Pub Date : 2023-10-10DOI: 10.1177/00202940231200956
Ye Chen, Guoliang Tao, Yitao Yao
Stabilization and learning are imperative to the high-performance feedback control of nonlinear systems. A dual adaptive robust control (DARC) scheme is proposed for nonlinear systems with model uncertainties to achieve a desired level of performance. Only the output of the nonlinear system is accessible in this work, all the states and parameters are learned online. Firstly, the DARC uses the prior physical bounds of systems to design a discontinuous projection with update rate limits which confines the bounds of parameter and state estimation. Then robustness of the nonlinear system can be guaranteed by the deterministic robust control (DRC) method. Secondly, a dual adaptive estimation mechanism (DAEM) is developed to learn the unknown parameters and states of systems. One part of the DAEM is the bounded gain forgetting (BGF) estimator, which is developed to handle inaccurate parameters and parametric variations. The other is the adaptive unscented Kalman filter (AUKF) synthesized for state estimation. The AUKF contains a statistic estimator based on the maximum a posterior (MAP) rule to estimate the unknown covariance matrix. Finally, simulation results illustrate the effectiveness of the suggested method.
{"title":"A dual adaptive robust control for nonlinear systems with parameter and state estimation","authors":"Ye Chen, Guoliang Tao, Yitao Yao","doi":"10.1177/00202940231200956","DOIUrl":"https://doi.org/10.1177/00202940231200956","url":null,"abstract":"Stabilization and learning are imperative to the high-performance feedback control of nonlinear systems. A dual adaptive robust control (DARC) scheme is proposed for nonlinear systems with model uncertainties to achieve a desired level of performance. Only the output of the nonlinear system is accessible in this work, all the states and parameters are learned online. Firstly, the DARC uses the prior physical bounds of systems to design a discontinuous projection with update rate limits which confines the bounds of parameter and state estimation. Then robustness of the nonlinear system can be guaranteed by the deterministic robust control (DRC) method. Secondly, a dual adaptive estimation mechanism (DAEM) is developed to learn the unknown parameters and states of systems. One part of the DAEM is the bounded gain forgetting (BGF) estimator, which is developed to handle inaccurate parameters and parametric variations. The other is the adaptive unscented Kalman filter (AUKF) synthesized for state estimation. The AUKF contains a statistic estimator based on the maximum a posterior (MAP) rule to estimate the unknown covariance matrix. Finally, simulation results illustrate the effectiveness of the suggested method.","PeriodicalId":49849,"journal":{"name":"Measurement & Control","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136357955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-10DOI: 10.1177/00202940231198133
Meiyan Chi, Xiaoning Zhu, Li Wang, Qin Zhang, Wenqian Liu
Due to the trade imbalance and poor management, a large number of empty containers are piled up after unpacking in importing regions, while the export-oriented areas are in urgent need of empty containers for replenishment. This paper aims to determine the volume of empty containers transferred from the surplus area to the shortage area and the inventory of each node from the operational level. We subdivide container freight stations into rail stations and road stations and consider using sea, road, and railway as transportation modes to transfer empty containers. A multi-period linear programing model of multimodal empty container repositioning is established aiming at minimizing the cost of empty container repositioning. A real case study of the transportation network in Northeast China is conducted to demonstrate that using multiple modes of transportation can significantly reduce the cost of empty container repositioning compared to using a single mode of transportation.
