Pub Date : 2022-04-20DOI: 10.1109/Control55989.2022.9781360
E. Gershon
Linear state-delayed continuous-time systems with state-multiplicative noise and polytopic type parameter uncertainty are considered. We address the problem of H∞ robust filtering of these systems by applying a vertex dependent Lyapunov function that considerably reduces the over-design that is inherent to the classical design which is based on single Lyapunov function for the whole parameter range. The improved solution is based on the application of the Finsler lemma leading to a unique Lyapunov function that is assigned to each vertex of the polytope uncertainty. An example is given that demonstrates the tractability and applicability of the design methods.
{"title":"Robust H∞ Vertex-dependent Filtering of State-delayed State-multiplicative Stochastic Systems","authors":"E. Gershon","doi":"10.1109/Control55989.2022.9781360","DOIUrl":"https://doi.org/10.1109/Control55989.2022.9781360","url":null,"abstract":"Linear state-delayed continuous-time systems with state-multiplicative noise and polytopic type parameter uncertainty are considered. We address the problem of H∞ robust filtering of these systems by applying a vertex dependent Lyapunov function that considerably reduces the over-design that is inherent to the classical design which is based on single Lyapunov function for the whole parameter range. The improved solution is based on the application of the Finsler lemma leading to a unique Lyapunov function that is assigned to each vertex of the polytope uncertainty. An example is given that demonstrates the tractability and applicability of the design methods.","PeriodicalId":101892,"journal":{"name":"2022 UKACC 13th International Conference on Control (CONTROL)","volume":"174 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124258945","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 : 2022-04-20DOI: 10.1109/Control55989.2022.9781465
Max Calcroft, A. Khan
Autonomous vehicles are redefining the transport industry – obstacle detection and avoidance are key to their operation. A number of sensor technologies have been developed and trialled. This paper presents the implementation of a Hokuyo URG-04LX Light Detection And Ranging (LiDAR) sensor on an autonomous vehicle developed with a Raspberry Pi 3B microcontroller and demonstrates its effectiveness for object detection and avoidance in varying conditions. The LiDAR sensor was integrated with the Raspberry Pi 3B using Python on LUbuntu (lightweight version of Ubuntu) and Robot Operating System (ROS). Various scenarios with low light conditions, reflective surfaces at multiple angles, simple stopping tests and different motion paths at varying speeds were tested. All tests were run at 3.2 and 4mph speed. It was found that the LiDAR sensor performed well for basic object detection but did not respond well to reflective or dark surfaces. We further compared the LiDAR’s performance with ultrasonic sensors and found that it outperformed ultrasonic sensors for stopping distances. Overall, the LiDAR acts as an effective sensor for the autonomous vehicle, showing its viability in detecting objects and acting as a small scale representation of autonomous technology.
