Pub Date : 2021-06-29DOI: 10.23919/ecc54610.2021.9654926
Rima Saadaoui, G. I. Bara, Hassan Omran, O. Piccin, E. Laroche
This paper presents the modeling and control of a flexible cable-driven parallel robot, taking into account the flexibility of the cables. The model is obtained based on the Lagrangian method and the assumed modes approach. Considering three cables, this model has been formulated using differential-algebraic equations and then transformed into an ordinary differential equations representation. Based on the linearization of the ODE representation along the center of the work-space, an ${mathcal{H}_infty }$ controller guaranteeing disturbance rejection and reference tracking has been synthesized. A reduced-order version of this controller has been also obtained. Our simulation results performed with the non-linear model show the good performance of the closed-loop system. A comparison between the reduced-order ${mathcal{H}_infty }$ controller and a PD controller taken from the literature has also been provided.
{"title":"H∞ Synthesis for a Planar Flexible Cable-Driven Robot","authors":"Rima Saadaoui, G. I. Bara, Hassan Omran, O. Piccin, E. Laroche","doi":"10.23919/ecc54610.2021.9654926","DOIUrl":"https://doi.org/10.23919/ecc54610.2021.9654926","url":null,"abstract":"This paper presents the modeling and control of a flexible cable-driven parallel robot, taking into account the flexibility of the cables. The model is obtained based on the Lagrangian method and the assumed modes approach. Considering three cables, this model has been formulated using differential-algebraic equations and then transformed into an ordinary differential equations representation. Based on the linearization of the ODE representation along the center of the work-space, an ${mathcal{H}_infty }$ controller guaranteeing disturbance rejection and reference tracking has been synthesized. A reduced-order version of this controller has been also obtained. Our simulation results performed with the non-linear model show the good performance of the closed-loop system. A comparison between the reduced-order ${mathcal{H}_infty }$ controller and a PD controller taken from the literature has also been provided.","PeriodicalId":105499,"journal":{"name":"2021 European Control Conference (ECC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115740395","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 : 2021-06-29DOI: 10.23919/ecc54610.2021.9655102
Alessandra Duz, M. Corno, S. Savaresi
Vehicle occupants head movements respond to the vehicle motion and have a significant impact on comfort. An accurate knowledge of these dynamics is thus important for planning the motion of autonomous vehicles. This paper focuses on the analysis and modeling of the head tilting movement caused by braking and acceleration. After discussing the differences between the driver and passenger’s head movements, we propose two dynamic models that captures these dynamics: a Wiener model and a Neural Network one. We identify and validate these models on data collected on an instrumented car showing that both can capture the movements caused by the longitudinal acceleration.
{"title":"Analysis and Identification of a Vehicle Occupant’s Head Position Dynamic Response to Longitudinal Acceleration","authors":"Alessandra Duz, M. Corno, S. Savaresi","doi":"10.23919/ecc54610.2021.9655102","DOIUrl":"https://doi.org/10.23919/ecc54610.2021.9655102","url":null,"abstract":"Vehicle occupants head movements respond to the vehicle motion and have a significant impact on comfort. An accurate knowledge of these dynamics is thus important for planning the motion of autonomous vehicles. This paper focuses on the analysis and modeling of the head tilting movement caused by braking and acceleration. After discussing the differences between the driver and passenger’s head movements, we propose two dynamic models that captures these dynamics: a Wiener model and a Neural Network one. We identify and validate these models on data collected on an instrumented car showing that both can capture the movements caused by the longitudinal acceleration.","PeriodicalId":105499,"journal":{"name":"2021 European Control Conference (ECC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115910528","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 : 2021-06-29DOI: 10.23919/ecc54610.2021.9655184
Federico Vesentini, Riccardo Muradore
Velocity Obstacle paradigm is one of the most popular and studied decentralized trajectory planning methods for multi-agent systems moving in dynamic environments. It has been successfully used in a multitude of real and simulated scenarios for the collision-free maneuver of ground or aerial mobile robots. In this paper we address the problem of adapting Velocity Obstacles to provide collision-free trajectories also for robotic manipulators with dynamic obstacles in their workspace. Simulation results show the effectiveness of the proposed approach.