{"title":"Multi-period empty container repositioning approach for multimodal transportation","authors":"Meiyan Chi, Xiaoning Zhu, Li Wang, Qin Zhang, Wenqian Liu","doi":"10.1177/00202940231198133","DOIUrl":"https://doi.org/10.1177/00202940231198133","url":null,"abstract":"Due to the trade imbalance and poor management, a large number of empty containers are piled up after unpacking in importing regions, while the export-oriented areas are in urgent need of empty containers for replenishment. This paper aims to determine the volume of empty containers transferred from the surplus area to the shortage area and the inventory of each node from the operational level. We subdivide container freight stations into rail stations and road stations and consider using sea, road, and railway as transportation modes to transfer empty containers. A multi-period linear programing model of multimodal empty container repositioning is established aiming at minimizing the cost of empty container repositioning. A real case study of the transportation network in Northeast China is conducted to demonstrate that using multiple modes of transportation can significantly reduce the cost of empty container repositioning compared to using a single mode of transportation.","PeriodicalId":49849,"journal":{"name":"Measurement & Control","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136294182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Three-dimensional elliptical vibration assisted cutting (3D-EVC) technology has been widely used in many high-precision technical fields due to its high-efficiency processing characteristics. However, the hysteresis and nonlinearity caused by the piezoelectric drive in the 3D-EVC system will impact the system control accuracy. This paper mainly studies the hysteresis and nonlinearity of the system, the feedforward-gray predicted fuzzy PID compound controller based on the generalized Bouc-Wen hysteresis nonlinear model and it is designed to realize the hysteresis compensation of the system. In this paper, input voltage and output displacement are represented by a mathematical relationship, and this relationship of the 3D-EVC system will be described by the generalized Bouc-Wen model. The improved flower pollination algorithm (IFPASO) is adopted in the identification process of parameters. A compound control strategy is formed based on traditional feed-forward control combined with fuzzy PID feedback control to compensate for hysteresis and nonlinearity, and an improved gray prediction model is introduced into the feedback loop. The 3D-EVC system tracking experiment verifies the effectiveness of the designed compound controller. Experiments have proved that the hysteresis component of the system is significantly reduced after the use of the compound controller for hysteresis compensation, and the system has a higher degree of stability.
{"title":"Compensation control strategy of hybrid driven three-dimensional elliptical vibration assisted cutting system based on piezoelectric hysteresis model","authors":"Mingming Lu, Yuyang Liu, Xifeng Fu, Jieqiong Lin, Jiakang Zhou, Yongsheng Du, Zhaopeng Hao","doi":"10.1177/00202940231201885","DOIUrl":"https://doi.org/10.1177/00202940231201885","url":null,"abstract":"Three-dimensional elliptical vibration assisted cutting (3D-EVC) technology has been widely used in many high-precision technical fields due to its high-efficiency processing characteristics. However, the hysteresis and nonlinearity caused by the piezoelectric drive in the 3D-EVC system will impact the system control accuracy. This paper mainly studies the hysteresis and nonlinearity of the system, the feedforward-gray predicted fuzzy PID compound controller based on the generalized Bouc-Wen hysteresis nonlinear model and it is designed to realize the hysteresis compensation of the system. In this paper, input voltage and output displacement are represented by a mathematical relationship, and this relationship of the 3D-EVC system will be described by the generalized Bouc-Wen model. The improved flower pollination algorithm (IFPASO) is adopted in the identification process of parameters. A compound control strategy is formed based on traditional feed-forward control combined with fuzzy PID feedback control to compensate for hysteresis and nonlinearity, and an improved gray prediction model is introduced into the feedback loop. The 3D-EVC system tracking experiment verifies the effectiveness of the designed compound controller. Experiments have proved that the hysteresis component of the system is significantly reduced after the use of the compound controller for hysteresis compensation, and the system has a higher degree of stability.","PeriodicalId":49849,"journal":{"name":"Measurement & Control","volume":"158 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135095405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The unsteady partial differential equations (UPDE) with convection term gives a clear descriptions for the solidification process of a slab in dynamic production of continuous casting. To give a suitable setting value of secondary cooling water flow rate for the dynamic control system, this study investigates an optimal control problem (OCP) of UPDE with convection term. Firstly, control vector discretization of OCP and the solution of UPDE are given. Secondly, due to the rapidity for gradient, this paper analyzes the expression of the gradient calculation method based on Hamiltonian function costate system by approximate treatment, matrix calculation and composite trapezoidal integral method. Thirdly, an improved three-term spectrum conjugate gradient algorithm (ITSCGA) is proposed to solve the OCP of UPDE, and the global convergence of the ITSCGA is demonstrated. Lastly, the performance of ITSCGA is demonstrated by experimental simulations. The results demonstrate that the ITSCGA provides a smaller temperature fluctuations, and improves the quality of a slab.
