi-objective problem and apply evolutionary algorithms to search for optimal solutions. Specifically, we consider the metrics of the system in both the frequency domain and the time domain. Integrated time and absolute error is used as a performance metric in the time domain, while bandwidth is used as a measure in the frequency domain. Simultaneously, the amplitude margin and phase margin are used as constraints to ensure the stability of the high-type control system. Then, we adopt evolutionary algorithms to solve the formulated multi-objective problem. Unlike most of the existing approaches, we formulate intelligent high type control as a multi-objective optimization problem based on our knowledge about the control system. Furthermore, evolutionary algorithms are adopted to search for optimal solutions to real-world controlling systems. Extensive experiments are conducted to evaluate the effectiveness of our proposed approach. Compared to the Z-N method and the extending symmetrical optimum criterion, our proposed method achieves an improvement in bandwidth of more than 126.6%, while reducing the overshoot by more than 56.8% and the settling time by more than 48.4% for all controlled objects used in the experiments. At the same time, the tracking errors of the ramp and parabolic signals are significantly reduced, which means this method effectively improves the system performance.
{"title":"Intelligent high-type control based on evolutionary multi-objective optimization","authors":"Hanwen Zhang, Qiong Liu, Yao Mao","doi":"10.1177/00202940221105857","DOIUrl":"https://doi.org/10.1177/00202940221105857","url":null,"abstract":"In this paper, we formulate high-type intelligent control as a multi-objective problem and apply evolutionary algorithms to search for optimal solutions. Specifically, we consider the metrics of the system in both the frequency domain and the time domain. Integrated time and absolute error is used as a performance metric in the time domain, while bandwidth is used as a measure in the frequency domain. Simultaneously, the amplitude margin and phase margin are used as constraints to ensure the stability of the high-type control system. Then, we adopt evolutionary algorithms to solve the formulated multi-objective problem. Unlike most of the existing approaches, we formulate intelligent high type control as a multi-objective optimization problem based on our knowledge about the control system. Furthermore, evolutionary algorithms are adopted to search for optimal solutions to real-world controlling systems. Extensive experiments are conducted to evaluate the effectiveness of our proposed approach. Compared to the Z-N method and the extending symmetrical optimum criterion, our proposed method achieves an improvement in bandwidth of more than 126.6%, while reducing the overshoot by more than 56.8% and the settling time by more than 48.4% for all controlled objects used in the experiments. At the same time, the tracking errors of the ramp and parabolic signals are significantly reduced, which means this method effectively improves the system performance.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"63 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85895285","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 : 2023-08-09DOI: 10.1177/00202940221090970
Du Xu, Tete Hu
In this paper, a continuously variable stiffness control strategy for shaft-hole assembly with a compliant wrist is proposed. The compliant wrist adjusts stiffness by changing the cantilever length of a super-elastic Ni-Ti wire. Its core idea is that when the contact force of the robot exceeds a particular value, the wrist adjusts the stiffness and can deform in a specific direction that guarantees assembly, allows a relatively significant misalignment, and produces a small force. The advantage of the proposed strategy is that the shaft-hole assembly status is supervised by calculating the deformation of compliant wrist based on contact force information, this significantly decrease the requirements of shaft-hole alignment accuracy. On this basis, the kinetostatic coupling kinematic and static force model is built and the fuzzy PD stiffness control strategy is designed to realize the desired stiffness of the wrist in various directions. Finally, the shaft-hole assembly experiments under different misalignment error demonstrates the reliability of the wrist, indicating the efficacy of the control method.
{"title":"Modelling and continuous stiffness control of robot with compliant wrist for misalignment shaft-hole assembly","authors":"Du Xu, Tete Hu","doi":"10.1177/00202940221090970","DOIUrl":"https://doi.org/10.1177/00202940221090970","url":null,"abstract":"In this paper, a continuously variable stiffness control strategy for shaft-hole assembly with a compliant wrist is proposed. The compliant wrist adjusts stiffness by changing the cantilever length of a super-elastic Ni-Ti wire. Its core idea is that when the contact force of the robot exceeds a particular value, the wrist adjusts the stiffness and can deform in a specific direction that guarantees assembly, allows a relatively significant misalignment, and produces a small force. The advantage of the proposed strategy is that the shaft-hole assembly status is supervised by calculating the deformation of compliant wrist based on contact force information, this significantly decrease the requirements of shaft-hole alignment accuracy. On this basis, the kinetostatic coupling kinematic and static force model is built and the fuzzy PD stiffness control strategy is designed to realize the desired stiffness of the wrist in various directions. Finally, the shaft-hole assembly experiments under different misalignment error demonstrates the reliability of the wrist, indicating the efficacy of the control method.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90346627","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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