Pub Date : 2020-07-01DOI: 10.23919/acc45564.2020.9147506
Zhenyu Lin, J. Baras
In this paper we present a modular Q-learning framework to deal with the robot task planning, runtime monitoring and self-correction problem. The task is specified using metric interval temporal logic (MITL) with finite time constraints. We first construct a runtime monitor automaton using three-valued LTL (LTL3), and a sub-task MITL monitor is constructed by decomposing and augmenting the monitor automaton. During the learning phase, a modular Q-learning approach is proposed such that each module could learn different sub-tasks. During runtime, the sub-task MITL monitors could monitor the execution and guide the agent for possible self-correction if an error occurs. Our experiments show that under our framework, the robot is able to learn a feasible execution sequence that satisfies the given MITL specifications under finite time constraints. When the runtime environment becomes different than the learning environment and the original action will violate the specifications, the robotic agent is able to self-correct and accomplish the task if it is still possible.
{"title":"Metric Interval Temporal Logic based Reinforcement Learning with Runtime Monitoring and Self-Correction","authors":"Zhenyu Lin, J. Baras","doi":"10.23919/acc45564.2020.9147506","DOIUrl":"https://doi.org/10.23919/acc45564.2020.9147506","url":null,"abstract":"In this paper we present a modular Q-learning framework to deal with the robot task planning, runtime monitoring and self-correction problem. The task is specified using metric interval temporal logic (MITL) with finite time constraints. We first construct a runtime monitor automaton using three-valued LTL (LTL3), and a sub-task MITL monitor is constructed by decomposing and augmenting the monitor automaton. During the learning phase, a modular Q-learning approach is proposed such that each module could learn different sub-tasks. During runtime, the sub-task MITL monitors could monitor the execution and guide the agent for possible self-correction if an error occurs. Our experiments show that under our framework, the robot is able to learn a feasible execution sequence that satisfies the given MITL specifications under finite time constraints. When the runtime environment becomes different than the learning environment and the original action will violate the specifications, the robotic agent is able to self-correct and accomplish the task if it is still possible.","PeriodicalId":288450,"journal":{"name":"2020 American Control Conference (ACC)","volume":"29 31","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113955264","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 : 2020-07-01DOI: 10.23919/ACC45564.2020.9147686
Jishnudeep Kar, A. Chakrabortty
In this paper we present two distributed algorithms for estimating the electro-mechanical oscillation mode shapes (eigen-vectors) of a power system using Synchrophasor measurements while also being aware of any cyber-threats that may bias these algorithms. We consider the power system to be divided into non-overlapping areas, each equipped with a local estimator. The local estimators exchange information for computing the mode shapes over a strongly connected communication graph, realized through an un-secure wide-area communication network (WAN). An attacker can intrude into this WAN, and manipulate the information exchanged between the estimators, thereby easily destabilizing the estimation loop. We develop mechanisms by which every estimator can either check the rank or inspect the singular values of appropriate data matrices. Any visible jump in the rank or singular values will enable the estimator to detect a potential manipulation. We validate our algorithms using a 4-machine 4-area power system and the IEEE 16-machine 68-bus system.
{"title":"Localizing Data Manipulators in Distributed Mode Shape Identification of Power Systems","authors":"Jishnudeep Kar, A. Chakrabortty","doi":"10.23919/ACC45564.2020.9147686","DOIUrl":"https://doi.org/10.23919/ACC45564.2020.9147686","url":null,"abstract":"In this paper we present two distributed algorithms for estimating the electro-mechanical oscillation mode shapes (eigen-vectors) of a power system using Synchrophasor measurements while also being aware of any cyber-threats that may bias these algorithms. We consider the power system to be divided into non-overlapping areas, each equipped with a local estimator. The local estimators exchange information for computing the mode shapes over a strongly connected communication graph, realized through an un-secure wide-area communication network (WAN). An attacker can intrude into this WAN, and manipulate the information exchanged between the estimators, thereby easily destabilizing the estimation loop. We develop mechanisms by which every estimator can either check the rank or inspect the singular values of appropriate data matrices. Any visible jump in the rank or singular values will enable the estimator to detect a potential manipulation. We validate our algorithms using a 4-machine 4-area power system and the IEEE 16-machine 68-bus system.","PeriodicalId":288450,"journal":{"name":"2020 American Control Conference (ACC)","volume":"96 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114023224","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 : 2020-07-01DOI: 10.23919/ACC45564.2020.9147902
A. Chhokra, Saqib Hasan, A. Dubey, G. Karsai
Cascading outages in power systems is a rare, but important phenomenon with huge social and economic implications. Due to the inherent complexity and heterogeneity of components in power system, analysis and prediction of the current and future states of the system is a challenging task. In this paper, we address prognosis of cascading outages in power systems by employing a novel approach based on reduced ordered binary decision diagrams. We present a systemic way of synthesizing these decision diagrams based on a simple cascade model. We also describe a workflow for finding the emergency load curtailment actions as a part of the mitigation strategy. In the end, we show the applicability of our approach using the standard IEEE 14 bus system.
