Pub Date : 2023-03-31DOI: 10.1177/00202940231165257
Ahmed Abdelmoniem, Abdullah Ali, Youssef Taher, M. Abdelaziz, S. Maged
The challenge of trajectory tracking of autonomous vehicles (AVs) is a critical aspect that must be effectively addressed. Recent studies are concerned with maintaining the yaw stability to guarantee the customers’ comfort throughout the journey. Most of the geometrical controllers solve this task by dividing it into consecutive point stabilization problems, limiting the controllers’ ability to handle sudden trajectory changes. One research presented a predictive Stanley lateral controller that uses a discrete prediction model to mimic human behavior by anticipating the vehicle’s future states. That controller is limited in its use, as the parameters must be manually tuned for every change in the maneuver or vehicle velocity. This article presents a novel approach for trajectory tracking in autonomous vehicles, by introducing a fuzzy supervisory controller that automatically adapts to changes in the vehicle’s velocity and maneuver by estimating the prediction horizon’s length and providing different weights for each controller. The proposed method overcomes the limitations of traditional controllers that require manual tuning of parameters, making it ready for real-world experiments. This is the main contribution of the research in this paper. The suggested technique demonstrated an advantage over the Basic Stanley controller and the manually tuned predictive Stanley controller in terms of the total lateral error and the model predictive control (MPC) in terms of computational time. The performance is determined by performing various simulations on V-Rep and hardware-in-the-loop (HIL) experiments on an E-CAR golf bus. A broad selection of velocities is used to validate the behavior of the vehicle while working on different maneuvers (double lane change, hook road, S road, and curved road).
{"title":"Fuzzy predictive Stanley lateral controller with adaptive prediction horizon","authors":"Ahmed Abdelmoniem, Abdullah Ali, Youssef Taher, M. Abdelaziz, S. Maged","doi":"10.1177/00202940231165257","DOIUrl":"https://doi.org/10.1177/00202940231165257","url":null,"abstract":"The challenge of trajectory tracking of autonomous vehicles (AVs) is a critical aspect that must be effectively addressed. Recent studies are concerned with maintaining the yaw stability to guarantee the customers’ comfort throughout the journey. Most of the geometrical controllers solve this task by dividing it into consecutive point stabilization problems, limiting the controllers’ ability to handle sudden trajectory changes. One research presented a predictive Stanley lateral controller that uses a discrete prediction model to mimic human behavior by anticipating the vehicle’s future states. That controller is limited in its use, as the parameters must be manually tuned for every change in the maneuver or vehicle velocity. This article presents a novel approach for trajectory tracking in autonomous vehicles, by introducing a fuzzy supervisory controller that automatically adapts to changes in the vehicle’s velocity and maneuver by estimating the prediction horizon’s length and providing different weights for each controller. The proposed method overcomes the limitations of traditional controllers that require manual tuning of parameters, making it ready for real-world experiments. This is the main contribution of the research in this paper. The suggested technique demonstrated an advantage over the Basic Stanley controller and the manually tuned predictive Stanley controller in terms of the total lateral error and the model predictive control (MPC) in terms of computational time. The performance is determined by performing various simulations on V-Rep and hardware-in-the-loop (HIL) experiments on an E-CAR golf bus. A broad selection of velocities is used to validate the behavior of the vehicle while working on different maneuvers (double lane change, hook road, S road, and curved road).","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90739184","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 : 2023-03-27DOI: 10.1177/00202940231164126
Jun Ma, Xiao Wang, Cuifeng Xu, Jing Ling
When dealing with complex trajectories, and the interference by the unmanned aerial vehicle (UAV) itself or other flying objects, the traditional detecting methods based on YOLOv5 network mainly focus on one UAV and difficult to detect the multi-UAV effectively. In order to improve the detection method, a novel algorithm combined with swin transformer blocks and a fusion-concat method based on YOLOv5 network, so called SF-YOLOv5, is proposed. Furthermore, by using the distance intersection over union and non-maximum suppression (DIoU-NMS) as post-processing method, the proposed network can remove redundant detection boxes and improve the efficiency of the multi-UAV detection. Experimental results verify the feasibility and effectiveness of the proposed network, and show that the mAP trained on the two datasets used in experiments has been improved by 2.5 and 4.11% respectively. The proposed network can detect multi-UAV while ensuring accuracy and speed, and can be effectively used in the field of UAV monitoring or other types of multi-object detection applications.
