Pub Date : 2021-12-14DOI: 10.1109/CDC45484.2021.9683478
M. Shehzad, F. Guéniat
The battery energy storage system’s integration with renewable energy (RE) micro-grids play an important role in solving power supply problems. To achieve reliable and economic operations of a RE micro-grid, in addition to maximize the integration of of renewable resources, the lifetime characteristics of a battery energy storage system also need to be fully investigated.This research study develops an optimization model that includes battery life loss cost, states switching costs, and operation and maintenance cost to obtain a set of optimal parameters of operation strategy. Considering the lifetime characteristics of battery storage system, a multi-objective optimization to maximize the power sold values, and to minimize the degradations concerning battery life cycles has been achieved being main control objectives of the research under study. Based on a model adopting mixed-integer constraints and dynamics, the problem of optimal load demand tracking, and electricity market participation is solved through the implementation of an model based predictive control (MPC) scheme. The efficacy of the proposed controller is proved through extensive simulations where the RE-based micro-grid running costs are minimized.
{"title":"Optimal operation of renewable energy microgrids considering lifetime characteristics of battery energy storage system","authors":"M. Shehzad, F. Guéniat","doi":"10.1109/CDC45484.2021.9683478","DOIUrl":"https://doi.org/10.1109/CDC45484.2021.9683478","url":null,"abstract":"The battery energy storage system’s integration with renewable energy (RE) micro-grids play an important role in solving power supply problems. To achieve reliable and economic operations of a RE micro-grid, in addition to maximize the integration of of renewable resources, the lifetime characteristics of a battery energy storage system also need to be fully investigated.This research study develops an optimization model that includes battery life loss cost, states switching costs, and operation and maintenance cost to obtain a set of optimal parameters of operation strategy. Considering the lifetime characteristics of battery storage system, a multi-objective optimization to maximize the power sold values, and to minimize the degradations concerning battery life cycles has been achieved being main control objectives of the research under study. Based on a model adopting mixed-integer constraints and dynamics, the problem of optimal load demand tracking, and electricity market participation is solved through the implementation of an model based predictive control (MPC) scheme. The efficacy of the proposed controller is proved through extensive simulations where the RE-based micro-grid running costs are minimized.","PeriodicalId":229089,"journal":{"name":"2021 60th IEEE Conference on Decision and Control (CDC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125952043","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 : 2021-12-14DOI: 10.1109/CDC45484.2021.9682846
Berkay Turan, César A. Uribe, Hoi-To Wai, M. Alizadeh
Large-scale optimization problems are usually characterized not only by large amounts of data points but points living in a high-dimensional space. Block coordinate methods allow for efficient implementations where steps can be made (block) coordinate-wise. Many existing algorithms rely on trustworthy gradient information and may fail to converge when such information becomes corrupted by possibly adversarial agents. We study the setting where the partial gradient with respect to each coordinate block is arbitrarily corrupted with some probability. We analyze the robustness properties of the normalized random block coordinate method (NRBCM) for non-convex optimization problems. We prove that NRBCM finds an $mathcal{O}(1/sqrt T )$-stationary point after T iterations if the corruption probabilities of partial gradients with respect to each block are below 1/2. With the additional assumption of gradient domination, faster rates are shown. Numerical evidence on a logistic classification problem supports our results.