{"title":"Velocity Obstacle-based Trajectory Planner for Two-Link Planar Manipulators","authors":"Federico Vesentini, Riccardo Muradore","doi":"10.23919/ecc54610.2021.9655184","DOIUrl":"https://doi.org/10.23919/ecc54610.2021.9655184","url":null,"abstract":"Velocity Obstacle paradigm is one of the most popular and studied decentralized trajectory planning methods for multi-agent systems moving in dynamic environments. It has been successfully used in a multitude of real and simulated scenarios for the collision-free maneuver of ground or aerial mobile robots. In this paper we address the problem of adapting Velocity Obstacles to provide collision-free trajectories also for robotic manipulators with dynamic obstacles in their workspace. Simulation results show the effectiveness of the proposed approach.","PeriodicalId":105499,"journal":{"name":"2021 European Control Conference (ECC)","volume":"295 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124273621","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 : 2021-06-29DOI: 10.23919/ecc54610.2021.9655204
J. M. Nadales, J. M. Manzano, A. Barriga, D. Limón
The implementation of nonlinear model predictive controllers for systems operating at high frequencies constitutes a significant challenge, mainly because of the complexity and time consumption of the optimization problem involved. An alternative that has been proposed is the employment of data-driven techniques to offline learn the control law, and then to implement it on a target embedded platform. Following this trend, in this paper we propose the implementation of predictive controllers on FPGA platforms making use of a parallel version of the machine learning technique known as Lipschitz interpolation. By doing this, computation time can be enormously accelerated. The results are compared to those obtained when the sequential algorithm runs on standard CPU platforms, and when the system is controlled by solving the optimization problem online, in terms of the error made and computing time. This method is validated in a case study where the nonlinear model predictive controller is employed to control a self-balancing two-wheel robot.
{"title":"Implementation of Fast Predictive Controllers on FPGA Platforms based on Parallel Lipschitz Interpolation","authors":"J. M. Nadales, J. M. Manzano, A. Barriga, D. Limón","doi":"10.23919/ecc54610.2021.9655204","DOIUrl":"https://doi.org/10.23919/ecc54610.2021.9655204","url":null,"abstract":"The implementation of nonlinear model predictive controllers for systems operating at high frequencies constitutes a significant challenge, mainly because of the complexity and time consumption of the optimization problem involved. An alternative that has been proposed is the employment of data-driven techniques to offline learn the control law, and then to implement it on a target embedded platform. Following this trend, in this paper we propose the implementation of predictive controllers on FPGA platforms making use of a parallel version of the machine learning technique known as Lipschitz interpolation. By doing this, computation time can be enormously accelerated. The results are compared to those obtained when the sequential algorithm runs on standard CPU platforms, and when the system is controlled by solving the optimization problem online, in terms of the error made and computing time. This method is validated in a case study where the nonlinear model predictive controller is employed to control a self-balancing two-wheel robot.","PeriodicalId":105499,"journal":{"name":"2021 European Control Conference (ECC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114352335","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 : 2021-06-29DOI: 10.23919/ecc54610.2021.9654909
Zonglin Liu, O. Stursberg
This paper introduces a distributed control strategy for constraint-coupled networked systems with nonlinear dynamics. Problems of this type are often too complicated to be solved in a centralized way, such that efficient distributed solution is required. The proposed method first casts the global problem into a mixed-integer programming (MIP) problem, and then solves the MIP problem by use of recently developed distributed solution schemes for this problem class. A reduction of the computational complexity compared to the centralized solution as well as the satisfaction of all constraints are guaranteed, and its efficiency is illustrated for a numeric example.