{"title":"SF-YOLOv5: Improved YOLOv5 with swin transformer and fusion-concat method for multi-UAV detection","authors":"Jun Ma, Xiao Wang, Cuifeng Xu, Jing Ling","doi":"10.1177/00202940231164126","DOIUrl":"https://doi.org/10.1177/00202940231164126","url":null,"abstract":"When dealing with complex trajectories, and the interference by the unmanned aerial vehicle (UAV) itself or other flying objects, the traditional detecting methods based on YOLOv5 network mainly focus on one UAV and difficult to detect the multi-UAV effectively. In order to improve the detection method, a novel algorithm combined with swin transformer blocks and a fusion-concat method based on YOLOv5 network, so called SF-YOLOv5, is proposed. Furthermore, by using the distance intersection over union and non-maximum suppression (DIoU-NMS) as post-processing method, the proposed network can remove redundant detection boxes and improve the efficiency of the multi-UAV detection. Experimental results verify the feasibility and effectiveness of the proposed network, and show that the mAP trained on the two datasets used in experiments has been improved by 2.5 and 4.11% respectively. The proposed network can detect multi-UAV while ensuring accuracy and speed, and can be effectively used in the field of UAV monitoring or other types of multi-object detection applications.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"75 1","pages":"1436 - 1445"},"PeriodicalIF":0.0,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85119984","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 : 2023-03-27DOI: 10.1177/00202940231164125
C. Gökçe
In this study, we propose a novel controller architecture and design for the automatic control of agricultural mobile robots to be used in farms and greenhouses. There are two novelties of this study. The first novelty is a completely new type of controller architecture proposed in which reference inputs and measured outputs are fed separately independent from each other to the controller. The controller architecture currently used in the literature uses only the difference between reference and measurement which is the error signal. The proposed architecture in this study is completely novel in the sense that not only the error information is used in the controller but also the information in reference inputs and information in measured outputs are used separately. This means a completely new type of look to control system by utilizing the information maximally in order to achieve superior performance. This performance boost is shown in the paper where the proposed architecture achieves up to 2000% better performance compared with state-of-the-art controllers. Second, controller architecture is grown to a complex structure from an initially simple PID structure. Using the maximal information comes with the cost of computational complexity to design the controller. The second novelty of growing the controller from initially simple PID equivalent controller tackles this difficulty by making the problem tractable and efficient to compute. This way the proposed novel controller can be designed within minutes in a commercially available laptop computer. The proposed controller is tested on a simulated agricultural mobile robot and results are compared with a previous state-of-the-art optimal controller. It is believed that the proposed architecture will be dominant in future automatic controllers and make current state-of-the-art controllers obsolete. This is because of the full utilization of information in controller design which results in robust disturbance rejection performance.