{"title":"On Robustness of the Normalized Random Block Coordinate Method for Non-Convex Optimization","authors":"Berkay Turan, César A. Uribe, Hoi-To Wai, M. Alizadeh","doi":"10.1109/CDC45484.2021.9682846","DOIUrl":"https://doi.org/10.1109/CDC45484.2021.9682846","url":null,"abstract":"Large-scale optimization problems are usually characterized not only by large amounts of data points but points living in a high-dimensional space. Block coordinate methods allow for efficient implementations where steps can be made (block) coordinate-wise. Many existing algorithms rely on trustworthy gradient information and may fail to converge when such information becomes corrupted by possibly adversarial agents. We study the setting where the partial gradient with respect to each coordinate block is arbitrarily corrupted with some probability. We analyze the robustness properties of the normalized random block coordinate method (NRBCM) for non-convex optimization problems. We prove that NRBCM finds an $mathcal{O}(1/sqrt T )$-stationary point after T iterations if the corruption probabilities of partial gradients with respect to each block are below 1/2. With the additional assumption of gradient domination, faster rates are shown. Numerical evidence on a logistic classification problem supports our results.","PeriodicalId":229089,"journal":{"name":"2021 60th IEEE Conference on Decision and Control (CDC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126105260","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 : 2021-12-14DOI: 10.1109/CDC45484.2021.9683320
Saket Adhau, Vihangkumar V. Naik, S. Skogestad
Solving Non-Linear Model Predictive Control (NMPC) online is often challenging due to the computational complexities involved. This issue can be avoided by approximating the optimization problem using supervised learning methods which comes with a trade-off on the optimality and/or constraint satisfaction. In this paper, a novel supervised learning framework for approximating NMPC is proposed, where we explicitly impart constraint knowledge within the neural networks. This knowledge is inherited by augmenting the loss function of the neural networks during the training phase with insights from KKT conditions. Logarithmic barrier functions are utilized to augment the loss function including conditions of primal and dual feasibility. The proposed framework can be applied to other machine learning based parametric approximators. This approach is easy to implement and its efficacy is demonstrated on a benchmark NMPC problem for continuous stirred tank reactor (CSTR).
{"title":"Constrained Neural Networks for Approximate Nonlinear Model Predictive Control","authors":"Saket Adhau, Vihangkumar V. Naik, S. Skogestad","doi":"10.1109/CDC45484.2021.9683320","DOIUrl":"https://doi.org/10.1109/CDC45484.2021.9683320","url":null,"abstract":"Solving Non-Linear Model Predictive Control (NMPC) online is often challenging due to the computational complexities involved. This issue can be avoided by approximating the optimization problem using supervised learning methods which comes with a trade-off on the optimality and/or constraint satisfaction. In this paper, a novel supervised learning framework for approximating NMPC is proposed, where we explicitly impart constraint knowledge within the neural networks. This knowledge is inherited by augmenting the loss function of the neural networks during the training phase with insights from KKT conditions. Logarithmic barrier functions are utilized to augment the loss function including conditions of primal and dual feasibility. The proposed framework can be applied to other machine learning based parametric approximators. This approach is easy to implement and its efficacy is demonstrated on a benchmark NMPC problem for continuous stirred tank reactor (CSTR).","PeriodicalId":229089,"journal":{"name":"2021 60th IEEE Conference on Decision and Control (CDC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123567280","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 : 2021-12-14DOI: 10.1109/CDC45484.2021.9682950
P. Wijnbergen, Stephan Trenn
This paper is concerned with the linear quadratic optimal control problem for impulse controllable differential algebraic equations on a bounded half open interval. Regarding the cost functional, a general positive semi-definite weight matrix is considered in the terminal cost. It is shown that for this problem, there generally does not exist an input that minimizes the cost functional. First it is shown that the problem can be reduced to finding an input to an index-1 DAE that minimizes a different quadratic cost functional. Second, necessary and sufficient conditions in terms of matrix equations are given for the existence of an optimal control.