{"title":"Parameterization optimal control of an unsteady partial differential equations with convection term by an improved three-term spectrum conjugate gradient algorithm","authors":"Yang Yu, Yu Wang, Xinfu Pang, Guodong Yang, Fengqi Zhang, Yiwen Qi","doi":"10.1177/00202940231201889","DOIUrl":"https://doi.org/10.1177/00202940231201889","url":null,"abstract":"The unsteady partial differential equations (UPDE) with convection term gives a clear descriptions for the solidification process of a slab in dynamic production of continuous casting. To give a suitable setting value of secondary cooling water flow rate for the dynamic control system, this study investigates an optimal control problem (OCP) of UPDE with convection term. Firstly, control vector discretization of OCP and the solution of UPDE are given. Secondly, due to the rapidity for gradient, this paper analyzes the expression of the gradient calculation method based on Hamiltonian function costate system by approximate treatment, matrix calculation and composite trapezoidal integral method. Thirdly, an improved three-term spectrum conjugate gradient algorithm (ITSCGA) is proposed to solve the OCP of UPDE, and the global convergence of the ITSCGA is demonstrated. Lastly, the performance of ITSCGA is demonstrated by experimental simulations. The results demonstrate that the ITSCGA provides a smaller temperature fluctuations, and improves the quality of a slab.","PeriodicalId":49849,"journal":{"name":"Measurement & Control","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135095769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-09DOI: 10.1177/00202940231201376
Kuan-Jung Chung, Chia-Wei Lin
RPThe wheel condition monitoring when the train in operation is significant task to prevent the occurrence of unexpected event. In this study, the piezoelectric sensors were installed on the railway track to collect the dynamic voltage-and-strain signals when the train wheels pressed them. These one-dimensional time series signals were transformed to the two-dimensional Recurrence Plots (RP) images as an input data sets for two deep learning models, Xception and EfficientNet-B7. The binary classification, Normal or Faulty as the diagnostical output to indicate the health state of the train wheels in that time. Five metrics were selected to evaluate the performance of two models, namely Accuracy, Precision, Recall, Miss Rate, and AUC. The results show that both models perform the high accuracy of 91.1% to the wheel condition classification. Furthermore, EfficientNet-B7 shows better performance in Recall, Miss-rate, and AUC metrics than those of Xception to express the premium ability in defective wheel identification, which is crucial for this application. Therefore, the efficientNet-B7 is selected as a favorable machine learning classifier for the fault diagnosis of rolling stock wheels. It is significant contribution to train wheel condition monitoring and health management since it provides the effective diagnostic information for maintenance decision to decrease the occurrence of unexpected event.
{"title":"Condition monitoring for fault diagnosis of railway wheels using recurrence plots and convolutional neural networks (RP-CNN) models","authors":"Kuan-Jung Chung, Chia-Wei Lin","doi":"10.1177/00202940231201376","DOIUrl":"https://doi.org/10.1177/00202940231201376","url":null,"abstract":"RPThe wheel condition monitoring when the train in operation is significant task to prevent the occurrence of unexpected event. In this study, the piezoelectric sensors were installed on the railway track to collect the dynamic voltage-and-strain signals when the train wheels pressed them. These one-dimensional time series signals were transformed to the two-dimensional Recurrence Plots (RP) images as an input data sets for two deep learning models, Xception and EfficientNet-B7. The binary classification, Normal or Faulty as the diagnostical output to indicate the health state of the train wheels in that time. Five metrics were selected to evaluate the performance of two models, namely Accuracy, Precision, Recall, Miss Rate, and AUC. The results show that both models perform the high accuracy of 91.1% to the wheel condition classification. Furthermore, EfficientNet-B7 shows better performance in Recall, Miss-rate, and AUC metrics than those of Xception to express the premium ability in defective wheel identification, which is crucial for this application. Therefore, the efficientNet-B7 is selected as a favorable machine learning classifier for the fault diagnosis of rolling stock wheels. It is significant contribution to train wheel condition monitoring and health management since it provides the effective diagnostic information for maintenance decision to decrease the occurrence of unexpected event.","PeriodicalId":49849,"journal":{"name":"Measurement & Control","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135095938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-05DOI: 10.1177/00202940231201375
