Pub Date : 2014-12-11DOI: 10.1109/CCA.2014.6981439
P. Cruz, R. Fierro
In this paper, we address the problem of lifting from the ground a cable-suspended load by a quadrotor aerial vehicle. Furthermore, we consider that the mass of the load is unknown. The lift maneuver is a critical step before proceeding with the transportation of a given cargo. However, it has received little attention in the literature so far. To deal with this problem, we break down the lift maneuver into simpler modes which represent the dynamics of the quadrotor-load system at particular operating regimes. From this decomposition, we obtain a series of waypoints that the aerial vehicle has to reach to accomplish the task. We combine geometric control with a least-squares estimation method to design an adaptive controller that follows a prescribed trajectory planned based on the waypoints. The effectiveness of the proposed control scheme is demonstrated by numerical simulations.
{"title":"Autonomous lift of a cable-suspended load by an unmanned aerial robot","authors":"P. Cruz, R. Fierro","doi":"10.1109/CCA.2014.6981439","DOIUrl":"https://doi.org/10.1109/CCA.2014.6981439","url":null,"abstract":"In this paper, we address the problem of lifting from the ground a cable-suspended load by a quadrotor aerial vehicle. Furthermore, we consider that the mass of the load is unknown. The lift maneuver is a critical step before proceeding with the transportation of a given cargo. However, it has received little attention in the literature so far. To deal with this problem, we break down the lift maneuver into simpler modes which represent the dynamics of the quadrotor-load system at particular operating regimes. From this decomposition, we obtain a series of waypoints that the aerial vehicle has to reach to accomplish the task. We combine geometric control with a least-squares estimation method to design an adaptive controller that follows a prescribed trajectory planned based on the waypoints. The effectiveness of the proposed control scheme is demonstrated by numerical simulations.","PeriodicalId":205599,"journal":{"name":"2014 IEEE Conference on Control Applications (CCA)","volume":"271 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122468597","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 : 2014-12-11DOI: 10.1109/CCA.2014.6981359
Cecilia Cvetanovic, E. Laroche
Models obtained from the laws of Physics are naturally written as differential-algebraic equations (DAE) also known as descriptor models. However, the usual methodology in control consists in reducing the model to a set of ordinary equations. Remaining in the DAE word has several advantages: the reduction step is not necessary any more and the parameter dependance might be simplified. This paper is a step forward towards a control methodology that would be entirely based on DAE models. Its goal is twofold. First, the tools and methods available for DAE models are reviewed. Second, a case taken form robotics is considered. The simulation being done with Maple, a linear model is derived and transferred to Matlab for synthesis. A H∞ controller is then synthesized and evaluated. The controlled system is then simulated with Maple.
{"title":"Towards DAE methodology for the control of cable-driven parallel robots","authors":"Cecilia Cvetanovic, E. Laroche","doi":"10.1109/CCA.2014.6981359","DOIUrl":"https://doi.org/10.1109/CCA.2014.6981359","url":null,"abstract":"Models obtained from the laws of Physics are naturally written as differential-algebraic equations (DAE) also known as descriptor models. However, the usual methodology in control consists in reducing the model to a set of ordinary equations. Remaining in the DAE word has several advantages: the reduction step is not necessary any more and the parameter dependance might be simplified. This paper is a step forward towards a control methodology that would be entirely based on DAE models. Its goal is twofold. First, the tools and methods available for DAE models are reviewed. Second, a case taken form robotics is considered. The simulation being done with Maple, a linear model is derived and transferred to Matlab for synthesis. A H∞ controller is then synthesized and evaluated. The controlled system is then simulated with Maple.","PeriodicalId":205599,"journal":{"name":"2014 IEEE Conference on Control Applications (CCA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122598342","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 : 2014-12-11DOI: 10.1109/CCA.2014.6981588
A. Beghi, L. Cecchinato, Marco Lissandrin, M. Rampazzo
Centrifugal chillers, using variable-speed turbo compressors with magnetic bearings, are becoming very common in Heating, Ventilation and Air Conditioning (HVAC) systems. Such solution guarantees superior energy efficiency, mostly under part load conditions, compared with traditional equipments, and it provides additional advantages such as light weight and a compact package. On the other hand, turbo machinery adds its own complexity to the whole HVAC system and its efficient management is a non-trivial task. In this paper a hybrid optimisation technique is employed to determine optimal operation, under various working conditions, for air-condensed water centrifugal chillers. The proposed method provides optimal solutions using a combination of two algorithms: A random population-based optimiser, the Gravitational Search Algorithm (GSA), followed by the deterministic Levenberg-Marquardt (LM) algorithm. The hybrid method effectively overcomes the problem of high sensitivity to initial conditions of LM technique and a shortcoming of GSA which reduces its searching efficiency when close to the optimum. The hybrid method has been tested in a Matlab®-based simulation environment where the performance of an air-condensed centrifugal chiller is adequately evaluated. Simulation results guarantee high energy efficiency in a wide range of chiller working conditions.