{"title":"Optimal control of DAEs with unconstrained terminal costs","authors":"P. Wijnbergen, Stephan Trenn","doi":"10.1109/CDC45484.2021.9682950","DOIUrl":"https://doi.org/10.1109/CDC45484.2021.9682950","url":null,"abstract":"This paper is concerned with the linear quadratic optimal control problem for impulse controllable differential algebraic equations on a bounded half open interval. Regarding the cost functional, a general positive semi-definite weight matrix is considered in the terminal cost. It is shown that for this problem, there generally does not exist an input that minimizes the cost functional. First it is shown that the problem can be reduced to finding an input to an index-1 DAE that minimizes a different quadratic cost functional. Second, necessary and sufficient conditions in terms of matrix equations are given for the existence of an optimal control.","PeriodicalId":229089,"journal":{"name":"2021 60th IEEE Conference on Decision and Control (CDC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123785988","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 : 2021-12-14DOI: 10.1109/CDC45484.2021.9683103
E. Eraslan, Y. Yildiz
This paper introduces an analytical framework for the derivation of distributed-parameter equations of motion of a flexible quadrotor. This approach helps obtain rigid and flexible equations of motion simultaneously, in a decoupled form, which facilitates the controller design. An adaptive controller is implemented using the developed model to prevent excessive oscillations due to flexible dynamics and to compensate uncertainties. Furthermore, a delay-dependent stability condition is obtained for the overall system dynamics, including the human UAV operator with reaction time delay, the adaptive controller and the flexible quadrotor dynamics. It is demonstrated via simulations that the flexible arm tip oscillations are reduced when the closed loop reference model adaptive controller is used, compared to a conventional model reference adaptive controller.
{"title":"Modeling and Adaptive Control of Flexible Quadrotor UAVs","authors":"E. Eraslan, Y. Yildiz","doi":"10.1109/CDC45484.2021.9683103","DOIUrl":"https://doi.org/10.1109/CDC45484.2021.9683103","url":null,"abstract":"This paper introduces an analytical framework for the derivation of distributed-parameter equations of motion of a flexible quadrotor. This approach helps obtain rigid and flexible equations of motion simultaneously, in a decoupled form, which facilitates the controller design. An adaptive controller is implemented using the developed model to prevent excessive oscillations due to flexible dynamics and to compensate uncertainties. Furthermore, a delay-dependent stability condition is obtained for the overall system dynamics, including the human UAV operator with reaction time delay, the adaptive controller and the flexible quadrotor dynamics. It is demonstrated via simulations that the flexible arm tip oscillations are reduced when the closed loop reference model adaptive controller is used, compared to a conventional model reference adaptive controller.","PeriodicalId":229089,"journal":{"name":"2021 60th IEEE Conference on Decision and Control (CDC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125291996","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 : 2021-12-14DOI: 10.1109/CDC45484.2021.9683637
Changhuang Wan, Gangshan Jing, R. Dai, R. Zhao
In this paper, we propose a formation maneuver control strategy to steer a triangulated formation from two dimensional (2D) space to three dimensional (3D) space, while maintaining the shape of each triangle during the transition. To describe the desired 3D formation shape, we adopt a weak rigidity function containing both distance and angle constraints, together with a sign function. The local shapes are preserved by restricting agents’ motions to the null-space of the distance rigidity function. Furthermore, we formulate this formation maneuver control as an optimal control problem to minimize the control efforts subject to system dynamics, local shape preserving constraints, initial and terminal boundary conditions, which can be solved via a nonlinear programming solver. In the end, two simulation examples are provided to show the effectiveness of our formation control strategy.