Habib Benbouhenni, Ilhami Colak, Nicu Bizon, Emad Abdelkarim
Energy ripples are among the common problems in renewable energies as a result of using less efficient strategies. In this work, a new technique is suggested to control a doubly-fed induction generator (DFIG) using the pulse width modulation (PWM). The new technique is based on the combination of neural networks and fractional-order control to minimize the reactive and active power ripples of the DFIG-based variable speed dual-rotor wind turbine system. The suggested fractional-order neural control (FONC) with the PWM is a simple, robust and a high-performance strategy. Simulation is performed using Matlab software to validate the effectiveness of the designed control of 1.5 MW DFIG and the obtained results are compared with the traditional direct power control (DPC) in different working conditions. In addition, the comparison between the suggested control and the DPC is performed in the cases of changing or not changing the device parameters in terms of ripple ratio, dynamic response, steady-state error, current quality, and overshoot of active and reactive power of the DFIG. As compared to the DPC, the proposed FONC technique improves the active and reactive power ripples by 65.71% and 84.74%, respectively. Also, improves the overshoot of the active and reactive power by 71.33% and 91.72%, respectively. The simulation results demonstrate the high performance and robustness of the FONC technique for the parametric variations of the DFIG-based variable speed dual-rotor wind turbine system compared to the DPC control.
{"title":"Fractional-order neural control of a DFIG supplied by a two-level PWM inverter for dual-rotor wind turbine system","authors":"Habib Benbouhenni, Ilhami Colak, Nicu Bizon, Emad Abdelkarim","doi":"10.1177/00202940231201375","DOIUrl":"https://doi.org/10.1177/00202940231201375","url":null,"abstract":"Energy ripples are among the common problems in renewable energies as a result of using less efficient strategies. In this work, a new technique is suggested to control a doubly-fed induction generator (DFIG) using the pulse width modulation (PWM). The new technique is based on the combination of neural networks and fractional-order control to minimize the reactive and active power ripples of the DFIG-based variable speed dual-rotor wind turbine system. The suggested fractional-order neural control (FONC) with the PWM is a simple, robust and a high-performance strategy. Simulation is performed using Matlab software to validate the effectiveness of the designed control of 1.5 MW DFIG and the obtained results are compared with the traditional direct power control (DPC) in different working conditions. In addition, the comparison between the suggested control and the DPC is performed in the cases of changing or not changing the device parameters in terms of ripple ratio, dynamic response, steady-state error, current quality, and overshoot of active and reactive power of the DFIG. As compared to the DPC, the proposed FONC technique improves the active and reactive power ripples by 65.71% and 84.74%, respectively. Also, improves the overshoot of the active and reactive power by 71.33% and 91.72%, respectively. The simulation results demonstrate the high performance and robustness of the FONC technique for the parametric variations of the DFIG-based variable speed dual-rotor wind turbine system compared to the DPC control.","PeriodicalId":49849,"journal":{"name":"Measurement & Control","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135483747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-26DOI: 10.1177/00202940231192990
Dejun Liu, Chao Song, Ming Du, Guangda Chen, Peilin Liu, Mahmoud A AL-Shurufa, Yanming Cheng
Multi-motor synchronous drive system is increasingly widely used in industry and manufacturing, where its control structure and control strategy affect the quality and efficiency of production. In order to solve the contradiction between fastness and overshoot, and the difficulty in determining the compensation law in the conventional PID, cross-coupling control, and master-slave control strategies used in multi-motor control, this paper proposes a self-coupling PID control strategy based on ring adjacent compensation to reduce the complexity of the control structure. Furthermore, this paper analyzes the self-coupling PID parameter tuning rules and establishes the control structure of the ring coupling strategy, and proves its validity mathematically. The simulation results verify that the proposed strategy provides a fast response speed, high control precision, good disturbance rejection, and synchronization performance.