{"title":"Oil-free centrifugal chiller optimal operation","authors":"A. Beghi, L. Cecchinato, Marco Lissandrin, M. Rampazzo","doi":"10.1109/CCA.2014.6981588","DOIUrl":"https://doi.org/10.1109/CCA.2014.6981588","url":null,"abstract":"Centrifugal chillers, using variable-speed turbo compressors with magnetic bearings, are becoming very common in Heating, Ventilation and Air Conditioning (HVAC) systems. Such solution guarantees superior energy efficiency, mostly under part load conditions, compared with traditional equipments, and it provides additional advantages such as light weight and a compact package. On the other hand, turbo machinery adds its own complexity to the whole HVAC system and its efficient management is a non-trivial task. In this paper a hybrid optimisation technique is employed to determine optimal operation, under various working conditions, for air-condensed water centrifugal chillers. The proposed method provides optimal solutions using a combination of two algorithms: A random population-based optimiser, the Gravitational Search Algorithm (GSA), followed by the deterministic Levenberg-Marquardt (LM) algorithm. The hybrid method effectively overcomes the problem of high sensitivity to initial conditions of LM technique and a shortcoming of GSA which reduces its searching efficiency when close to the optimum. The hybrid method has been tested in a Matlab®-based simulation environment where the performance of an air-condensed centrifugal chiller is adequately evaluated. Simulation results guarantee high energy efficiency in a wide range of chiller working conditions.","PeriodicalId":205599,"journal":{"name":"2014 IEEE Conference on Control Applications (CCA)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122751992","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 : 2014-12-11DOI: 10.1109/CCA.2014.6981598
Emrah Bıyık, Sahika Genc, James D. Brooks
The peak kW of a typical New York State office building is thought to primarily be a function of the HVAC system, often the buildings largest load, but may also be influenced by occupancy and other loads. First, a simple lumped parameter model with a minimum amount of building's physical input data, and trained with actual thermal and electrical data, is considered to approximate the thermal/electric consumption performance of the building and HVAC system on a zonal basis. Then, the lumped parameter model integrated with a dynamic human comfort model is used to develop optimized zonal thermostat setpoint schedules to minimize the cooling systems contribution to the buildings peak power load while maintaining human comfort at a desired level. A 24-hour weather and occupancy forecasts are also incorporated into the optimization algorithm. The key difference of our approach compared to previous approaches that utilize model-predictive control is that a minimal set of measurement profiles are utilized to reduce the installation cost resulting in a cost effective advanced controls solution for a large number of small and medium size office buildings. The model predictive optimization approach is implemented at multiple demonstration sites. The hardware architecture and software platform installed at one of the demonstration buildings are discussed. Finally, it is demonstrated that the proposed controller can effectively minimize peak cooling load on the HVAC equipment while achieving a satisfactory thermal comfort inside the building.