{"title":"LiDAR-based Obstacle Detection and Avoidance for Autonomous Vehicles using Raspberry Pi 3B","authors":"Max Calcroft, A. Khan","doi":"10.1109/Control55989.2022.9781465","DOIUrl":"https://doi.org/10.1109/Control55989.2022.9781465","url":null,"abstract":"Autonomous vehicles are redefining the transport industry – obstacle detection and avoidance are key to their operation. A number of sensor technologies have been developed and trialled. This paper presents the implementation of a Hokuyo URG-04LX Light Detection And Ranging (LiDAR) sensor on an autonomous vehicle developed with a Raspberry Pi 3B microcontroller and demonstrates its effectiveness for object detection and avoidance in varying conditions. The LiDAR sensor was integrated with the Raspberry Pi 3B using Python on LUbuntu (lightweight version of Ubuntu) and Robot Operating System (ROS). Various scenarios with low light conditions, reflective surfaces at multiple angles, simple stopping tests and different motion paths at varying speeds were tested. All tests were run at 3.2 and 4mph speed. It was found that the LiDAR sensor performed well for basic object detection but did not respond well to reflective or dark surfaces. We further compared the LiDAR’s performance with ultrasonic sensors and found that it outperformed ultrasonic sensors for stopping distances. Overall, the LiDAR acts as an effective sensor for the autonomous vehicle, showing its viability in detecting objects and acting as a small scale representation of autonomous technology.","PeriodicalId":101892,"journal":{"name":"2022 UKACC 13th International Conference on Control (CONTROL)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126060721","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 : 2022-04-20DOI: 10.1109/Control55989.2022.9781456
Alfredo Peinado Gonzalo, M. Entezami, Clive Roberts, P. Weston, G. Yeo, R. Horridge, E. Stewart, M. Hayward, Matthew Rippin
Distance estimation is necessary in railway track condition monitoring to evaluate the state of the track and locate faults. To do that, this paper proposes a novel method that combines an Inertial Measurement Unit (IMU) and Global Navigation Satellite System (GNSS) to estimate distance and then correct it using track geometry features such as crosslevel as a reference. This correction is used to align the track data accurately, which helps to observe the evolution of the track over a year and to evaluate the effects of track features such as tunnels, bridges, or switches and crosses, demonstrating that the distance estimation method is reliable and allows supervision of the track.
{"title":"Observations on track evolution from onboard inertial measurements","authors":"Alfredo Peinado Gonzalo, M. Entezami, Clive Roberts, P. Weston, G. Yeo, R. Horridge, E. Stewart, M. Hayward, Matthew Rippin","doi":"10.1109/Control55989.2022.9781456","DOIUrl":"https://doi.org/10.1109/Control55989.2022.9781456","url":null,"abstract":"Distance estimation is necessary in railway track condition monitoring to evaluate the state of the track and locate faults. To do that, this paper proposes a novel method that combines an Inertial Measurement Unit (IMU) and Global Navigation Satellite System (GNSS) to estimate distance and then correct it using track geometry features such as crosslevel as a reference. This correction is used to align the track data accurately, which helps to observe the evolution of the track over a year and to evaluate the effects of track features such as tunnels, bridges, or switches and crosses, demonstrating that the distance estimation method is reliable and allows supervision of the track.","PeriodicalId":101892,"journal":{"name":"2022 UKACC 13th International Conference on Control (CONTROL)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133649373","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 : 2022-04-20DOI: 10.1109/Control55989.2022.9781437
Saikat Dutta, Ramkrishnan Ambur, O. Olaby, M. Hamadache, E. Stewart, R. Dixon
The scheduled maintenance procedure required for the safe running of a switch system is costly and often involves large time. In the changing rail network, the scheduled maintenance process is needed to be replaced with advanced condition monitoring approaches which can predict and detect degradation in the system performance and notify the operator. The present research addresses the challenge to detect any degradation or change of performance of the switch actuation system using continuous time parameter estimation method. A switch system with an electro-mechanical actuator has been considered and the developed technique is tested with changing switch parameters. A new switch actuator is now built and validated and installed in a working test switch system. The method will be tested for different unhealthy/fault scenarios with the working actuator connected to a working switch system