{"title":"Research on self-coupling PID for multi-driven synchronization control with ring adjacent compensation","authors":"Dejun Liu, Chao Song, Ming Du, Guangda Chen, Peilin Liu, Mahmoud A AL-Shurufa, Yanming Cheng","doi":"10.1177/00202940231192990","DOIUrl":"https://doi.org/10.1177/00202940231192990","url":null,"abstract":"Multi-motor synchronous drive system is increasingly widely used in industry and manufacturing, where its control structure and control strategy affect the quality and efficiency of production. In order to solve the contradiction between fastness and overshoot, and the difficulty in determining the compensation law in the conventional PID, cross-coupling control, and master-slave control strategies used in multi-motor control, this paper proposes a self-coupling PID control strategy based on ring adjacent compensation to reduce the complexity of the control structure. Furthermore, this paper analyzes the self-coupling PID parameter tuning rules and establishes the control structure of the ring coupling strategy, and proves its validity mathematically. The simulation results verify that the proposed strategy provides a fast response speed, high control precision, good disturbance rejection, and synchronization performance.","PeriodicalId":49849,"journal":{"name":"Measurement & Control","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134958622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
For the problem of the rotor position estimation and control accuracy of permanent magnet synchronous motor (PMSM), this paper proposes a PMSM sensorless based on radial basis function (RBF) neural network optimized Automatic disturbance rejection control (RBF-ADRC) and strong tracking filter (STF) improved square root generalized fifth-order cubature Kalman filter (SGHCKF-STF). The Automatic disturbance rejection control (ADRC) has strong robustness, but there are many parameters and difficult to adjust. Now we use RBF neural network to adjust the parameters in ADRC online so as to improve the robustness and anti-disturbance ability. In order to improve the estimation accuracy of rotor position and speed, the orthogonal triangle (QR) decomposition and STF are introduced on the basis of the generalized fifth-order cubature Kalman filter (GHCKF) to design the SGHCKF-STF algorithm that not only ensure the non-positive nature of the covariance matrix but also improve the ability to cope with sudden changes in state during the filtering process. Experimental results show that the combination of RBF-ADRC and SGHCKF-STF improve the sensorless control effect of the PMSM to some extent.
{"title":"Sensorless control of a PMSM based on an RBF neural network-optimized ADRC and SGHCKF-STF algorithm","authors":"Haoran Li, Rongyun Zhang, Peicheng Shi, Ye Mei, Kunming Zheng, Tian Qiu","doi":"10.1177/00202940231195908","DOIUrl":"https://doi.org/10.1177/00202940231195908","url":null,"abstract":"For the problem of the rotor position estimation and control accuracy of permanent magnet synchronous motor (PMSM), this paper proposes a PMSM sensorless based on radial basis function (RBF) neural network optimized Automatic disturbance rejection control (RBF-ADRC) and strong tracking filter (STF) improved square root generalized fifth-order cubature Kalman filter (SGHCKF-STF). The Automatic disturbance rejection control (ADRC) has strong robustness, but there are many parameters and difficult to adjust. Now we use RBF neural network to adjust the parameters in ADRC online so as to improve the robustness and anti-disturbance ability. In order to improve the estimation accuracy of rotor position and speed, the orthogonal triangle (QR) decomposition and STF are introduced on the basis of the generalized fifth-order cubature Kalman filter (GHCKF) to design the SGHCKF-STF algorithm that not only ensure the non-positive nature of the covariance matrix but also improve the ability to cope with sudden changes in state during the filtering process. Experimental results show that the combination of RBF-ADRC and SGHCKF-STF improve the sensorless control effect of the PMSM to some extent.","PeriodicalId":49849,"journal":{"name":"Measurement & Control","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136060187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-22DOI: 10.1177/00202940231198130
Juan Liang, Qian Xu, Na Wang
In practice, many systems are affected by mismatched disturbances, which do not satisfy the match condition. This study focuses on a variable gain super-twisting sliding mode controller that achieves global robust fixed-time stabilization of second-order systems with matched and mismatched disturbances without disturbances observers. The proposed controller and the sliding variables adopt a state-dependent variable exponent coefficient, which improves the robustness properties of a sliding surface and switching control law. At the same time, the control strategy alleviates the chattering phenomenon by using the variable-gain super-twisting algorithm. The settling time is calculated a priori by the Lyapunov method. Simulation results show that, compared with recently published controllers, our proposed control strategy can suppress the mismatched disturbance more rapidly, simply, and effectively.
