Pub Date : 2021-09-06DOI: 10.1080/21642583.2021.1969700
Yixian Fang, Rui Bai
This paper has studied the adaptive fuzzy fault-tolerant control (FTC) for active suspension systems via the sensor failure compensation method. In the control design, fuzzy logic systems (FLSs) are used to identify the unknown nonlinear dynamics, and the projection technique is utilized to deal with the multiple sensor failures. Combining with the backstepping technique, a novel FTC method has been developed. The proposed control method can guarantee that all the signals in the closed-loop system are all bounded, and the tracking error can converge to the neighbourhood of the origin. Finally, a simulation for the quarter active suspension system is given to verify the effectiveness of the developed control scheme.
{"title":"Adaptive fuzzy sensor failure compensation for active suspension systems with multiple sensor failures","authors":"Yixian Fang, Rui Bai","doi":"10.1080/21642583.2021.1969700","DOIUrl":"https://doi.org/10.1080/21642583.2021.1969700","url":null,"abstract":"This paper has studied the adaptive fuzzy fault-tolerant control (FTC) for active suspension systems via the sensor failure compensation method. In the control design, fuzzy logic systems (FLSs) are used to identify the unknown nonlinear dynamics, and the projection technique is utilized to deal with the multiple sensor failures. Combining with the backstepping technique, a novel FTC method has been developed. The proposed control method can guarantee that all the signals in the closed-loop system are all bounded, and the tracking error can converge to the neighbourhood of the origin. Finally, a simulation for the quarter active suspension system is given to verify the effectiveness of the developed control scheme.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2021-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41688467","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 : 2021-09-06DOI: 10.1080/21642583.2021.1975321
Peiyun Ye, Yang Yu, Wei Wang
This paper studies the trajectory tracking problem of quadrotor unmanned aerial vehicle (QUAV) with model nonlinearities and external disturbances via event-triggered control technique. Dividing the QUAV system into position subsystem and attitude subsystem, an adaptive fuzzy control algorithm is designed in position subsystem to provide desired pitch and roll angles for the attitude subsystem. Then, by constructing an event-triggered mechanism, an event-triggered adaptive fuzzy control algorithm is presented in the attitude subsystem, where the control law and the fuzzy parameter adaptive law are updated in an aperiodic form. Based on Lyapunov stability theory, it is proved that all signals in the closed-loop system are uniformly ultimately bounded via the impulsive dynamical system tool, and the tracking errors converge to a small neighbourhood of the origin. Besides, it is proved that there is a positive lower bound between the intersample time to avoid Zeno behaviour. Finally, simulation results illustrate that the proposed control scheme can guarantee the trajectory tracking performance of the QUAV system, while it can reduce the update frequency of the controller and improve the resource utilization.
{"title":"Event-triggered control for trajectory tracking of quadrotor unmanned aerial vehicle","authors":"Peiyun Ye, Yang Yu, Wei Wang","doi":"10.1080/21642583.2021.1975321","DOIUrl":"https://doi.org/10.1080/21642583.2021.1975321","url":null,"abstract":"This paper studies the trajectory tracking problem of quadrotor unmanned aerial vehicle (QUAV) with model nonlinearities and external disturbances via event-triggered control technique. Dividing the QUAV system into position subsystem and attitude subsystem, an adaptive fuzzy control algorithm is designed in position subsystem to provide desired pitch and roll angles for the attitude subsystem. Then, by constructing an event-triggered mechanism, an event-triggered adaptive fuzzy control algorithm is presented in the attitude subsystem, where the control law and the fuzzy parameter adaptive law are updated in an aperiodic form. Based on Lyapunov stability theory, it is proved that all signals in the closed-loop system are uniformly ultimately bounded via the impulsive dynamical system tool, and the tracking errors converge to a small neighbourhood of the origin. Besides, it is proved that there is a positive lower bound between the intersample time to avoid Zeno behaviour. Finally, simulation results illustrate that the proposed control scheme can guarantee the trajectory tracking performance of the QUAV system, while it can reduce the update frequency of the controller and improve the resource utilization.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2021-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43305626","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 : 2021-07-27DOI: 10.1080/21642583.2021.1954105
Ruitong Wu, Kewen Li
ABSTRACT In this article, an adaptive event-triggered control scheme is first investigated for new type tyre systems based on vehicle. The intricate systems are transformed into a nonlinear model to research. The improved event-triggered mechanism (ETM) is proposed to enhance effectively the data transmission capacity of the systems and reduce the communication bandwidth. For the sake of conquering the problem of ‘explosion of complexity’ in traditional adaptive backstepping recursive design process, the dynamic surface control (DSC) technique is introduced in control design process. Based on the Lyapunov stability theory, the developed control scheme guarantees all the variables in the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB). Finally, the simulation results verify the rationality and effectiveness of the proposed control scheme.