{"title":"Single-layer neural-network based control of agricultural mobile robot","authors":"C. Gökçe","doi":"10.1177/00202940231164125","DOIUrl":"https://doi.org/10.1177/00202940231164125","url":null,"abstract":"In this study, we propose a novel controller architecture and design for the automatic control of agricultural mobile robots to be used in farms and greenhouses. There are two novelties of this study. The first novelty is a completely new type of controller architecture proposed in which reference inputs and measured outputs are fed separately independent from each other to the controller. The controller architecture currently used in the literature uses only the difference between reference and measurement which is the error signal. The proposed architecture in this study is completely novel in the sense that not only the error information is used in the controller but also the information in reference inputs and information in measured outputs are used separately. This means a completely new type of look to control system by utilizing the information maximally in order to achieve superior performance. This performance boost is shown in the paper where the proposed architecture achieves up to 2000% better performance compared with state-of-the-art controllers. Second, controller architecture is grown to a complex structure from an initially simple PID structure. Using the maximal information comes with the cost of computational complexity to design the controller. The second novelty of growing the controller from initially simple PID equivalent controller tackles this difficulty by making the problem tractable and efficient to compute. This way the proposed novel controller can be designed within minutes in a commercially available laptop computer. The proposed controller is tested on a simulated agricultural mobile robot and results are compared with a previous state-of-the-art optimal controller. It is believed that the proposed architecture will be dominant in future automatic controllers and make current state-of-the-art controllers obsolete. This is because of the full utilization of information in controller design which results in robust disturbance rejection performance.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"14 1","pages":"1446 - 1454"},"PeriodicalIF":0.0,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85534310","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 : 2023-03-27DOI: 10.1177/00202940231160569
Wen-Qian Jing, Guang-Sheng Liu
In order to solve the problems of spatial resolution limit and reduce the measurement cost, the compressive sensing theory and the sparse regularization are applied to the near-field acoustic holography (NAH) technology. In the previous works, the Equivalent Source Method (ESM)-based NAH has been extended in the sparsity framework by sampling the sound pressure signals sparsely. However, this Compressive ESM (CESM) mode would suffer from the low precision problem in the particle velocity reconstruction. To improve the reconstruction accuracy of the particle velocity, this paper is going to take the sparse particle velocity as the input of NAH to establish a new CESM mode based on the particle velocity measurement. In the meantime, the number of sampling points will be reduced greatly without losing the reconstruction accuracy when compared to the conventional ESM with the Tikhonov regularization based on the particle velocity measurement. Several numerical simulation experiments have been carried out to examine the performance of the proposed model. The results show that the proposed model delivers a satisfactory performance in the reconstruction of both the pressure and particle velocity on the condition that the number of sampling points is much smaller than that of the conventional ESM, and the proposed model performs much better than the existing CESM mode based on the sound pressure measurement especially when reconstructing the particle velocity.
{"title":"Compressive equivalent source method based on particle velocity measurements for near-field acoustic holography","authors":"Wen-Qian Jing, Guang-Sheng Liu","doi":"10.1177/00202940231160569","DOIUrl":"https://doi.org/10.1177/00202940231160569","url":null,"abstract":"In order to solve the problems of spatial resolution limit and reduce the measurement cost, the compressive sensing theory and the sparse regularization are applied to the near-field acoustic holography (NAH) technology. In the previous works, the Equivalent Source Method (ESM)-based NAH has been extended in the sparsity framework by sampling the sound pressure signals sparsely. However, this Compressive ESM (CESM) mode would suffer from the low precision problem in the particle velocity reconstruction. To improve the reconstruction accuracy of the particle velocity, this paper is going to take the sparse particle velocity as the input of NAH to establish a new CESM mode based on the particle velocity measurement. In the meantime, the number of sampling points will be reduced greatly without losing the reconstruction accuracy when compared to the conventional ESM with the Tikhonov regularization based on the particle velocity measurement. Several numerical simulation experiments have been carried out to examine the performance of the proposed model. The results show that the proposed model delivers a satisfactory performance in the reconstruction of both the pressure and particle velocity on the condition that the number of sampling points is much smaller than that of the conventional ESM, and the proposed model performs much better than the existing CESM mode based on the sound pressure measurement especially when reconstructing the particle velocity.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"30 1","pages":"1471 - 1482"},"PeriodicalIF":0.0,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85493652","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 : 2023-03-26DOI: 10.1177/00202940231156195
T. Tran, V. T. Duong, Huy Hung Nguyen, T. Nguyen
In this paper, a novel backstepping terminal super-twisting sliding mode (TSTSM) with high order sliding mode observer (HOSMO) is proposed to control the two degrees of freedom (DOFs) Serial Elastic Actuator (SEA), inspired by a lower limb of humanoid robots. First, the dynamic model, extended from our previous study, is presented for developing the control algorithm. Secondly, the backstepping technique is utilized to separate the overall system into two subsystems. One of the challenges of SEA is to deal with the evident oscillations caused by the elastic element, which might lead to the degrading performance of load position control. In order to reduce this adverse effect, a TSTSM is proposed to control the position tracking of two subsystems. The advantages of TSTSM are the finite-time convergence despite the bounded perturbation and the dramatic reduction of the chattering phenomenon. To construct and implement the TSTSM controller, it requires the knowledge of all states, which is not available in the current lower limb system setup. Therefore, a HOSMO is utilized to estimate the unknown states. Finally, experiment results are carried out to assess the effectiveness of the proposed controller and compare it with those of different control schemes.