{"title":"Fixed-time stability super-twisting sliding mode control with mismatched disturbances","authors":"Juan Liang, Qian Xu, Na Wang","doi":"10.1177/00202940231198130","DOIUrl":"https://doi.org/10.1177/00202940231198130","url":null,"abstract":"In practice, many systems are affected by mismatched disturbances, which do not satisfy the match condition. This study focuses on a variable gain super-twisting sliding mode controller that achieves global robust fixed-time stabilization of second-order systems with matched and mismatched disturbances without disturbances observers. The proposed controller and the sliding variables adopt a state-dependent variable exponent coefficient, which improves the robustness properties of a sliding surface and switching control law. At the same time, the control strategy alleviates the chattering phenomenon by using the variable-gain super-twisting algorithm. The settling time is calculated a priori by the Lyapunov method. Simulation results show that, compared with recently published controllers, our proposed control strategy can suppress the mismatched disturbance more rapidly, simply, and effectively.","PeriodicalId":49849,"journal":{"name":"Measurement & Control","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136060025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-22DOI: 10.1177/00202940231199998
Zhe Song, Xi Xiao, Jun Yang, Tao Tao, Xuesong Mei
To enhance the anti-inertia disturbance ability of permanent magnet synchronous motor (PMSM) speed system, an adaptive sliding mode control with inertia identification is proposed. A novel sliding mode control (NSMC) based on a new reaching law coupled with model reference adaptive system (MRAS) inertia identification is realized the adaptive control, named MRAS+NSMC. In the NSMC construct process, an integral sliding mode surface and a variable speed reaching law are introduced to avoid speed differentiation and improve dynamics, respectively. And the new reaching law imported a successive sigmoid( s) to replace the traditional sign( s) to suppress chattering phenomena. For the problem that the performance deteriorated by rotational inertia variation caused by load changes, the inertia is estimated in real time according to the MRAS theory, and the identification value is updated to the NSMC controller to realize adaptive MRAS+NSMC speed control. Experimental results show that the proposed adaptive MRAS+NSMC control has a faster speed response, and the speed response time is reduced from 85 to 49 ms compared with conventional SMC control. In addition, it has strong robustness to inertia disturbances and high speed tracking accuracy. Compared with conventional SMC, the speed tracking accuracy of proposed MRAS+NSMC is increased from 12% to 4%. This makes the proposed MRAS+NSMC control has great potential practical significance for speed control of PMSM.
{"title":"A novel sliding mode control with MRAS inertia identification for permanent magnet synchronous motors","authors":"Zhe Song, Xi Xiao, Jun Yang, Tao Tao, Xuesong Mei","doi":"10.1177/00202940231199998","DOIUrl":"https://doi.org/10.1177/00202940231199998","url":null,"abstract":"To enhance the anti-inertia disturbance ability of permanent magnet synchronous motor (PMSM) speed system, an adaptive sliding mode control with inertia identification is proposed. A novel sliding mode control (NSMC) based on a new reaching law coupled with model reference adaptive system (MRAS) inertia identification is realized the adaptive control, named MRAS+NSMC. In the NSMC construct process, an integral sliding mode surface and a variable speed reaching law are introduced to avoid speed differentiation and improve dynamics, respectively. And the new reaching law imported a successive sigmoid( s) to replace the traditional sign( s) to suppress chattering phenomena. For the problem that the performance deteriorated by rotational inertia variation caused by load changes, the inertia is estimated in real time according to the MRAS theory, and the identification value is updated to the NSMC controller to realize adaptive MRAS+NSMC speed control. Experimental results show that the proposed adaptive MRAS+NSMC control has a faster speed response, and the speed response time is reduced from 85 to 49 ms compared with conventional SMC control. In addition, it has strong robustness to inertia disturbances and high speed tracking accuracy. Compared with conventional SMC, the speed tracking accuracy of proposed MRAS+NSMC is increased from 12% to 4%. This makes the proposed MRAS+NSMC control has great potential practical significance for speed control of PMSM.","PeriodicalId":49849,"journal":{"name":"Measurement & Control","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136060364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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