{"title":"Distributed Control of Networked Systems with Nonlinear Dynamics and Coupling Constraints","authors":"Zonglin Liu, O. Stursberg","doi":"10.23919/ecc54610.2021.9654909","DOIUrl":"https://doi.org/10.23919/ecc54610.2021.9654909","url":null,"abstract":"This paper introduces a distributed control strategy for constraint-coupled networked systems with nonlinear dynamics. Problems of this type are often too complicated to be solved in a centralized way, such that efficient distributed solution is required. The proposed method first casts the global problem into a mixed-integer programming (MIP) problem, and then solves the MIP problem by use of recently developed distributed solution schemes for this problem class. A reduction of the computational complexity compared to the centralized solution as well as the satisfaction of all constraints are guaranteed, and its efficiency is illustrated for a numeric example.","PeriodicalId":105499,"journal":{"name":"2021 European Control Conference (ECC)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114872651","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 : 2021-06-29DOI: 10.23919/ECC54610.2021.9655183
Martin Kosch, Ahmed Elkhashap, Philipp Koschorrek, R. Zweigel, D. Abel
The automation of ships offers great potential in terms of safety and efficiency. For this reason, the research project AKOON investigates the automation of an overactuated river ferry. This task requires the development of advanced control algorithms that can safely track a roughly planned trajectory in spite of obstacles nearby, external disturbances, and limited propulsion forces. This paper presents a new control concept specifically designed for the automation of the overactuated river ferry. Since usual control approaches such as feedback linearization or linear model predictive control are not suited for the consideration of most real obstacles, a nonlinear model predictive control using a multiple shooting strategy is proposed. In addition, a disturbance observer is presented that utilizes a customized dynamic model of the examined ferry. The control concept is implemented on an industrial controller that is examined in a hardware-in-the-loop test bench resembling a real-world configuration. During the river crossing, a maximum horizontal tracking error of less than 5 m and a maximum yaw angle error of less than 10° are desired whenever the reference trajectory is feasible. It is shown by means of an exemplary simulation scenario that the proposed control concept enables a collision-free trajectory tracking and that the specified maximum errors are not exceeded.
{"title":"Hardware-in-the-Loop Trajectory Tracking and Collision Avoidance of Automated Inland Vessels Using Model Predictive Control*","authors":"Martin Kosch, Ahmed Elkhashap, Philipp Koschorrek, R. Zweigel, D. Abel","doi":"10.23919/ECC54610.2021.9655183","DOIUrl":"https://doi.org/10.23919/ECC54610.2021.9655183","url":null,"abstract":"The automation of ships offers great potential in terms of safety and efficiency. For this reason, the research project AKOON investigates the automation of an overactuated river ferry. This task requires the development of advanced control algorithms that can safely track a roughly planned trajectory in spite of obstacles nearby, external disturbances, and limited propulsion forces. This paper presents a new control concept specifically designed for the automation of the overactuated river ferry. Since usual control approaches such as feedback linearization or linear model predictive control are not suited for the consideration of most real obstacles, a nonlinear model predictive control using a multiple shooting strategy is proposed. In addition, a disturbance observer is presented that utilizes a customized dynamic model of the examined ferry. The control concept is implemented on an industrial controller that is examined in a hardware-in-the-loop test bench resembling a real-world configuration. During the river crossing, a maximum horizontal tracking error of less than 5 m and a maximum yaw angle error of less than 10° are desired whenever the reference trajectory is feasible. It is shown by means of an exemplary simulation scenario that the proposed control concept enables a collision-free trajectory tracking and that the specified maximum errors are not exceeded.","PeriodicalId":105499,"journal":{"name":"2021 European Control Conference (ECC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116902885","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 : 2021-06-29DOI: 10.23919/ecc54610.2021.9654994
S. Alavi, N. Hudon
This paper considers the problem of dynamic output feedback controller design for the stabilization of systems described by the combination of a structured component, a generalized Hamiltonian system, and an unstructured dynamical component. First, a nonlinear Luenberger observer is designed for unmeasured state estimation. Then, using Lyapunov stability, a dynamic stabilizing feedback controller is designed. Asymptotic stability of the overall system in closed-loop is proven for systems centered at the origin and at an arbitrary output. Finally, application of the proposed approach is illustrated through numerical studies of a nonlinear chemical reactor system.