{"title":"Continuous Time Parameter Estimation Method for a Railway Track Switch Actuator","authors":"Saikat Dutta, Ramkrishnan Ambur, O. Olaby, M. Hamadache, E. Stewart, R. Dixon","doi":"10.1109/Control55989.2022.9781437","DOIUrl":"https://doi.org/10.1109/Control55989.2022.9781437","url":null,"abstract":"The scheduled maintenance procedure required for the safe running of a switch system is costly and often involves large time. In the changing rail network, the scheduled maintenance process is needed to be replaced with advanced condition monitoring approaches which can predict and detect degradation in the system performance and notify the operator. The present research addresses the challenge to detect any degradation or change of performance of the switch actuation system using continuous time parameter estimation method. A switch system with an electro-mechanical actuator has been considered and the developed technique is tested with changing switch parameters. A new switch actuator is now built and validated and installed in a working test switch system. The method will be tested for different unhealthy/fault scenarios with the working actuator connected to a working switch system","PeriodicalId":101892,"journal":{"name":"2022 UKACC 13th International Conference on Control (CONTROL)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115942100","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 : 2022-04-20DOI: 10.1109/Control55989.2022.9781375
B. Chen, B. Chu
High performance consensus tracking problem operating repetitively has attracted significant research interest in different fields. Recent research apply iterative learning control (ILC) for such problems, since ILC does not require a highly accurate model to achieve the high accuracy requirement (which is in contrast to most of the conventional control methodologies). However, existing ILC designs for high performance consensus tracking problem either focus on the tracking under fixed topology (while the switching topologies structure that is common used in reality has not been taken into account), or can only guarantee the convergence performance when the controller satisfies certain conditions. To address these limitations, this paper proposes a novel ILC algorithm for the high performance consensus tracking problem with switching topologies. The design of the novel performance index guarantees monotonic convergence of the tracking error norm to zero without any restriction on the controller. Furthermore, the proposed algorithm is suitable for homogeneous and heterogeneous networked systems, which is appealing in practice. A distributed implementation using the idea of the alternating direction method of multiplies for the proposed algorithm is provided, allowing the algorithm to be applied to large scale networked dynamical systems. Convergence properties of the algorithm are analysed rigorously and numerical examples are presented to show the algorithm’s effectiveness.
{"title":"Distributed Iterative Learning Control for High Performance Consensus Tracking Problem with Switching Topologies","authors":"B. Chen, B. Chu","doi":"10.1109/Control55989.2022.9781375","DOIUrl":"https://doi.org/10.1109/Control55989.2022.9781375","url":null,"abstract":"High performance consensus tracking problem operating repetitively has attracted significant research interest in different fields. Recent research apply iterative learning control (ILC) for such problems, since ILC does not require a highly accurate model to achieve the high accuracy requirement (which is in contrast to most of the conventional control methodologies). However, existing ILC designs for high performance consensus tracking problem either focus on the tracking under fixed topology (while the switching topologies structure that is common used in reality has not been taken into account), or can only guarantee the convergence performance when the controller satisfies certain conditions. To address these limitations, this paper proposes a novel ILC algorithm for the high performance consensus tracking problem with switching topologies. The design of the novel performance index guarantees monotonic convergence of the tracking error norm to zero without any restriction on the controller. Furthermore, the proposed algorithm is suitable for homogeneous and heterogeneous networked systems, which is appealing in practice. A distributed implementation using the idea of the alternating direction method of multiplies for the proposed algorithm is provided, allowing the algorithm to be applied to large scale networked dynamical systems. Convergence properties of the algorithm are analysed rigorously and numerical examples are presented to show the algorithm’s effectiveness.","PeriodicalId":101892,"journal":{"name":"2022 UKACC 13th International Conference on Control (CONTROL)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128637724","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 : 2022-04-20DOI: 10.1109/Control55989.2022.9781452
Yue Liu, Long Zhang
This paper proposes an ageing evaluation method for wind turbine system by using a data driven method. This method directly uses the input and output data of the wind turbine system, and the autoregressive with exogenous (ARX) model to identify the wind turbine system. The input and output data include wind speed, generated power, and pitch angle, and they are generated by a wind turbine simulation model with four ageing cases: mechanical power, magnetizing inductance, pitch angle controller gain and pitch angle change rate. By using the generated power and pitch angle data of wind turbine under different ageing levels, the data-driven models can be obtained. By comparing the model parameters in different states identified by the ARX model, results show that the degree of ageing can be reflected by the parameter changes. This demonstrates that the method can detect the ageing of wind turbines.