{"title":"Model predictive building thermostatic controls of small-to-medium commercial buildings for optimal peak load reduction incorporating dynamic human comfort models: Algorithm and implementation","authors":"Emrah Bıyık, Sahika Genc, James D. Brooks","doi":"10.1109/CCA.2014.6981598","DOIUrl":"https://doi.org/10.1109/CCA.2014.6981598","url":null,"abstract":"The peak kW of a typical New York State office building is thought to primarily be a function of the HVAC system, often the buildings largest load, but may also be influenced by occupancy and other loads. First, a simple lumped parameter model with a minimum amount of building's physical input data, and trained with actual thermal and electrical data, is considered to approximate the thermal/electric consumption performance of the building and HVAC system on a zonal basis. Then, the lumped parameter model integrated with a dynamic human comfort model is used to develop optimized zonal thermostat setpoint schedules to minimize the cooling systems contribution to the buildings peak power load while maintaining human comfort at a desired level. A 24-hour weather and occupancy forecasts are also incorporated into the optimization algorithm. The key difference of our approach compared to previous approaches that utilize model-predictive control is that a minimal set of measurement profiles are utilized to reduce the installation cost resulting in a cost effective advanced controls solution for a large number of small and medium size office buildings. The model predictive optimization approach is implemented at multiple demonstration sites. The hardware architecture and software platform installed at one of the demonstration buildings are discussed. Finally, it is demonstrated that the proposed controller can effectively minimize peak cooling load on the HVAC equipment while achieving a satisfactory thermal comfort inside the building.","PeriodicalId":205599,"journal":{"name":"2014 IEEE Conference on Control Applications (CCA)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133242987","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 : 2014-12-11DOI: 10.1109/CCA.2014.6981340
Z. Yakoub, M. Amairi, M. Chetoui, M. Aoun
This paper deals with continuous-time fractional closed-loop system identification in a noisy output context. A bias correction method called the bias-eliminated least squares is extended for indirect approach identification of closed-loop system with fractional models. This method is based on the least squares method combined with the state variable filter and assumes that the regulator order can not be lower than the process order. The performances of the proposed method are assessed through a numerical example.
{"title":"A bias-eliminated least squares method for continuous-time fractional closed-loop system identification","authors":"Z. Yakoub, M. Amairi, M. Chetoui, M. Aoun","doi":"10.1109/CCA.2014.6981340","DOIUrl":"https://doi.org/10.1109/CCA.2014.6981340","url":null,"abstract":"This paper deals with continuous-time fractional closed-loop system identification in a noisy output context. A bias correction method called the bias-eliminated least squares is extended for indirect approach identification of closed-loop system with fractional models. This method is based on the least squares method combined with the state variable filter and assumes that the regulator order can not be lower than the process order. The performances of the proposed method are assessed through a numerical example.","PeriodicalId":205599,"journal":{"name":"2014 IEEE Conference on Control Applications (CCA)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133244292","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 : 2014-12-11DOI: 10.1109/CCA.2014.6981408
Tim Schwickart, H. Voos, M. Darouach
This paper presents a novel energy-efficient model-predictive cruise control formulation for electric vehicles. The controller and the underlying dynamic model are designed to meet the properties of a series-production electric vehicle whose characteristics are identified by measurements. A predictive eco-cruise controller involves the minimisation of a compromise between terms related to driving speed and energy consumption which are in general both described by nonlinear differential equations. In this work, a coordinate transformation is used which leads to a linear differential motion equation without loss of information. The energy consumption map is approximated by the maximum of a set of linear functions which is implicitly determined in the optimisation problem. The reformulations finally lead to a model-predictive control approach with quadratic cost function, linear prediction model and linear constraints that corresponds to a piecewise linear system behaviour and allows a fast real-time implementation with guaranteed convergence. Simulation results of the MPC controller in closed-loop operation finally show the effectiveness of the approach.