{"title":"Terminal super-twisting sliding mode based on high order sliding mode observer for two DOFs lower limb system","authors":"T. Tran, V. T. Duong, Huy Hung Nguyen, T. Nguyen","doi":"10.1177/00202940231156195","DOIUrl":"https://doi.org/10.1177/00202940231156195","url":null,"abstract":"In this paper, a novel backstepping terminal super-twisting sliding mode (TSTSM) with high order sliding mode observer (HOSMO) is proposed to control the two degrees of freedom (DOFs) Serial Elastic Actuator (SEA), inspired by a lower limb of humanoid robots. First, the dynamic model, extended from our previous study, is presented for developing the control algorithm. Secondly, the backstepping technique is utilized to separate the overall system into two subsystems. One of the challenges of SEA is to deal with the evident oscillations caused by the elastic element, which might lead to the degrading performance of load position control. In order to reduce this adverse effect, a TSTSM is proposed to control the position tracking of two subsystems. The advantages of TSTSM are the finite-time convergence despite the bounded perturbation and the dramatic reduction of the chattering phenomenon. To construct and implement the TSTSM controller, it requires the knowledge of all states, which is not available in the current lower limb system setup. Therefore, a HOSMO is utilized to estimate the unknown states. Finally, experiment results are carried out to assess the effectiveness of the proposed controller and compare it with those of different control schemes.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"1 1","pages":"1455 - 1470"},"PeriodicalIF":0.0,"publicationDate":"2023-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77797819","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 : 2023-03-25DOI: 10.1177/00202940231159117
Shimin Yang, Nan Cao, Bing Yu
Almost all of the wear debris generated during the operation of the machine is suspended in the circulating lubricating oil. The analysis of the wear debris in the lubricating oil can effectively monitor the wear state of the machine and provide early warning of failures. An overview on inductive sensors for measuring wear debris in lubrication is introduced. To begin with, the significance of analyzing the wear debris in lubricating oil is explained and the working principle of the inductive wear sensors is illustrated. Furthermore, the development of inductive wear sensors and the key limitations are summarized. Finally, some rest factors affecting the sensor and the processing method of the induction signal aliasing are discussed, and the future development trend is prospected. It is pointed out that developing high sensitivity wear debris inductive sensors, increasing sensor throughput, and solving the problem of aliasing of detection signals are the following issues that should be further studied in the future.
{"title":"Wear debris measurement in lubricating oil based on inductive method: A review","authors":"Shimin Yang, Nan Cao, Bing Yu","doi":"10.1177/00202940231159117","DOIUrl":"https://doi.org/10.1177/00202940231159117","url":null,"abstract":"Almost all of the wear debris generated during the operation of the machine is suspended in the circulating lubricating oil. The analysis of the wear debris in the lubricating oil can effectively monitor the wear state of the machine and provide early warning of failures. An overview on inductive sensors for measuring wear debris in lubrication is introduced. To begin with, the significance of analyzing the wear debris in lubricating oil is explained and the working principle of the inductive wear sensors is illustrated. Furthermore, the development of inductive wear sensors and the key limitations are summarized. Finally, some rest factors affecting the sensor and the processing method of the induction signal aliasing are discussed, and the future development trend is prospected. It is pointed out that developing high sensitivity wear debris inductive sensors, increasing sensor throughput, and solving the problem of aliasing of detection signals are the following issues that should be further studied in the future.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"6 1","pages":"1422 - 1435"},"PeriodicalIF":0.0,"publicationDate":"2023-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74588753","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 : 2023-03-22DOI: 10.1177/00202940231161573
Jinxia Wu, Jianwei Li, Chuang Liu, Wei-Tzen Yang
This paper studies robust stabilization problem and state feedback controller design problem for a class of complex production process systems by pattern class variable instead of state variable or output variable. Firstly, the maximum entropy clustering method is introduced and modeling method based on multi-dimensional moving pattern is given. Nonlinear state space models of systems with input-delay are established by using the trajectories of pattern class variable. Then sufficient conditions for robust stabilization of the system are obtained by Linear Matrix Inequality. In addition, a state feedback controller is designed based on this condition. Finally, the effectiveness of the methods is illustrated by taking the actual working conditions data as an example.