{"title":"Data-driven fault identification of ageing wind turbine*","authors":"Yue Liu, Long Zhang","doi":"10.1109/Control55989.2022.9781452","DOIUrl":"https://doi.org/10.1109/Control55989.2022.9781452","url":null,"abstract":"This paper proposes an ageing evaluation method for wind turbine system by using a data driven method. This method directly uses the input and output data of the wind turbine system, and the autoregressive with exogenous (ARX) model to identify the wind turbine system. The input and output data include wind speed, generated power, and pitch angle, and they are generated by a wind turbine simulation model with four ageing cases: mechanical power, magnetizing inductance, pitch angle controller gain and pitch angle change rate. By using the generated power and pitch angle data of wind turbine under different ageing levels, the data-driven models can be obtained. By comparing the model parameters in different states identified by the ARX model, results show that the degree of ageing can be reflected by the parameter changes. This demonstrates that the method can detect the ageing of wind turbines.","PeriodicalId":101892,"journal":{"name":"2022 UKACC 13th International Conference on Control (CONTROL)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129544885","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 : 2022-04-20DOI: 10.1109/Control55989.2022.9781460
E. Ikonen, Markus Neuvonen, István Selek, Mikko Salo, Mika Liukkonen
Estimation of power plant fuel input fractions based on unscented Kalman filtering using a first principles simulation model of the furnace is considered. The approach is described, together with experimental results using data from a full scale circulating fluidized bed power plant. The results encourage the fusion of machine learning and physical models in monitoring of industrial processes.
{"title":"On-line estimation of circulating fluidized bed boiler fuel composition","authors":"E. Ikonen, Markus Neuvonen, István Selek, Mikko Salo, Mika Liukkonen","doi":"10.1109/Control55989.2022.9781460","DOIUrl":"https://doi.org/10.1109/Control55989.2022.9781460","url":null,"abstract":"Estimation of power plant fuel input fractions based on unscented Kalman filtering using a first principles simulation model of the furnace is considered. The approach is described, together with experimental results using data from a full scale circulating fluidized bed power plant. The results encourage the fusion of machine learning and physical models in monitoring of industrial processes.","PeriodicalId":101892,"journal":{"name":"2022 UKACC 13th International Conference on Control (CONTROL)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116751765","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 : 2022-04-20DOI: 10.1109/Control55989.2022.9781373
A. Procter, Fan Zhang, J. Maddy
This paper outlines control of a hydrogen storage system attached to a tidal lagoon power generation system which meets a specific power demand pattern from the combined system to enable variable tidal power generation to be part of the renewable energy mix.The hydrogen storage system consists of an electrolyser subsystem, fuel cell subsystem and a hydrogen storage. The hydrogen storage system is controlled by a supervisory Hybrid Controller based on Mixed Logical Dynamical Model Predictive Control (MLD MPC). The optimisation sets start-stop instructions to the equipment and provides continuous references once the equipment is running to meet the control requirements. The control is based on a hydrogen balance for the system which embeds the key requirement that the overall system including equipment auxiliaries meets all its own power requirements from either the tidal lagoon or the hydrogen storage system.The simulation shows that optimisation functions meet the demand at all times, while maintaining the hydrogen storage level to allow the fuel cell to run when required to cover the demand.
