Pub Date : 2017-05-24DOI: 10.23919/ACC.2017.7963259
Yonghao Gui, Chunghun Kim, C. Chung
We propose a grid voltage modulated (GVM) direct power control (DPC) strategy for a grid-connected voltage source inverter (VSI) to control the instantaneous active and reactive powers. The GVM-DPC presents the system in d-q frame without using a phase-lock loop. In addition, the GVM method converts the system into a linear time-invariant system. The GVM-DPC is designed to obtain two separate second-order systems for not only the convergence rate of the instantaneous active and reactive powers but also the steady-state performance. In addition, the closed-loop system is exponentially stable in the whole operating range. The proposed method is verified by using MATLAB/Simulink with PLECS blockset. The simulation results show that the proposed method has not only good tracking performances in both active and reactive powers but also a lower current total harmonic distortion than that of the sliding mode control DPC method. Finally, the proposed method is validated by using a hardware-in-the-loop system with a digital signal processor. The experimental results are similar to simulation results. Moreover, the robustness to the line impedance and the grid voltage is tested and discussed.
{"title":"Grid voltage modulated direct power control for grid connected voltage source inverters","authors":"Yonghao Gui, Chunghun Kim, C. Chung","doi":"10.23919/ACC.2017.7963259","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963259","url":null,"abstract":"We propose a grid voltage modulated (GVM) direct power control (DPC) strategy for a grid-connected voltage source inverter (VSI) to control the instantaneous active and reactive powers. The GVM-DPC presents the system in d-q frame without using a phase-lock loop. In addition, the GVM method converts the system into a linear time-invariant system. The GVM-DPC is designed to obtain two separate second-order systems for not only the convergence rate of the instantaneous active and reactive powers but also the steady-state performance. In addition, the closed-loop system is exponentially stable in the whole operating range. The proposed method is verified by using MATLAB/Simulink with PLECS blockset. The simulation results show that the proposed method has not only good tracking performances in both active and reactive powers but also a lower current total harmonic distortion than that of the sliding mode control DPC method. Finally, the proposed method is validated by using a hardware-in-the-loop system with a digital signal processor. The experimental results are similar to simulation results. Moreover, the robustness to the line impedance and the grid voltage is tested and discussed.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129246339","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 : 2017-05-24DOI: 10.23919/ACC.2017.7963380
Torstein Thode Kristoffersen, C. Holden, S. Skogestad, O. Egeland
Compact separators are increasingly used for subsea separation of hydrocarbons, because of their low weight and low cost. A problem is their small volume, which makes them very sensitive to flow variations. This can degrade separation performance, which in turn can cause operational problems and economic loss. Improved control can increase robustness and therefore, the focus of this paper is to derive a control-oriented model based on first principles to enable the development of robust control algorithms. The derived model is controlled by a PI feedback control algorithm and tuned using the SIMC tuning rules. The model is qualitatively verified in simulations, and the behaviour confirmed with reported observations from experimental work and field applications from literature.
{"title":"Control-oriented modelling of gas-liquid cylindrical cyclones","authors":"Torstein Thode Kristoffersen, C. Holden, S. Skogestad, O. Egeland","doi":"10.23919/ACC.2017.7963380","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963380","url":null,"abstract":"Compact separators are increasingly used for subsea separation of hydrocarbons, because of their low weight and low cost. A problem is their small volume, which makes them very sensitive to flow variations. This can degrade separation performance, which in turn can cause operational problems and economic loss. Improved control can increase robustness and therefore, the focus of this paper is to derive a control-oriented model based on first principles to enable the development of robust control algorithms. The derived model is controlled by a PI feedback control algorithm and tuned using the SIMC tuning rules. The model is qualitatively verified in simulations, and the behaviour confirmed with reported observations from experimental work and field applications from literature.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128954866","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 : 2017-05-24DOI: 10.23919/ACC.2017.7963632
Arnab Raha, A. Chakrabarty, V. Raghunathan, G. Buzzard
The design of energy-efficient and ultrafast nonlinear model predictive controllers (NMPCs) is critical for decision-making in modern engineering systems. To this end, an embedded systems approach is proposed for hardware acceleration of a stabilizing explicit NMPC (ENMPC). Tools from approximate computing are employed to simplify the ENMPC control law and design an ultra-fast, low-power, miniaturized ASIC (application specific integrated circuit) deploying the control mechanism. Approximation bounds on the embedded controller and stability guarantees of the closed-loop system are provided. The efficacy and energy-savings of the embedded ENMPC is verified in an ASIC-in-the-loop simulation experiment. Whereas the exact ENMPC law requires 79K gates for implementation, consumes 13.66 mW of power, and operates at 0.3 GHz on 45 nm Nangate technology, the approximating ASIC requires only 3.6K gates (resulting in a 25× area reduction), consumes a meager 0.47 mW of power (29× power reduction), and runs at 0.5 GHz (more than 105× faster than cutting-edge embedded NMPCs).