{"title":"Robust stabilization for a class of complex production process systems based on multi-dimensional moving pattern","authors":"Jinxia Wu, Jianwei Li, Chuang Liu, Wei-Tzen Yang","doi":"10.1177/00202940231161573","DOIUrl":"https://doi.org/10.1177/00202940231161573","url":null,"abstract":"This paper studies robust stabilization problem and state feedback controller design problem for a class of complex production process systems by pattern class variable instead of state variable or output variable. Firstly, the maximum entropy clustering method is introduced and modeling method based on multi-dimensional moving pattern is given. Nonlinear state space models of systems with input-delay are established by using the trajectories of pattern class variable. Then sufficient conditions for robust stabilization of the system are obtained by Linear Matrix Inequality. In addition, a state feedback controller is designed based on this condition. Finally, the effectiveness of the methods is illustrated by taking the actual working conditions data as an example.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"16 1","pages":"1410 - 1421"},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84138089","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 : 2023-03-20DOI: 10.1177/00202940231161568
K. Liang, Zhiqiang Yang, Wei Fang, Jian Wang
One credible method for performance evaluation of network timing service was proposed, based on one kind of disciplined time standard with GNSS time transfer, NIMDO. The performance of the NTP timing service were characterized over multiple baselines on both the Internet and the Intranet, and the network delay and the timing offset were analyzed in detail. The results show that on the Internet the averaged timing offsets via the NTP servers are roughly hundreds of μs to several ms level, and on the Intranet the averaged timing offsets via the NTP servers are at about 20 μs level. NTP timing service was mainly affected by white phase noise, and flicker phase noise at the different sites. The maximum change of the timing offset was one-half of the maximum change of RTDelay. The uncertainties have been separately evaluated as less than 30 ms on the Internet and less than 60 μs on the Intranet for NTP timing service.
{"title":"Performance characterization of network timing with remote traceability via GNSS time transfer","authors":"K. Liang, Zhiqiang Yang, Wei Fang, Jian Wang","doi":"10.1177/00202940231161568","DOIUrl":"https://doi.org/10.1177/00202940231161568","url":null,"abstract":"One credible method for performance evaluation of network timing service was proposed, based on one kind of disciplined time standard with GNSS time transfer, NIMDO. The performance of the NTP timing service were characterized over multiple baselines on both the Internet and the Intranet, and the network delay and the timing offset were analyzed in detail. The results show that on the Internet the averaged timing offsets via the NTP servers are roughly hundreds of μs to several ms level, and on the Intranet the averaged timing offsets via the NTP servers are at about 20 μs level. NTP timing service was mainly affected by white phase noise, and flicker phase noise at the different sites. The maximum change of the timing offset was one-half of the maximum change of RTDelay. The uncertainties have been separately evaluated as less than 30 ms on the Internet and less than 60 μs on the Intranet for NTP timing service.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"30 1","pages":"1387 - 1395"},"PeriodicalIF":0.0,"publicationDate":"2023-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87142788","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 : 2023-03-20DOI: 10.1177/00202940231159928
Long Li, Shengzheng Kang, Dongming Bai, Hongtao Wu, Jiangli Yu
Piezoelectric micropositioning systems (PMSs) have been widely utilized in the high-precision manipulation applications, but are also subjected to undesired nonlinearities, like hysteresis, and parameter uncertainties. To solve this problem, this paper proposes a new robust sliding mode control scheme for a class of nonlinear PMSs with time-varying uncertainties. Different from the conventional sliding mode control (SMC), the proposed controller further combines the Fourier series-based function estimation technique, fuzzy logic system and adaptive learning algorithm to realize online estimation and compensation of system time-varying uncertainties without their boundary information. The adaptive laws of Fourier coefficients and fuzzy adjustable parameters are obtained via the Lyapunov stability theory. Compared with the existing SMC methods, the proposed control effectively eliminates the control chattering problem, and guarantees the convergence of the tracking error in finite time in the presence of time-varying uncertainties. Theoretical analysis and numerical simulation results show that the proposed control strategy can meet the high-speed, high-precision robust tracking performance requirements of PMSs for micro/nano-manipulation applications.