{"title":"Control of a Tidal Lagoon Power Generation Hydrogen Storage System","authors":"A. Procter, Fan Zhang, J. Maddy","doi":"10.1109/Control55989.2022.9781373","DOIUrl":"https://doi.org/10.1109/Control55989.2022.9781373","url":null,"abstract":"This paper outlines control of a hydrogen storage system attached to a tidal lagoon power generation system which meets a specific power demand pattern from the combined system to enable variable tidal power generation to be part of the renewable energy mix.The hydrogen storage system consists of an electrolyser subsystem, fuel cell subsystem and a hydrogen storage. The hydrogen storage system is controlled by a supervisory Hybrid Controller based on Mixed Logical Dynamical Model Predictive Control (MLD MPC). The optimisation sets start-stop instructions to the equipment and provides continuous references once the equipment is running to meet the control requirements. The control is based on a hydrogen balance for the system which embeds the key requirement that the overall system including equipment auxiliaries meets all its own power requirements from either the tidal lagoon or the hydrogen storage system.The simulation shows that optimisation functions meet the demand at all times, while maintaining the hydrogen storage level to allow the fuel cell to run when required to cover the demand.","PeriodicalId":101892,"journal":{"name":"2022 UKACC 13th International Conference on Control (CONTROL)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115444702","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 : 2022-04-20DOI: 10.1109/Control55989.2022.9781446
Qusay Hawari, James Fleming, Taeseong Kim, Christopher Ward
This work addresses blade pitch controllers for variable speed wind turbines for the purpose of maintaining power at rated value during above rated wind speeds. The work proposes a collective proportional integral (PI) pitch controller design that accounts for the effects of low frequency aero-elastic modes to enhance the performance of the basic PI controller used in industry. Validation was performed by testing the proposed controller on a non-linear model for the DTU10MW turbine under turbulent wind conditions. Statistical analysis of fatigue loads at the main shaft bearing were further investigated to verify that the proposed controller does not add excessive loading compared with the basic controller.
{"title":"Stability Margin Analysis for PI Pitch Controllers on Large Wind Turbines","authors":"Qusay Hawari, James Fleming, Taeseong Kim, Christopher Ward","doi":"10.1109/Control55989.2022.9781446","DOIUrl":"https://doi.org/10.1109/Control55989.2022.9781446","url":null,"abstract":"This work addresses blade pitch controllers for variable speed wind turbines for the purpose of maintaining power at rated value during above rated wind speeds. The work proposes a collective proportional integral (PI) pitch controller design that accounts for the effects of low frequency aero-elastic modes to enhance the performance of the basic PI controller used in industry. Validation was performed by testing the proposed controller on a non-linear model for the DTU10MW turbine under turbulent wind conditions. Statistical analysis of fatigue loads at the main shaft bearing were further investigated to verify that the proposed controller does not add excessive loading compared with the basic controller.","PeriodicalId":101892,"journal":{"name":"2022 UKACC 13th International Conference on Control (CONTROL)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124362822","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 : 2022-04-20DOI: 10.1109/Control55989.2022.9781444
Muhammad Saleheen Aftab, John Anthony Rossiter, G. Panoutsos
Predictive functional control (PFC) is a cheap and simplified model predictive controller, which competes with PID in price and performance. While the tuning process in PFC for simple dynamics is well established and straightforward, it becomes far more ambiguous and often less effective for processes exhibiting challenging behaviour, such as poor damping, instability and/or non-minimum phase characteristics. In this paper, we present a relative PFC algorithm that, when implemented with pre-stabilised prediction dynamics if needed, simplifies performance tuning to merely adjusting one parameter. Furthermore, it provides far superior closed-loop control in practical scenarios, where the conventional PFC and PID fail to perform, as demonstrated with three simulation case studies.
{"title":"Predictive Functional Control for Difficult Dynamic Processes with a Simplified Tuning Mechanism","authors":"Muhammad Saleheen Aftab, John Anthony Rossiter, G. Panoutsos","doi":"10.1109/Control55989.2022.9781444","DOIUrl":"https://doi.org/10.1109/Control55989.2022.9781444","url":null,"abstract":"Predictive functional control (PFC) is a cheap and simplified model predictive controller, which competes with PID in price and performance. While the tuning process in PFC for simple dynamics is well established and straightforward, it becomes far more ambiguous and often less effective for processes exhibiting challenging behaviour, such as poor damping, instability and/or non-minimum phase characteristics. In this paper, we present a relative PFC algorithm that, when implemented with pre-stabilised prediction dynamics if needed, simplifies performance tuning to merely adjusting one parameter. Furthermore, it provides far superior closed-loop control in practical scenarios, where the conventional PFC and PID fail to perform, as demonstrated with three simulation case studies.","PeriodicalId":101892,"journal":{"name":"2022 UKACC 13th International Conference on Control (CONTROL)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127913992","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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