{"title":"Ultrafast embedded explicit model predictive control for nonlinear systems","authors":"Arnab Raha, A. Chakrabarty, V. Raghunathan, G. Buzzard","doi":"10.23919/ACC.2017.7963632","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963632","url":null,"abstract":"The design of energy-efficient and ultrafast nonlinear model predictive controllers (NMPCs) is critical for decision-making in modern engineering systems. To this end, an embedded systems approach is proposed for hardware acceleration of a stabilizing explicit NMPC (ENMPC). Tools from approximate computing are employed to simplify the ENMPC control law and design an ultra-fast, low-power, miniaturized ASIC (application specific integrated circuit) deploying the control mechanism. Approximation bounds on the embedded controller and stability guarantees of the closed-loop system are provided. The efficacy and energy-savings of the embedded ENMPC is verified in an ASIC-in-the-loop simulation experiment. Whereas the exact ENMPC law requires 79K gates for implementation, consumes 13.66 mW of power, and operates at 0.3 GHz on 45 nm Nangate technology, the approximating ASIC requires only 3.6K gates (resulting in a 25× area reduction), consumes a meager 0.47 mW of power (29× power reduction), and runs at 0.5 GHz (more than 105× faster than cutting-edge embedded NMPCs).","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121141643","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 : 2017-05-24DOI: 10.23919/ACC.2017.7963006
Pierre-Jean Meyer, Dimos V. Dimarogonas
This paper presents a compositional approach to specification-guided abstraction refinement for control synthesis of a nonlinear system associated with a method to over-approximate its reachable sets. The control specification consists in following a lasso-shaped sequence of regions of the state space. The dynamics are decomposed into subsystems with partial control, partial state observation and possible overlaps between their respective observed state spaces. A finite abstraction is created for each subsystem through a refinement procedure, which starts from a coarse partition of the state space and then proceeds backwards on the lasso sequence to iteratively split the elements of the partition whose coarseness prevents the satisfaction of the specification. The composition of the local controllers obtained for each subsystem is proved to enforce the desired specification on the original system. This approach is illustrated in a nonlinear numerical example.
{"title":"Compositional abstraction refinement for control synthesis under lasso-shaped specifications","authors":"Pierre-Jean Meyer, Dimos V. Dimarogonas","doi":"10.23919/ACC.2017.7963006","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963006","url":null,"abstract":"This paper presents a compositional approach to specification-guided abstraction refinement for control synthesis of a nonlinear system associated with a method to over-approximate its reachable sets. The control specification consists in following a lasso-shaped sequence of regions of the state space. The dynamics are decomposed into subsystems with partial control, partial state observation and possible overlaps between their respective observed state spaces. A finite abstraction is created for each subsystem through a refinement procedure, which starts from a coarse partition of the state space and then proceeds backwards on the lasso sequence to iteratively split the elements of the partition whose coarseness prevents the satisfaction of the specification. The composition of the local controllers obtained for each subsystem is proved to enforce the desired specification on the original system. This approach is illustrated in a nonlinear numerical example.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121241831","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 : 2017-05-24DOI: 10.23919/ACC.2017.7963142
A. Alleyne
Modern energy systems for mobile (e.g. vehicles) and stationary systems (e.g. buildings) operate over multiple physical domains. The thermal energy domain is a critical one to consider for ensuring maximum system performance. Much of the waste energy in these systems is manifested as thermal energy and so managing/minimizing this is a critical component to performance. Additionally, thermal management is also critical for system safety. As evidenced by the recent Samsung Galaxy Note incidents, thermal management is critical. Should thermal management fail, the entire system can fail. In addition to the traditional thermal management components such as pumps and heat exchangers there is a current and increasing need to introduce advanced controls; both for safety and performance.