{"title":"A Binary Decision Diagram Based Cascade Prognostics Scheme For Power Systems","authors":"A. Chhokra, Saqib Hasan, A. Dubey, G. Karsai","doi":"10.23919/ACC45564.2020.9147902","DOIUrl":"https://doi.org/10.23919/ACC45564.2020.9147902","url":null,"abstract":"Cascading outages in power systems is a rare, but important phenomenon with huge social and economic implications. Due to the inherent complexity and heterogeneity of components in power system, analysis and prediction of the current and future states of the system is a challenging task. In this paper, we address prognosis of cascading outages in power systems by employing a novel approach based on reduced ordered binary decision diagrams. We present a systemic way of synthesizing these decision diagrams based on a simple cascade model. We also describe a workflow for finding the emergency load curtailment actions as a part of the mitigation strategy. In the end, we show the applicability of our approach using the standard IEEE 14 bus system.","PeriodicalId":288450,"journal":{"name":"2020 American Control Conference (ACC)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114783577","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 : 2020-07-01DOI: 10.23919/ACC45564.2020.9147223
Masih Haseli, J. Cortés
This paper presents a parallel data-driven method to identify finite-dimensional subspaces that are invariant under the Koopman operator describing a dynamical system. Our approach builds on Symmetric Subspace Decomposition (SSD), which is a centralized scheme to find Koopman-invariant subspaces and Koopman eigenfunctions. Given a dictionary of functions, a collection of processors communicating through a strongly connected time-invariant directed graph, and a set of data snapshots gathered from the dynamical system, our approach distributes the data snapshots among the processors and initializes each processor with the original dictionary. Then, at each iteration, processors prune their dictionary by using the information received from their neighbors and applying the SSD method on the pruned dictionary with their local data. We prove that the algorithm terminates in a finite number of iterations and that the processors, upon termination, reach consensus on the maximal Koopman-invariant subspace in the span of the dictionary (and is therefore equivalent to SSD). A simulation example shows significant gains in time complexity by the proposed method over SSD.
{"title":"Fast Identification of Koopman-Invariant Subspaces: Parallel Symmetric Subspace Decomposition","authors":"Masih Haseli, J. Cortés","doi":"10.23919/ACC45564.2020.9147223","DOIUrl":"https://doi.org/10.23919/ACC45564.2020.9147223","url":null,"abstract":"This paper presents a parallel data-driven method to identify finite-dimensional subspaces that are invariant under the Koopman operator describing a dynamical system. Our approach builds on Symmetric Subspace Decomposition (SSD), which is a centralized scheme to find Koopman-invariant subspaces and Koopman eigenfunctions. Given a dictionary of functions, a collection of processors communicating through a strongly connected time-invariant directed graph, and a set of data snapshots gathered from the dynamical system, our approach distributes the data snapshots among the processors and initializes each processor with the original dictionary. Then, at each iteration, processors prune their dictionary by using the information received from their neighbors and applying the SSD method on the pruned dictionary with their local data. We prove that the algorithm terminates in a finite number of iterations and that the processors, upon termination, reach consensus on the maximal Koopman-invariant subspace in the span of the dictionary (and is therefore equivalent to SSD). A simulation example shows significant gains in time complexity by the proposed method over SSD.","PeriodicalId":288450,"journal":{"name":"2020 American Control Conference (ACC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127683381","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 : 2020-07-01DOI: 10.23919/ACC45564.2020.9147852
Daniel S. Campos, J. D. Val
This paper deals with some notions of observability coupled with corresponding notions of norm energy for a certain class of stochastic models. The class is devoted to systems subjected to a relevant degree of uncertainty, obtained from the concept that control and state variations increase uncertainties (CSVIU) in a poorly known system. The paper develops conditions under which finiteness of the norm connects with the stability of the system in an appropriate and similar stochastic sense. The rank test of the observability matrices ties these notions in an observability test, placing the analysis on the same foot of deterministic systems. Besides, the results here have the potential to establish useful connections for the stochastic norm problems presented here.