{"title":"Adaptive event-triggered control for new type tyre systems based on vehicles","authors":"Ruitong Wu, Kewen Li","doi":"10.1080/21642583.2021.1954105","DOIUrl":"https://doi.org/10.1080/21642583.2021.1954105","url":null,"abstract":"ABSTRACT In this article, an adaptive event-triggered control scheme is first investigated for new type tyre systems based on vehicle. The intricate systems are transformed into a nonlinear model to research. The improved event-triggered mechanism (ETM) is proposed to enhance effectively the data transmission capacity of the systems and reduce the communication bandwidth. For the sake of conquering the problem of ‘explosion of complexity’ in traditional adaptive backstepping recursive design process, the dynamic surface control (DSC) technique is introduced in control design process. Based on the Lyapunov stability theory, the developed control scheme guarantees all the variables in the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB). Finally, the simulation results verify the rationality and effectiveness of the proposed control scheme.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/21642583.2021.1954105","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42696021","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 : 2021-07-11DOI: 10.1080/21642583.2021.1949403
Dongmei Wang
In this work, an adaptive control problem is investigated for the nonlinear active suspension systems (ASSs) with stochastic disturbances and time delay. Also, in the suspension system, the nonlinearity of the springs and the dampers are considered. In order to be closer to the actual system, the external random disturbances are not neglected in this paper. It is worth mentioning that unknown time-varying delay is considered in this study to facilitate the treatment of transmission time delay. Based on Lyapunov theory and backstepping technique, the presented adaptive controller is able to ensure that all the signals in close-loop system are uniformly ultimately bounded in probability. Finally, the simulation results further illustrate the effectiveness of the proposed approach.
{"title":"Adaptive control for the nonlinear suspension systems with stochastic disturbances and unknown time delay","authors":"Dongmei Wang","doi":"10.1080/21642583.2021.1949403","DOIUrl":"https://doi.org/10.1080/21642583.2021.1949403","url":null,"abstract":"In this work, an adaptive control problem is investigated for the nonlinear active suspension systems (ASSs) with stochastic disturbances and time delay. Also, in the suspension system, the nonlinearity of the springs and the dampers are considered. In order to be closer to the actual system, the external random disturbances are not neglected in this paper. It is worth mentioning that unknown time-varying delay is considered in this study to facilitate the treatment of transmission time delay. Based on Lyapunov theory and backstepping technique, the presented adaptive controller is able to ensure that all the signals in close-loop system are uniformly ultimately bounded in probability. Finally, the simulation results further illustrate the effectiveness of the proposed approach.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2021-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43506949","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 : 2021-05-03DOI: 10.1080/21642583.2020.1848657
Yuhao Zhu, Yongjin Yu, C. Xiao, Bo Wang
ABSTRACT In the SPMSM no-speed control system, the traditional SMC speed controlling led to a difference in adjustment speed, a large amount of overshoot and obvious chattering. In order to solve this problem, a new non-singular fast Terminal-SMC speed controller is designed and the continuous function υ(s) is used to replace the traditional symbolic function, which effectively improves the observation accuracy, and reduces the system chattering. The Lyapunov function is designed to prove the system’s stability. The simulation results show that the new NSFT-SMC has faster responded speed, stronger system robustness, and less chattering during stable operation. Comparing with traditional SMC speed control and hyperbolic tangent function SMC speed control, it has better control performance.
{"title":"SPMSM sensorless control of a new non-singular fast terminal sliding mode speed controller","authors":"Yuhao Zhu, Yongjin Yu, C. Xiao, Bo Wang","doi":"10.1080/21642583.2020.1848657","DOIUrl":"https://doi.org/10.1080/21642583.2020.1848657","url":null,"abstract":"ABSTRACT In the SPMSM no-speed control system, the traditional SMC speed controlling led to a difference in adjustment speed, a large amount of overshoot and obvious chattering. In order to solve this problem, a new non-singular fast Terminal-SMC speed controller is designed and the continuous function υ(s) is used to replace the traditional symbolic function, which effectively improves the observation accuracy, and reduces the system chattering. The Lyapunov function is designed to prove the system’s stability. The simulation results show that the new NSFT-SMC has faster responded speed, stronger system robustness, and less chattering during stable operation. Comparing with traditional SMC speed control and hyperbolic tangent function SMC speed control, it has better control performance.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2021-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/21642583.2020.1848657","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41649994","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 : 2021-05-03DOI: 10.1080/21642583.2020.1833787
Yuanyuan Xu, Bing Chen
This paper focuses on adaptive neural control for a class of non-strict feedback nonlinear systems with state delays and input delay. By combining integral transformation with adaptive neural control approach, a backstepping-based adaptive neural control scheme is proposed. The suggested control schemes guarantees that the tracking error converges to a small neighbourhood of the origin, meanwhile, all the closed-loop signals remain bounded. Simulation examples are used to verify the effectiveness of the proposed method.