{"title":"Local Shape-Preserving Formation Maneuver Control of Multi-agent Systems: From 2D to 3D","authors":"Changhuang Wan, Gangshan Jing, R. Dai, R. Zhao","doi":"10.1109/CDC45484.2021.9683637","DOIUrl":"https://doi.org/10.1109/CDC45484.2021.9683637","url":null,"abstract":"In this paper, we propose a formation maneuver control strategy to steer a triangulated formation from two dimensional (2D) space to three dimensional (3D) space, while maintaining the shape of each triangle during the transition. To describe the desired 3D formation shape, we adopt a weak rigidity function containing both distance and angle constraints, together with a sign function. The local shapes are preserved by restricting agents’ motions to the null-space of the distance rigidity function. Furthermore, we formulate this formation maneuver control as an optimal control problem to minimize the control efforts subject to system dynamics, local shape preserving constraints, initial and terminal boundary conditions, which can be solved via a nonlinear programming solver. In the end, two simulation examples are provided to show the effectiveness of our formation control strategy.","PeriodicalId":229089,"journal":{"name":"2021 60th IEEE Conference on Decision and Control (CDC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125526119","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 : 2021-12-14DOI: 10.1109/CDC45484.2021.9682837
Antonello Venturino, S. Bertrand, C. Stoica, T. Alamo, E. Camacho
This paper focuses on Distributed State Estimation over a peer-to-peer sensor network composed by possible low-computational sensors. We propose a new ℓ-step Neighbourhood Distributed Moving Horizon Estimation technique with fused arrival cost and pre-estimation, improving the accuracy of the estimation, while reducing the computation time compared to other approaches from the literature. Simultaneously, convergence of the estimation error is improved by means of spreading the information amongst neighbourhoods, which comes natural in the sliding window data present in the Moving Horizon Estimation paradigm.
{"title":"A New ℓ-step Neighbourhood Distributed Moving Horizon Estimator","authors":"Antonello Venturino, S. Bertrand, C. Stoica, T. Alamo, E. Camacho","doi":"10.1109/CDC45484.2021.9682837","DOIUrl":"https://doi.org/10.1109/CDC45484.2021.9682837","url":null,"abstract":"This paper focuses on Distributed State Estimation over a peer-to-peer sensor network composed by possible low-computational sensors. We propose a new ℓ-step Neighbourhood Distributed Moving Horizon Estimation technique with fused arrival cost and pre-estimation, improving the accuracy of the estimation, while reducing the computation time compared to other approaches from the literature. Simultaneously, convergence of the estimation error is improved by means of spreading the information amongst neighbourhoods, which comes natural in the sliding window data present in the Moving Horizon Estimation paradigm.","PeriodicalId":229089,"journal":{"name":"2021 60th IEEE Conference on Decision and Control (CDC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125526282","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 : 2021-12-14DOI: 10.1109/CDC45484.2021.9683536
Gianluca Villani, L. Scardovi
In this paper we investigate the dynamics of a network of N diffusively-coupled compartments, each modelling a bistable switch. The dynamics of each compartment is described by a piecewise linear differential equation. We prove that all the solutions converge to the set of equilibria and that this is a structural property, as it does not depend on the system parameters and the interconnection topology. The theoretical results are supplemented with numerical results which suggest new directions for future research.
{"title":"Global analysis of networks of piecewise affine bistable switches","authors":"Gianluca Villani, L. Scardovi","doi":"10.1109/CDC45484.2021.9683536","DOIUrl":"https://doi.org/10.1109/CDC45484.2021.9683536","url":null,"abstract":"In this paper we investigate the dynamics of a network of N diffusively-coupled compartments, each modelling a bistable switch. The dynamics of each compartment is described by a piecewise linear differential equation. We prove that all the solutions converge to the set of equilibria and that this is a structural property, as it does not depend on the system parameters and the interconnection topology. The theoretical results are supplemented with numerical results which suggest new directions for future research.","PeriodicalId":229089,"journal":{"name":"2021 60th IEEE Conference on Decision and Control (CDC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126828858","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 : 2021-12-14DOI: 10.1109/CDC45484.2021.9683696
M. Fauser, Ping Zhang
In this paper, a resilient homomorphic encryption scheme for cyber-physical systems (CPS) is presented. The proposed approach allows the calculation process of feedback controllers to be carried out in an encrypted environment. Moreover, the proposed approach is able to neutralize the effect of attacks injected in the encrypted signals sent over the network, so that the controller can still get the true sensor information. We shall first show that the proposed resilient homomorphic encryption scheme can calculate the multiplication of a matrix with a vector directly based on the ciphertexts, whose result after decryption is the same as the matrix-vector product got based on plaintexts. By transforming the control law into a matrix-vector product, the evaluation of the controller can be carried out with ciphertexts. As a result, the resilient homomorphic encryption scheme ensures the confidentiality of both the signals sent over the network and the controller parameters. In addition, a CPS utilizing the proposed encryption scheme is resilient to additive attacks, as long as the attacks are inside the resilience range. The proposed approach is illustrated through the well-established quadruple-tank benchmark process.