{"title":"A real-time implementable model-predictive cruise controller for electric vehicles and energy-efficient driving","authors":"Tim Schwickart, H. Voos, M. Darouach","doi":"10.1109/CCA.2014.6981408","DOIUrl":"https://doi.org/10.1109/CCA.2014.6981408","url":null,"abstract":"This paper presents a novel energy-efficient model-predictive cruise control formulation for electric vehicles. The controller and the underlying dynamic model are designed to meet the properties of a series-production electric vehicle whose characteristics are identified by measurements. A predictive eco-cruise controller involves the minimisation of a compromise between terms related to driving speed and energy consumption which are in general both described by nonlinear differential equations. In this work, a coordinate transformation is used which leads to a linear differential motion equation without loss of information. The energy consumption map is approximated by the maximum of a set of linear functions which is implicitly determined in the optimisation problem. The reformulations finally lead to a model-predictive control approach with quadratic cost function, linear prediction model and linear constraints that corresponds to a piecewise linear system behaviour and allows a fast real-time implementation with guaranteed convergence. Simulation results of the MPC controller in closed-loop operation finally show the effectiveness of the approach.","PeriodicalId":205599,"journal":{"name":"2014 IEEE Conference on Control Applications (CCA)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132336521","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 : 2014-12-11DOI: 10.1109/CCA.2014.6981472
F. Azar, M. Perrier
This paper introduces a new method for slope seeking control of the model-independent nonlinear continuous static scalar and unconstrained systems. The proposed controller is the generalization of a global optimization scheme based on multi-unit extremum seeking control that drives the estimated gradient to an arbitrary slope. Herein, a monotonically decreasing offset is introduced between the inputs of two identical units and the estimated gradient by finite difference is controlled to a commanded slope of the nonlinear map by means of an integrator. The algorithm is applied to an illustrative simulation to demonstrate the successful capability of the proposed slope seeking feedback control.
{"title":"Slope seeking control using multi-units","authors":"F. Azar, M. Perrier","doi":"10.1109/CCA.2014.6981472","DOIUrl":"https://doi.org/10.1109/CCA.2014.6981472","url":null,"abstract":"This paper introduces a new method for slope seeking control of the model-independent nonlinear continuous static scalar and unconstrained systems. The proposed controller is the generalization of a global optimization scheme based on multi-unit extremum seeking control that drives the estimated gradient to an arbitrary slope. Herein, a monotonically decreasing offset is introduced between the inputs of two identical units and the estimated gradient by finite difference is controlled to a commanded slope of the nonlinear map by means of an integrator. The algorithm is applied to an illustrative simulation to demonstrate the successful capability of the proposed slope seeking feedback control.","PeriodicalId":205599,"journal":{"name":"2014 IEEE Conference on Control Applications (CCA)","volume":"72 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134504588","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 : 2014-12-11DOI: 10.1109/CCA.2014.6981425
A. Muñoz‐Vázquez, Vicente Parra‐Vega, A. Sánchez‐Orta, O. García, Carlos Izaguirre
The model-free sliding mode control based on fractional order sliding surface is built upon: i) An absolutely continuous control structure that does not require the exact dynamic model to induce a fractional sliding motion in finite time, and ii) A methodology to design fractional references with a clear counterpart in the frequency domain is proposed. This in order to improve the system response, in particular the transient period, and to generate a high-performance during the sliding motion. Numerical simulations support the proposal and illustrates the closed-loop system, which provides a better insight of the proposed scheme.