{"title":"Adaptive neural network control for nonlinear non-strict feedback time-delay systems","authors":"Yuanyuan Xu, Bing Chen","doi":"10.1080/21642583.2020.1833787","DOIUrl":"https://doi.org/10.1080/21642583.2020.1833787","url":null,"abstract":"This paper focuses on adaptive neural control for a class of non-strict feedback nonlinear systems with state delays and input delay. By combining integral transformation with adaptive neural control approach, a backstepping-based adaptive neural control scheme is proposed. The suggested control schemes guarantees that the tracking error converges to a small neighbourhood of the origin, meanwhile, all the closed-loop signals remain bounded. Simulation examples are used to verify the effectiveness of the proposed method.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2021-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/21642583.2020.1833787","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42859855","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 : 2021-05-03DOI: 10.1080/21642583.2020.1833786
Yadong Li, Bing Chen
For a class of non-strict-feedback nonlinear systems with input delay and saturation, the tracking control problem is addressed in this paper. An auxiliary system is constructed to handle the difficulty in control design caused by input delay. Moreover, hyperbolic tangent function is used to approximate the non-smooth saturation function to achieve controller design. The unknown nonlinear functions generated in backstepping control design are approximated by radial basis function neural networks. And then, with the help of backstepping approach, an adaptive neural control scheme is proposed. It is proved by Lyapunov stability theory that the tracking errors converge to a small neighbourhood of the origin and the other closed-loop signals are bounded. At last, a simulation example is able to verify the validity of this tracking control scheme.
{"title":"Adaptive neural tracking control for a class of nonlinear systems with input delay and saturation","authors":"Yadong Li, Bing Chen","doi":"10.1080/21642583.2020.1833786","DOIUrl":"https://doi.org/10.1080/21642583.2020.1833786","url":null,"abstract":"For a class of non-strict-feedback nonlinear systems with input delay and saturation, the tracking control problem is addressed in this paper. An auxiliary system is constructed to handle the difficulty in control design caused by input delay. Moreover, hyperbolic tangent function is used to approximate the non-smooth saturation function to achieve controller design. The unknown nonlinear functions generated in backstepping control design are approximated by radial basis function neural networks. And then, with the help of backstepping approach, an adaptive neural control scheme is proposed. It is proved by Lyapunov stability theory that the tracking errors converge to a small neighbourhood of the origin and the other closed-loop signals are bounded. At last, a simulation example is able to verify the validity of this tracking control scheme.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2021-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/21642583.2020.1833786","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47625165","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 : 2021-05-03DOI: 10.1080/21642583.2020.1833788
Xinyi Sun, Hua Yang, Qi-Fang Liu, Yan-Hong Liu
In this paper, the event-triggered control for greenhouse temperature based on Computational Fluid Dynamics (CFD) is investigated. To overcome the deficiency of sensor which can only represent the temperature value of some points inside the greenhouse, CFD technology is used to simulate and output the temperature field data of the entire greenhouse. Furthermore, in order to reduce the network resource consumption, the event-triggered mechanism is adopted in CFD simulation output-controller channel. When the greenhouse temperature meets the event-triggered condition, the simulated data is transmitted to the controller. Moreover, multi-objective particle swarm optimization (MOPSO) is used to design the controller to solve the contradiction between energy consumption and control accuracy in the control process. Finally, a numerical simulation example is provided to illustrate the effectiveness of given event-triggered scheme for greenhouse temperature under natural ventilation based on CFD simulation. The simulation results show that the control scheme given in this paper can effectively regulate the greenhouse internal temperature and meet the control requirements.