{"title":"Robust high-precision tracking control for a class of nonlinear piezoelectric micropositioning systems with time-varying uncertainties","authors":"Long Li, Shengzheng Kang, Dongming Bai, Hongtao Wu, Jiangli Yu","doi":"10.1177/00202940231159928","DOIUrl":"https://doi.org/10.1177/00202940231159928","url":null,"abstract":"Piezoelectric micropositioning systems (PMSs) have been widely utilized in the high-precision manipulation applications, but are also subjected to undesired nonlinearities, like hysteresis, and parameter uncertainties. To solve this problem, this paper proposes a new robust sliding mode control scheme for a class of nonlinear PMSs with time-varying uncertainties. Different from the conventional sliding mode control (SMC), the proposed controller further combines the Fourier series-based function estimation technique, fuzzy logic system and adaptive learning algorithm to realize online estimation and compensation of system time-varying uncertainties without their boundary information. The adaptive laws of Fourier coefficients and fuzzy adjustable parameters are obtained via the Lyapunov stability theory. Compared with the existing SMC methods, the proposed control effectively eliminates the control chattering problem, and guarantees the convergence of the tracking error in finite time in the presence of time-varying uncertainties. Theoretical analysis and numerical simulation results show that the proposed control strategy can meet the high-speed, high-precision robust tracking performance requirements of PMSs for micro/nano-manipulation applications.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"80 1","pages":"1396 - 1409"},"PeriodicalIF":0.0,"publicationDate":"2023-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90605795","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 : 2023-03-20DOI: 10.1177/00202940231159115
P. Cheng, Jinyan Pan, Yi Zhang
This paper aims at developing a novel detection and identification method against malicious attacks in intelligent transportation. Due to the development and applications of communication and advanced sensor technologies, intelligent transportation has faced new safety risks. In particular, the emerging malicious attacks, such as false data injection attack, can mask the destruction of physical dynamic by tampering with information in layer to fool the current detection methods. Because of this reason, an adaptive unknown input observer-based detection and identification method is developed. Firstly, a physical dynamics model of vehicle networking system is established by considering the actual physical state. Considering the spoofing characteristics of false data injection attack, an unknown input observer-based detection method is proposed. Through the design of adaptive unknown input observer parameters, the detection performance, can be improved by cutting down the state estimation error. Compared with the UIO-based detection method, simulations demonstrate that the false positive rate can be reduced 0.1%. Based on the feature of state residuals that is not sensitive to the attacked ith residual, but sensitive to other residuals, a novel identification criterion is developed. At last, simulation experiments on the Matlab verify the performance of the proposed detection and identification algorithm in intelligent transportation system.
{"title":"Adaptive unknown input observer-based detection and identification method for intelligent transportation under malicious attack","authors":"P. Cheng, Jinyan Pan, Yi Zhang","doi":"10.1177/00202940231159115","DOIUrl":"https://doi.org/10.1177/00202940231159115","url":null,"abstract":"This paper aims at developing a novel detection and identification method against malicious attacks in intelligent transportation. Due to the development and applications of communication and advanced sensor technologies, intelligent transportation has faced new safety risks. In particular, the emerging malicious attacks, such as false data injection attack, can mask the destruction of physical dynamic by tampering with information in layer to fool the current detection methods. Because of this reason, an adaptive unknown input observer-based detection and identification method is developed. Firstly, a physical dynamics model of vehicle networking system is established by considering the actual physical state. Considering the spoofing characteristics of false data injection attack, an unknown input observer-based detection method is proposed. Through the design of adaptive unknown input observer parameters, the detection performance, can be improved by cutting down the state estimation error. Compared with the UIO-based detection method, simulations demonstrate that the false positive rate can be reduced 0.1%. Based on the feature of state residuals that is not sensitive to the attacked ith residual, but sensitive to other residuals, a novel identification criterion is developed. At last, simulation experiments on the Matlab verify the performance of the proposed detection and identification algorithm in intelligent transportation system.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"117 1","pages":"1377 - 1386"},"PeriodicalIF":0.0,"publicationDate":"2023-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85505315","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}