{"title":"ACC tutorial session proposal thermal and HVAC control systems: Challenges and opportunities","authors":"A. Alleyne","doi":"10.23919/ACC.2017.7963142","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963142","url":null,"abstract":"Modern energy systems for mobile (e.g. vehicles) and stationary systems (e.g. buildings) operate over multiple physical domains. The thermal energy domain is a critical one to consider for ensuring maximum system performance. Much of the waste energy in these systems is manifested as thermal energy and so managing/minimizing this is a critical component to performance. Additionally, thermal management is also critical for system safety. As evidenced by the recent Samsung Galaxy Note incidents, thermal management is critical. Should thermal management fail, the entire system can fail. In addition to the traditional thermal management components such as pumps and heat exchangers there is a current and increasing need to introduce advanced controls; both for safety and performance.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"163 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115265603","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 : 2017-05-24DOI: 10.23919/ACC.2017.7963470
Swaroop S. Guggilam, Changhong Zhao, E. Dall’Anese, Y. Chen, S. Dhople
Power networks have to withstand a variety of disturbances that affect system frequency, and the problem is compounded with the increasing integration of intermittent renewable generation. Following a large-signal generation or load disturbance, system frequency is arrested leveraging primary frequency control provided by governor action in synchronous generators. In this work, we propose a framework for distributed energy resources (DERs) deployed in distribution networks to provide (supplemental) primary frequency response. Particularly, we demonstrate how power-frequency droop slopes for individual DERs can be designed so that the distribution feeder presents a guaranteed frequency-regulation characteristic at the feeder head. Furthermore, the droop slopes are engineered such that injections of individual DERs conform to a well-defined fairness objective that does not penalize them for their location on the distribution feeder. Time-domain simulations for an illustrative network composed of a combined transmission network and distribution network with frequency-responsive DERs are provided to validate the approach.
{"title":"Primary frequency response with aggregated DERs","authors":"Swaroop S. Guggilam, Changhong Zhao, E. Dall’Anese, Y. Chen, S. Dhople","doi":"10.23919/ACC.2017.7963470","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963470","url":null,"abstract":"Power networks have to withstand a variety of disturbances that affect system frequency, and the problem is compounded with the increasing integration of intermittent renewable generation. Following a large-signal generation or load disturbance, system frequency is arrested leveraging primary frequency control provided by governor action in synchronous generators. In this work, we propose a framework for distributed energy resources (DERs) deployed in distribution networks to provide (supplemental) primary frequency response. Particularly, we demonstrate how power-frequency droop slopes for individual DERs can be designed so that the distribution feeder presents a guaranteed frequency-regulation characteristic at the feeder head. Furthermore, the droop slopes are engineered such that injections of individual DERs conform to a well-defined fairness objective that does not penalize them for their location on the distribution feeder. Time-domain simulations for an illustrative network composed of a combined transmission network and distribution network with frequency-responsive DERs are provided to validate the approach.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114061849","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 : 2017-05-24DOI: 10.23919/ACC.2017.7963716
Viktor Rausch, Andreas Hansen, Eugen Solowjow, Chang Liu, E. Kreuzer, J. Karl Hedrick
Deep neural networks are frequently used for computer vision, speech recognition and text processing. The reason is their ability to regress highly nonlinear functions. We present an end-to-end controller for steering autonomous vehicles based on a convolutional neural network (CNN). The deployed framework does not require explicit hand-engineered algorithms for lane detection, object detection or path planning. The trained neural net directly maps pixel data from a front-facing camera to steering commands and does not require any other sensors. We compare the controller performance with the steering behavior of a human driver.
{"title":"Learning a deep neural net policy for end-to-end control of autonomous vehicles","authors":"Viktor Rausch, Andreas Hansen, Eugen Solowjow, Chang Liu, E. Kreuzer, J. Karl Hedrick","doi":"10.23919/ACC.2017.7963716","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963716","url":null,"abstract":"Deep neural networks are frequently used for computer vision, speech recognition and text processing. The reason is their ability to regress highly nonlinear functions. We present an end-to-end controller for steering autonomous vehicles based on a convolutional neural network (CNN). The deployed framework does not require explicit hand-engineered algorithms for lane detection, object detection or path planning. The trained neural net directly maps pixel data from a front-facing camera to steering commands and does not require any other sensors. We compare the controller performance with the steering behavior of a human driver.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115900786","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 : 2017-05-24DOI: 10.23919/ACC.2017.7963029
Farzaneh Tatari, M. Naghibi-Sistani, K. Vamvoudakis
This work proposes an online optimal distributed learning algorithm to find the game theoretic solution of systems on graphs with completely unknown dynamics. The proposed algorithm learns online the approximate solution to the cooperative coupled Hamilton-Jacobi (HJ) equations. Each player employs an actor/critic network structure to learn the optimal cost and the optimal policy along with intelligent identifiers to obviate the knowledge of the system dynamics. We use recorded experiences concurrently with current data to guarantee proper state exploration. The closed-loop system is proved to be stable and the policies form a Nash equilibrium. Finally, simulation results verify the effectiveness of the proposed approach.