{"title":"Observability Notions for CSVIU and Stability in Connection with Some Norms","authors":"Daniel S. Campos, J. D. Val","doi":"10.23919/ACC45564.2020.9147852","DOIUrl":"https://doi.org/10.23919/ACC45564.2020.9147852","url":null,"abstract":"This paper deals with some notions of observability coupled with corresponding notions of norm energy for a certain class of stochastic models. The class is devoted to systems subjected to a relevant degree of uncertainty, obtained from the concept that control and state variations increase uncertainties (CSVIU) in a poorly known system. The paper develops conditions under which finiteness of the norm connects with the stability of the system in an appropriate and similar stochastic sense. The rank test of the observability matrices ties these notions in an observability test, placing the analysis on the same foot of deterministic systems. Besides, the results here have the potential to establish useful connections for the stochastic norm problems presented here.","PeriodicalId":288450,"journal":{"name":"2020 American Control Conference (ACC)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127776750","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 : 2020-07-01DOI: 10.23919/ACC45564.2020.9147364
Xin Ning, Walter Bomela, Shin Li
In this paper, we investigate an iterative method for computing optimal controls for general affine nonlinear quadratic tracking problems. The control law is computed iteratively by solving a sequence of linear quadratic tracking problems and, in particular, it consists of solving a set of coupled differential equations derived from the Hamilton-Jacobi-Bellman equation. The convergence of the iterative scheme is shown by constructing a contraction mapping and using the fixed-point theorem. The versatility and effectiveness of the proposed method is demonstrated in numerical simulations of three structurally different nonlinear systems.
{"title":"An Iterative Method for Optimal Control of Nonlinear Quadratic Tracking Problems","authors":"Xin Ning, Walter Bomela, Shin Li","doi":"10.23919/ACC45564.2020.9147364","DOIUrl":"https://doi.org/10.23919/ACC45564.2020.9147364","url":null,"abstract":"In this paper, we investigate an iterative method for computing optimal controls for general affine nonlinear quadratic tracking problems. The control law is computed iteratively by solving a sequence of linear quadratic tracking problems and, in particular, it consists of solving a set of coupled differential equations derived from the Hamilton-Jacobi-Bellman equation. The convergence of the iterative scheme is shown by constructing a contraction mapping and using the fixed-point theorem. The versatility and effectiveness of the proposed method is demonstrated in numerical simulations of three structurally different nonlinear systems.","PeriodicalId":288450,"journal":{"name":"2020 American Control Conference (ACC)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126378944","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 : 2020-07-01DOI: 10.23919/acc45564.2020.9147780
Jin Sung Kim, Seung-Hi Lee, C. Chung
In this paper, we propose a scheme of lane change control for automated vehicle without path planning and its tracking. It is not easy to make path planning for lane change although there are several method for the path planning such as using a combination of sinusoidal functions and high order polynomial functions. In this paper, time-varying hyperplane is utilized to cope with the problem of path planning and control for lateral motion in lane change control. Designing a sliding hyperplane in terms of lateral position and velocity is presented so that the lateral error converges uniformly and smoothly during lane changing irrespective of the amount of lateral offset. The simulation-based optimization approach is utilized to obtain the optimal time-varying sliding hyperplane. The stability of the closed-loop system is proved with the analysis of a discrete time-varying system. The effectiveness of the proposed method is validated with numerical simulation showing the uniform settling of lateral tracking error no matter what the desired lateral offset is commanded.
{"title":"Lane Change Control with Optimal Time-varying Sliding Mode in Automated Driving Vehicle","authors":"Jin Sung Kim, Seung-Hi Lee, C. Chung","doi":"10.23919/acc45564.2020.9147780","DOIUrl":"https://doi.org/10.23919/acc45564.2020.9147780","url":null,"abstract":"In this paper, we propose a scheme of lane change control for automated vehicle without path planning and its tracking. It is not easy to make path planning for lane change although there are several method for the path planning such as using a combination of sinusoidal functions and high order polynomial functions. In this paper, time-varying hyperplane is utilized to cope with the problem of path planning and control for lateral motion in lane change control. Designing a sliding hyperplane in terms of lateral position and velocity is presented so that the lateral error converges uniformly and smoothly during lane changing irrespective of the amount of lateral offset. The simulation-based optimization approach is utilized to obtain the optimal time-varying sliding hyperplane. The stability of the closed-loop system is proved with the analysis of a discrete time-varying system. The effectiveness of the proposed method is validated with numerical simulation showing the uniform settling of lateral tracking error no matter what the desired lateral offset is commanded.","PeriodicalId":288450,"journal":{"name":"2020 American Control Conference (ACC)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125731500","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 : 2020-07-01DOI: 10.23919/ACC45564.2020.9147897
S. Kadam, Aishwarya Rao, B. Prusty, H. Palanthandalam-Madapusi
Trackability is the ability of a system to follow arbitrary reference commands and is equivalent to a system being right invertible. For systems that are trackable, feedforward inversion-based control (along with an additional feedback loop) is a common method to achieve tracking. In this paper, we focus on trackability for linear discrete-time MIMO systems and examine the idea of selective tracking that is particularly useful when a system is not trackable but it is possible to track either certain subsets of outputs or certain combinations of them. We show that tracking each component of the output vector can be assigned a priority within the context of an inversion-based controller to provide significant flexibility in selectively tracking outputs of interest even when the system as a whole is untrackable. We further demonstrate various aspects of trackability theory and selective tracking through a few simulation examples including a quadrotor example.