{"title":"Attitude tracking control of a quadrotor based on absolutely continuous fractional integral sliding modes","authors":"A. Muñoz‐Vázquez, Vicente Parra‐Vega, A. Sánchez‐Orta, O. García, Carlos Izaguirre","doi":"10.1109/CCA.2014.6981425","DOIUrl":"https://doi.org/10.1109/CCA.2014.6981425","url":null,"abstract":"The model-free sliding mode control based on fractional order sliding surface is built upon: i) An absolutely continuous control structure that does not require the exact dynamic model to induce a fractional sliding motion in finite time, and ii) A methodology to design fractional references with a clear counterpart in the frequency domain is proposed. This in order to improve the system response, in particular the transient period, and to generate a high-performance during the sliding motion. Numerical simulations support the proposal and illustrates the closed-loop system, which provides a better insight of the proposed scheme.","PeriodicalId":205599,"journal":{"name":"2014 IEEE Conference on Control Applications (CCA)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125171346","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 : 2014-12-11DOI: 10.1109/CCA.2014.6981457
I. Furtat, E. Tupichin
The paper describes the robust algorithm for nonlinear SISO plants under parametric uncertainties and external disturbances. Unlike other known results it is shown that in the control system only one filter of dimension n is used, where n is a dynamical order of a plant. Calculation derivatives of stabilizing control signals are realized by first order observers. It allows simplifying the analytical calculation of the control system. Algorithm provides compensation of parametric uncertainties and external disturbances with required accuracy. Simulations are illustrated an efficiency of proposed scheme for an unstable nonlinear plant and control of a magnetic levitation system.
{"title":"Control of nonlinear plant based on modified robust backstepping algorithm","authors":"I. Furtat, E. Tupichin","doi":"10.1109/CCA.2014.6981457","DOIUrl":"https://doi.org/10.1109/CCA.2014.6981457","url":null,"abstract":"The paper describes the robust algorithm for nonlinear SISO plants under parametric uncertainties and external disturbances. Unlike other known results it is shown that in the control system only one filter of dimension n is used, where n is a dynamical order of a plant. Calculation derivatives of stabilizing control signals are realized by first order observers. It allows simplifying the analytical calculation of the control system. Algorithm provides compensation of parametric uncertainties and external disturbances with required accuracy. Simulations are illustrated an efficiency of proposed scheme for an unstable nonlinear plant and control of a magnetic levitation system.","PeriodicalId":205599,"journal":{"name":"2014 IEEE Conference on Control Applications (CCA)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132192032","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 : 2014-12-11DOI: 10.1109/CCA.2014.6981558
S. E. Benattia, S. Tebbani, D. Dumur, D. Selișteanu
This paper deals with the design of a predictive control law for microalgae culture process to regulate the biomass concentration at a chosen setpoint. However, the performances of the Nonlinear Model Predictive Controller usually decrease when the true plant evolution deviates significantly from that predicted by the model. Thus, a robust criterion under model's parameters uncertainties is considered, implying solving a min-max optimization problem. In order to reduce the computational burden and complexity induced by this formulation, a sensitivity analysis is carried out to determine the most influential parameters which will be considered in the optimization step. The proposed approach is validated in simulation and numerical results are given to illustrate its efficiency for setpoint tracking in the presence of parameters uncertainties.
{"title":"Robust Nonlinear Model Predictive Controller based on sensitivity analysis — Application to a continuous photobioreactor","authors":"S. E. Benattia, S. Tebbani, D. Dumur, D. Selișteanu","doi":"10.1109/CCA.2014.6981558","DOIUrl":"https://doi.org/10.1109/CCA.2014.6981558","url":null,"abstract":"This paper deals with the design of a predictive control law for microalgae culture process to regulate the biomass concentration at a chosen setpoint. However, the performances of the Nonlinear Model Predictive Controller usually decrease when the true plant evolution deviates significantly from that predicted by the model. Thus, a robust criterion under model's parameters uncertainties is considered, implying solving a min-max optimization problem. In order to reduce the computational burden and complexity induced by this formulation, a sensitivity analysis is carried out to determine the most influential parameters which will be considered in the optimization step. The proposed approach is validated in simulation and numerical results are given to illustrate its efficiency for setpoint tracking in the presence of parameters uncertainties.","PeriodicalId":205599,"journal":{"name":"2014 IEEE Conference on Control Applications (CCA)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132264129","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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