{"title":"Event-triggered control for greenhouse temperature under natural ventilation based on computational fluid dynamics","authors":"Xinyi Sun, Hua Yang, Qi-Fang Liu, Yan-Hong Liu","doi":"10.1080/21642583.2020.1833788","DOIUrl":"https://doi.org/10.1080/21642583.2020.1833788","url":null,"abstract":"In this paper, the event-triggered control for greenhouse temperature based on Computational Fluid Dynamics (CFD) is investigated. To overcome the deficiency of sensor which can only represent the temperature value of some points inside the greenhouse, CFD technology is used to simulate and output the temperature field data of the entire greenhouse. Furthermore, in order to reduce the network resource consumption, the event-triggered mechanism is adopted in CFD simulation output-controller channel. When the greenhouse temperature meets the event-triggered condition, the simulated data is transmitted to the controller. Moreover, multi-objective particle swarm optimization (MOPSO) is used to design the controller to solve the contradiction between energy consumption and control accuracy in the control process. Finally, a numerical simulation example is provided to illustrate the effectiveness of given event-triggered scheme for greenhouse temperature under natural ventilation based on CFD simulation. The simulation results show that the control scheme given in this paper can effectively regulate the greenhouse internal temperature and meet the control requirements.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2021-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/21642583.2020.1833788","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44064015","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 : 2021-05-03DOI: 10.1080/21642583.2020.1833789
Jie Xu, Li Sheng, Ming Gao
This paper focuses on the fault estimation problem for a class of nonlinear systems with sensor gain degradation and stochastic protocol (SP) based on strong tracking filtering. The phenomenon of the sensor gain degradation is described by sequences of stochastic variables in a known interval. The stochastic protocol (SP) is used to deal with possible data conflicts in multi-signal transmission. The augmented system is constructed by combining the original system state vectors and the related faults into an augmented state vectors. The strong tracking filter (STF) is designed by introducing a fading factor into the filter structure to solve the problem of burst faults. Finally, a simulation example is given to verify the effectiveness and applicability of the proposed filter.
{"title":"Fault estimation for nonlinear systems with sensor gain degradation and stochastic protocol based on strong tracking filtering","authors":"Jie Xu, Li Sheng, Ming Gao","doi":"10.1080/21642583.2020.1833789","DOIUrl":"https://doi.org/10.1080/21642583.2020.1833789","url":null,"abstract":"This paper focuses on the fault estimation problem for a class of nonlinear systems with sensor gain degradation and stochastic protocol (SP) based on strong tracking filtering. The phenomenon of the sensor gain degradation is described by sequences of stochastic variables in a known interval. The stochastic protocol (SP) is used to deal with possible data conflicts in multi-signal transmission. The augmented system is constructed by combining the original system state vectors and the related faults into an augmented state vectors. The strong tracking filter (STF) is designed by introducing a fading factor into the filter structure to solve the problem of burst faults. Finally, a simulation example is given to verify the effectiveness and applicability of the proposed filter.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2021-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/21642583.2020.1833789","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45685861","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 : 2021-05-03DOI: 10.1080/21642583.2021.1872043
Meng Zhang, N. Zhong, Mingyuan Ma
Photovoltaic (PV) energy can be considered to be as highly efficient energy source since it is ecofriendly, harmless and available endlessly. In order to improve the output power of photovoltaic cells, the maximum power point tracking technology is used in PV systems. This paper designs a sliding mode controller based on SEPIC converter to implement MPPT. The difference from other methods is that the proposed method uses the circuit output voltage U 0 in the closed-loop system, so that the controller has better control effect. The buck-boost feature of the SEPIC widens the applicable PV voltage and thus increases the adopted PV module flexibility. First, the photovoltaic array is modeled and the simulation results are analyzed in this paper. Then model and analyze the SEPIC circuit and derive a sliding mode control strategy based on this circuit. Finally, the results obtained in MATLAB/Simulink were compared with the conventional P&O algorithm and INC algorithm. The results show that the sliding mode controller proposed in this paper has faster speed and less oscillation when tracking the maximum power point (MPP).
{"title":"Sliding mode control of SEPIC converter based photovoltaic system","authors":"Meng Zhang, N. Zhong, Mingyuan Ma","doi":"10.1080/21642583.2021.1872043","DOIUrl":"https://doi.org/10.1080/21642583.2021.1872043","url":null,"abstract":"Photovoltaic (PV) energy can be considered to be as highly efficient energy source since it is ecofriendly, harmless and available endlessly. In order to improve the output power of photovoltaic cells, the maximum power point tracking technology is used in PV systems. This paper designs a sliding mode controller based on SEPIC converter to implement MPPT. The difference from other methods is that the proposed method uses the circuit output voltage U 0 in the closed-loop system, so that the controller has better control effect. The buck-boost feature of the SEPIC widens the applicable PV voltage and thus increases the adopted PV module flexibility. First, the photovoltaic array is modeled and the simulation results are analyzed in this paper. Then model and analyze the SEPIC circuit and derive a sliding mode control strategy based on this circuit. Finally, the results obtained in MATLAB/Simulink were compared with the conventional P&O algorithm and INC algorithm. The results show that the sliding mode controller proposed in this paper has faster speed and less oscillation when tracking the maximum power point (MPP).","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2021-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/21642583.2021.1872043","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47902901","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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