{"title":"Distributed optimal synchronization control of linear networked systems under unknown dynamics","authors":"Farzaneh Tatari, M. Naghibi-Sistani, K. Vamvoudakis","doi":"10.23919/ACC.2017.7963029","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963029","url":null,"abstract":"This work proposes an online optimal distributed learning algorithm to find the game theoretic solution of systems on graphs with completely unknown dynamics. The proposed algorithm learns online the approximate solution to the cooperative coupled Hamilton-Jacobi (HJ) equations. Each player employs an actor/critic network structure to learn the optimal cost and the optimal policy along with intelligent identifiers to obviate the knowledge of the system dynamics. We use recorded experiences concurrently with current data to guarantee proper state exploration. The closed-loop system is proved to be stable and the policies form a Nash equilibrium. Finally, simulation results verify the effectiveness of the proposed approach.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130926248","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 : 2017-05-24DOI: 10.23919/ACC.2017.7963341
Shiyi Yang, Nan Wei, Soo Jeon, Ricardo Bencatel, A. Girard
This paper presents a time-critical cargo drop strategy that allows a fixed-wing unmanned aerial vehicle (UAV) carrying a cargo under an unknown wind field, to accomplish the cargo drop mission within the least amount of time while minimizing the cargo landing error. Specifically, we treat the spatial wind distribution as a noisy vector field and apply the Gaussian process (GP) regression method to estimate the wind model. In order to optimize the strategy, the objective function to be maximized has been chosen as the weighted sum of two conflicting objectives: more knowledge of the wind field and less travel time. We present some simulation results to compare the performance of the proposed strategy with a conventional method. Results demonstrate the advantage of the proposed method in terms of accuracy and multi-functionality over the non-estimation strategy.
{"title":"Real-time optimal path planning and wind estimation using Gaussian process regression for precision airdrop","authors":"Shiyi Yang, Nan Wei, Soo Jeon, Ricardo Bencatel, A. Girard","doi":"10.23919/ACC.2017.7963341","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963341","url":null,"abstract":"This paper presents a time-critical cargo drop strategy that allows a fixed-wing unmanned aerial vehicle (UAV) carrying a cargo under an unknown wind field, to accomplish the cargo drop mission within the least amount of time while minimizing the cargo landing error. Specifically, we treat the spatial wind distribution as a noisy vector field and apply the Gaussian process (GP) regression method to estimate the wind model. In order to optimize the strategy, the objective function to be maximized has been chosen as the weighted sum of two conflicting objectives: more knowledge of the wind field and less travel time. We present some simulation results to compare the performance of the proposed strategy with a conventional method. Results demonstrate the advantage of the proposed method in terms of accuracy and multi-functionality over the non-estimation strategy.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126534693","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 : 2017-05-24DOI: 10.23919/ACC.2017.7963253
Matt Wytock, N. Moehle, Stephen P. Boyd
We present a simple, practical method for managing the energy produced and consumed by a network of devices. Our method is based on (convex) model predictive control. We handle uncertainty using a robust model predictive control formulation that considers a finite number of possible scenarios. A key attribute of our formulation is the encapsulation of device details, an idea naturally implemented with object-oriented programming. We introduce an open-source Python library implementing our method and demonstrate its use in planning and control at various scales in the electrical grid: managing a smart home, shared charging of electric vehicles, and integrating a wind farm into the transmission network.
{"title":"Dynamic energy management with scenario-based robust MPC","authors":"Matt Wytock, N. Moehle, Stephen P. Boyd","doi":"10.23919/ACC.2017.7963253","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963253","url":null,"abstract":"We present a simple, practical method for managing the energy produced and consumed by a network of devices. Our method is based on (convex) model predictive control. We handle uncertainty using a robust model predictive control formulation that considers a finite number of possible scenarios. A key attribute of our formulation is the encapsulation of device details, an idea naturally implemented with object-oriented programming. We introduce an open-source Python library implementing our method and demonstrate its use in planning and control at various scales in the electrical grid: managing a smart home, shared charging of electric vehicles, and integrating a wind farm into the transmission network.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"2011 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124282181","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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