{"title":"Resilient Homomorphic Encryption Scheme for Cyber-Physical Systems","authors":"M. Fauser, Ping Zhang","doi":"10.1109/CDC45484.2021.9683696","DOIUrl":"https://doi.org/10.1109/CDC45484.2021.9683696","url":null,"abstract":"In this paper, a resilient homomorphic encryption scheme for cyber-physical systems (CPS) is presented. The proposed approach allows the calculation process of feedback controllers to be carried out in an encrypted environment. Moreover, the proposed approach is able to neutralize the effect of attacks injected in the encrypted signals sent over the network, so that the controller can still get the true sensor information. We shall first show that the proposed resilient homomorphic encryption scheme can calculate the multiplication of a matrix with a vector directly based on the ciphertexts, whose result after decryption is the same as the matrix-vector product got based on plaintexts. By transforming the control law into a matrix-vector product, the evaluation of the controller can be carried out with ciphertexts. As a result, the resilient homomorphic encryption scheme ensures the confidentiality of both the signals sent over the network and the controller parameters. In addition, a CPS utilizing the proposed encryption scheme is resilient to additive attacks, as long as the attacks are inside the resilience range. The proposed approach is illustrated through the well-established quadruple-tank benchmark process.","PeriodicalId":229089,"journal":{"name":"2021 60th IEEE Conference on Decision and Control (CDC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126860479","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 : 2021-12-14DOI: 10.1109/CDC45484.2021.9683381
Jingting Zhang, Yan Gu, P. Stegagno, Weizhen Zeng, C. Yuan
This paper is focused on the reference-tracking control problem of distributed parameter systems modeled by a class of parabolic partial differential equations (PDEs) with uncertain nonlinear dynamics. An adaptive tracking control scheme is developed by utilizing radial basis function neural networks (RBF NNs) to deal with nonlinear system uncertainties. Specifically, the Galerkin method is first employed to derive a reduced-order ordinary differential equation (ODE) model to approximate the original PDE system. Based on this, an adaptive tracking control scheme is developed based on the singular perturbation theory and Lyapunov stability theory. With the control scheme implemented on the original PDE system, the system output can be guaranteed to track a prescribed reference trajectory with desired system stability and tracking accuracy. Simulation study on a representative transport-reaction process is conducted to demonstrate the effectiveness of the proposed approach.
{"title":"Adaptive NN-Based Reference-Tracking Control of Uncertain Nonlinear Parabolic PDE Systems","authors":"Jingting Zhang, Yan Gu, P. Stegagno, Weizhen Zeng, C. Yuan","doi":"10.1109/CDC45484.2021.9683381","DOIUrl":"https://doi.org/10.1109/CDC45484.2021.9683381","url":null,"abstract":"This paper is focused on the reference-tracking control problem of distributed parameter systems modeled by a class of parabolic partial differential equations (PDEs) with uncertain nonlinear dynamics. An adaptive tracking control scheme is developed by utilizing radial basis function neural networks (RBF NNs) to deal with nonlinear system uncertainties. Specifically, the Galerkin method is first employed to derive a reduced-order ordinary differential equation (ODE) model to approximate the original PDE system. Based on this, an adaptive tracking control scheme is developed based on the singular perturbation theory and Lyapunov stability theory. With the control scheme implemented on the original PDE system, the system output can be guaranteed to track a prescribed reference trajectory with desired system stability and tracking accuracy. Simulation study on a representative transport-reaction process is conducted to demonstrate the effectiveness of the proposed approach.","PeriodicalId":229089,"journal":{"name":"2021 60th IEEE Conference on Decision and Control (CDC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126862396","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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