{"title":"Selective Tracking Using Linear Trackability Analysis and Inversion-based Tracking Control","authors":"S. Kadam, Aishwarya Rao, B. Prusty, H. Palanthandalam-Madapusi","doi":"10.23919/ACC45564.2020.9147897","DOIUrl":"https://doi.org/10.23919/ACC45564.2020.9147897","url":null,"abstract":"Trackability is the ability of a system to follow arbitrary reference commands and is equivalent to a system being right invertible. For systems that are trackable, feedforward inversion-based control (along with an additional feedback loop) is a common method to achieve tracking. In this paper, we focus on trackability for linear discrete-time MIMO systems and examine the idea of selective tracking that is particularly useful when a system is not trackable but it is possible to track either certain subsets of outputs or certain combinations of them. We show that tracking each component of the output vector can be assigned a priority within the context of an inversion-based controller to provide significant flexibility in selectively tracking outputs of interest even when the system as a whole is untrackable. We further demonstrate various aspects of trackability theory and selective tracking through a few simulation examples including a quadrotor example.","PeriodicalId":288450,"journal":{"name":"2020 American Control Conference (ACC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121851519","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 : 2020-07-01DOI: 10.23919/ACC45564.2020.9147987
K. K. Rangan, Helen Durand
A method for integrating optimization and control during on-line process operation is known as economic model predictive control (EMPC). EMPC optimizes a general cost function which reflects process economics subject to a model of the process. One formulation of EMPC which can maintain closed-loop stability in the presence of sufficiently small disturbances is Lyapunov-based EMPC (LEMPC). In this work, we make precise connections between closed-loop stability considerations under LEMPC and numerical approximations (via Taylor series) of the solution of the nonlinear dynamic model of the process used in the controller. A chemical process example is utilized to demonstrate the concepts developed.
{"title":"Lyapunov-based Economic Model Predictive Control with Taylor Series State Approximations","authors":"K. K. Rangan, Helen Durand","doi":"10.23919/ACC45564.2020.9147987","DOIUrl":"https://doi.org/10.23919/ACC45564.2020.9147987","url":null,"abstract":"A method for integrating optimization and control during on-line process operation is known as economic model predictive control (EMPC). EMPC optimizes a general cost function which reflects process economics subject to a model of the process. One formulation of EMPC which can maintain closed-loop stability in the presence of sufficiently small disturbances is Lyapunov-based EMPC (LEMPC). In this work, we make precise connections between closed-loop stability considerations under LEMPC and numerical approximations (via Taylor series) of the solution of the nonlinear dynamic model of the process used in the controller. A chemical process example is utilized to demonstrate the concepts developed.","PeriodicalId":288450,"journal":{"name":"2020 American Control Conference (ACC)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121597999","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 : 2020-07-01DOI: 10.23919/ACC45564.2020.9147535
Xuan-Zhi ZHU, Pedro Casau, C. Silvestre
This paper presents an event-triggered controller that solves the problem of trajectory tracking for an aerial vehicle with a thrust actuation in a single body-fixed direction and full angular velocity actuation. Under the framework of hybrid dynamical systems, we first design a globally stabilizing hybrid control law and then derive an appropriate eventtriggering mechanism for sampling of actuation signals. We prove that bounded reference trajectories are rendered globally asymptotically stable for the closed-loop system. To enable practical implementation of the proposed event-triggered controller on digital platforms, we provide a modified event-triggering mechanism that achieves practical stability while avoiding Zeno solutions. The results are illustrated by numerical simulations and further verified by experiments.
{"title":"Global Trajectory Tracking for a Quadrotor through Event-Triggered Control: Synthesis, Simulations, and Experiments*","authors":"Xuan-Zhi ZHU, Pedro Casau, C. Silvestre","doi":"10.23919/ACC45564.2020.9147535","DOIUrl":"https://doi.org/10.23919/ACC45564.2020.9147535","url":null,"abstract":"This paper presents an event-triggered controller that solves the problem of trajectory tracking for an aerial vehicle with a thrust actuation in a single body-fixed direction and full angular velocity actuation. Under the framework of hybrid dynamical systems, we first design a globally stabilizing hybrid control law and then derive an appropriate eventtriggering mechanism for sampling of actuation signals. We prove that bounded reference trajectories are rendered globally asymptotically stable for the closed-loop system. To enable practical implementation of the proposed event-triggered controller on digital platforms, we provide a modified event-triggering mechanism that achieves practical stability while avoiding Zeno solutions. The results are illustrated by numerical simulations and further verified by experiments.","PeriodicalId":288450,"journal":{"name":"2020 American Control Conference (ACC)","volume":"85 10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115795919","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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