{"title":"Observer and dynamic feedback stabilizing control design for generalized Hamiltonian systems with unstructured dynamics","authors":"S. Alavi, N. Hudon","doi":"10.23919/ecc54610.2021.9654994","DOIUrl":"https://doi.org/10.23919/ecc54610.2021.9654994","url":null,"abstract":"This paper considers the problem of dynamic output feedback controller design for the stabilization of systems described by the combination of a structured component, a generalized Hamiltonian system, and an unstructured dynamical component. First, a nonlinear Luenberger observer is designed for unmeasured state estimation. Then, using Lyapunov stability, a dynamic stabilizing feedback controller is designed. Asymptotic stability of the overall system in closed-loop is proven for systems centered at the origin and at an arbitrary output. Finally, application of the proposed approach is illustrated through numerical studies of a nonlinear chemical reactor system.","PeriodicalId":105499,"journal":{"name":"2021 European Control Conference (ECC)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117229504","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 : 2021-06-29DOI: 10.23919/ecc54610.2021.9654897
M. Corno, Stefano Dattilo, S. Savaresi
This paper presents a driveline active damping strategy for electric vehicles. We first propose a black-box identification of the main oscillation modes of a transmission of a 4 Wheel Driven electric vehicle. We identify the models in a variety of conditions. We then design the active damping control using ${mathcal{H}_infty }$ considerations on the identified models. Extensive experimental validation shows that the active damping reduces of 24% the longitudinal jerk during sharp acceleration maneuvers without negatively affecting the longitudinal acceleration. Furthermore, we test the controller under a variety of condition to assess its robustness with respect to transmission load variations, friction changes and velocity.
提出了一种电动汽车传动系统主动阻尼策略。我们首先提出了一种4轮驱动电动汽车变速器主要振动模式的黑盒识别方法。我们在各种条件下识别模型。然后，我们在识别的模型上使用${mathcal{H}_infty }$考虑因素设计主动阻尼控制。大量的实验验证表明，主动阻尼降低了24％% the longitudinal jerk during sharp acceleration maneuvers without negatively affecting the longitudinal acceleration. Furthermore, we test the controller under a variety of condition to assess its robustness with respect to transmission load variations, friction changes and velocity.
{"title":"Black-Box Model-Based Active Damping of Driveline Oscillations","authors":"M. Corno, Stefano Dattilo, S. Savaresi","doi":"10.23919/ecc54610.2021.9654897","DOIUrl":"https://doi.org/10.23919/ecc54610.2021.9654897","url":null,"abstract":"This paper presents a driveline active damping strategy for electric vehicles. We first propose a black-box identification of the main oscillation modes of a transmission of a 4 Wheel Driven electric vehicle. We identify the models in a variety of conditions. We then design the active damping control using ${mathcal{H}_infty }$ considerations on the identified models. Extensive experimental validation shows that the active damping reduces of 24% the longitudinal jerk during sharp acceleration maneuvers without negatively affecting the longitudinal acceleration. Furthermore, we test the controller under a variety of condition to assess its robustness with respect to transmission load variations, friction changes and velocity.","PeriodicalId":105499,"journal":{"name":"2021 European Control Conference (ECC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128505115","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 : 2021-06-29DOI: 10.23919/ecc54610.2021.9655086
M. Bolognini, L. Fagiano
Multicopter drones equipped with cameras can perform rapid inspections of large buildings, including those with hard to reach features, like bridge pylons. Drones can be made autonomous by providing them with a method to choose a path that maximizes the collected information during the limited flight time allowed by the battery. It is therefore crucial to optimize the trajectories to minimize inspection time. The problem of finding an approximately optimal path passing through a series of desired inspection points in a three-dimensional environment with obstacles is considered. A hierarchical approach is proposed, where the space containing the inspection points is partitioned into different regions and multiple instances of the TSP (Travelling Salesman Problem) are solved, decreasing the overall complexity. An extended graph is used in the TSP, in order to tackle the problem of collision avoidance while planning the trajectory between point pairs. This approach leads to an efficient and scalable method capable of avoiding obstacles, and significantly reduces the time needed to find an optimal path with respect to non-hierarchical methods. Simulation results highlight these features.
{"title":"A Scalable Hierarchical Path Planning technique for Autonomous Inspections with multicopter drones","authors":"M. Bolognini, L. Fagiano","doi":"10.23919/ecc54610.2021.9655086","DOIUrl":"https://doi.org/10.23919/ecc54610.2021.9655086","url":null,"abstract":"Multicopter drones equipped with cameras can perform rapid inspections of large buildings, including those with hard to reach features, like bridge pylons. Drones can be made autonomous by providing them with a method to choose a path that maximizes the collected information during the limited flight time allowed by the battery. It is therefore crucial to optimize the trajectories to minimize inspection time. The problem of finding an approximately optimal path passing through a series of desired inspection points in a three-dimensional environment with obstacles is considered. A hierarchical approach is proposed, where the space containing the inspection points is partitioned into different regions and multiple instances of the TSP (Travelling Salesman Problem) are solved, decreasing the overall complexity. An extended graph is used in the TSP, in order to tackle the problem of collision avoidance while planning the trajectory between point pairs. This approach leads to an efficient and scalable method capable of avoiding obstacles, and significantly reduces the time needed to find an optimal path with respect to non-hierarchical methods. Simulation results highlight these features.","PeriodicalId":105499,"journal":{"name":"2021 European Control Conference (ECC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129614408","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 : 2021-06-29DOI: 10.23919/ecc54610.2021.9654856
Francesco Vitale, C. Roncoli
We present a reference tracking control problem with obstacle avoidance for connected and automated vehicles. The proposed approach allows to deal with obstacles in the control loop in the first instance, coping with real-time operations while safely waiting for an eventually new planned trajectory from the guidance loop. An obstacle avoidance algorithm is designed to produce suitable constraints for an optimization control problem to be solved via Nonlinear Model Predictive Control. Such an algorithm is based on task priority management, so that the reference tracking task is handled as a lower priority task with respect to the obstacle avoidance task. Automated vehicles are managed in a decentralized fashion, so that they can process independently any sensed potential obstacles, including conventional vehicles. In the presence of vehicle connectivity, vehicles may exchange information about their states to make decisions based on more accurate predictions. The proposed method is evaluated via simulation experiments, for a set of scenarios in the context of urban traffic.
{"title":"An MPC-based Task Priority Management Approach for Connected and Automated Vehicles Reference Tracking with Obstacle Avoidance*","authors":"Francesco Vitale, C. Roncoli","doi":"10.23919/ecc54610.2021.9654856","DOIUrl":"https://doi.org/10.23919/ecc54610.2021.9654856","url":null,"abstract":"We present a reference tracking control problem with obstacle avoidance for connected and automated vehicles. The proposed approach allows to deal with obstacles in the control loop in the first instance, coping with real-time operations while safely waiting for an eventually new planned trajectory from the guidance loop. An obstacle avoidance algorithm is designed to produce suitable constraints for an optimization control problem to be solved via Nonlinear Model Predictive Control. Such an algorithm is based on task priority management, so that the reference tracking task is handled as a lower priority task with respect to the obstacle avoidance task. Automated vehicles are managed in a decentralized fashion, so that they can process independently any sensed potential obstacles, including conventional vehicles. In the presence of vehicle connectivity, vehicles may exchange information about their states to make decisions based on more accurate predictions. The proposed method is evaluated via simulation experiments, for a set of scenarios in the context of urban traffic.","PeriodicalId":105499,"journal":{"name":"2021 European Control Conference (ECC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132897871","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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