Pub Date : 2021-06-29DOI: 10.23919/ecc54610.2021.9655186
Xinyong Wang, C. Fiter, Ying Tang, L. Hetel
This work investigates the stability for a class of linear hyperbolic systems with distributed sampled-data controllers. First, we convert the original system into an equivalent system in which the sampling induced error is modeled as a reset integrator. Then by means of an appropriate Lyapunov function coupled with the Razumikhin technique, sufficient conditions are given for the Rε - stability of the system. Finally, our results are validated by a numerical example.
{"title":"Sampled-data Control for a Class of Linear Hyperbolic Systems via the Lyapunov-Razumikhin Technique*","authors":"Xinyong Wang, C. Fiter, Ying Tang, L. Hetel","doi":"10.23919/ecc54610.2021.9655186","DOIUrl":"https://doi.org/10.23919/ecc54610.2021.9655186","url":null,"abstract":"This work investigates the stability for a class of linear hyperbolic systems with distributed sampled-data controllers. First, we convert the original system into an equivalent system in which the sampling induced error is modeled as a reset integrator. Then by means of an appropriate Lyapunov function coupled with the Razumikhin technique, sufficient conditions are given for the Rε - stability of the system. Finally, our results are validated by a numerical example.","PeriodicalId":105499,"journal":{"name":"2021 European Control Conference (ECC)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131160162","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 : 2021-06-29DOI: 10.23919/ecc54610.2021.9655126
Muhammad Saleheen Aftab, J. Rossiter
Predictive functional control (PFC) is a popular industrial process control strategy, but its rather simplistic design renders it less effective in more demanding situations; for example, under-damping, open-loop instability or significant non-minimum phase characteristics have been difficult to control. Devising efficient strategies for such systems remains a topic of interest within the PFC community. This paper shows how a systematic pre-conditioning approach can improve PFC performance for under-damped systems. The proposed pre-conditioning stage is essentially an additional feedback loop whose sole purpose is to provide reliable predictions for PFC decision making. To prevent complicated performance tuning and constraints management procedures, compensator design is kept fairly simple and intuitive. Numerical studies verify the efficacy of the proposal.
{"title":"Predictive Functional Control with Explicit Pre-conditioning for Oscillatory Dynamic Systems","authors":"Muhammad Saleheen Aftab, J. Rossiter","doi":"10.23919/ecc54610.2021.9655126","DOIUrl":"https://doi.org/10.23919/ecc54610.2021.9655126","url":null,"abstract":"Predictive functional control (PFC) is a popular industrial process control strategy, but its rather simplistic design renders it less effective in more demanding situations; for example, under-damping, open-loop instability or significant non-minimum phase characteristics have been difficult to control. Devising efficient strategies for such systems remains a topic of interest within the PFC community. This paper shows how a systematic pre-conditioning approach can improve PFC performance for under-damped systems. The proposed pre-conditioning stage is essentially an additional feedback loop whose sole purpose is to provide reliable predictions for PFC decision making. To prevent complicated performance tuning and constraints management procedures, compensator design is kept fairly simple and intuitive. Numerical studies verify the efficacy of the proposal.","PeriodicalId":105499,"journal":{"name":"2021 European Control Conference (ECC)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131527963","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 : 2021-06-29DOI: 10.23919/ecc54610.2021.9655132
Jiaying Lin, Aravindaraja Puthiyavinayagam, Shuchen Liu, M. Kurowski, Jan-Jöran Gehrt, R. Zweigel, D. Abel
This paper presents a novel approach to Multi-Object-Tracking (MOT), which solves the well-known problem of maritime surveillance. We use exteroceptive sensors, such as LiDAR, and Automatic Identification System (AIS), to measure the surroundings’ Vessels. These objects are associated using evidence theory. Afterward, the proposed algorithm tracks all the objects using a new concept: each object is tracked with a respective filter bank consisting of three Adaptive Extended Kalman Filters (AEKF) as subfilters. These have the same prediction model but different correction algorithms based on various measurement sources. The covariance noise matrices are adapted based on the current measurement quality. The filter banks can overcome drawbacks such as wrong and incomplete measurements, thus improving tracking performance.We have validated the algorithm in real-world scenarios in Rostock Harbor, Germany. The proposed algorithm can track all the objects within the view simultaneously in real-time. By comparing with a reference vessel, the mean 2D position error is ca. 2 m, which is much smaller than the AIS-only solution (5 to 10 m). During the test drive, the filter bank can detect and compensate for incorrect information, such as biased AIS positioning or incomplete LiDAR measurements, to guarantee robust positioning.
{"title":"Real-time Multi-Object Tracking using Adaptive Filtering and Filter Banks for Maritime Applications","authors":"Jiaying Lin, Aravindaraja Puthiyavinayagam, Shuchen Liu, M. Kurowski, Jan-Jöran Gehrt, R. Zweigel, D. Abel","doi":"10.23919/ecc54610.2021.9655132","DOIUrl":"https://doi.org/10.23919/ecc54610.2021.9655132","url":null,"abstract":"This paper presents a novel approach to Multi-Object-Tracking (MOT), which solves the well-known problem of maritime surveillance. We use exteroceptive sensors, such as LiDAR, and Automatic Identification System (AIS), to measure the surroundings’ Vessels. These objects are associated using evidence theory. Afterward, the proposed algorithm tracks all the objects using a new concept: each object is tracked with a respective filter bank consisting of three Adaptive Extended Kalman Filters (AEKF) as subfilters. These have the same prediction model but different correction algorithms based on various measurement sources. The covariance noise matrices are adapted based on the current measurement quality. The filter banks can overcome drawbacks such as wrong and incomplete measurements, thus improving tracking performance.We have validated the algorithm in real-world scenarios in Rostock Harbor, Germany. The proposed algorithm can track all the objects within the view simultaneously in real-time. By comparing with a reference vessel, the mean 2D position error is ca. 2 m, which is much smaller than the AIS-only solution (5 to 10 m). During the test drive, the filter bank can detect and compensate for incorrect information, such as biased AIS positioning or incomplete LiDAR measurements, to guarantee robust positioning.","PeriodicalId":105499,"journal":{"name":"2021 European Control Conference (ECC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127824537","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 : 2021-06-29DOI: 10.23919/ecc54610.2021.9655105
R. Boffadossi, L. Fagiano, A. Cataldo, Marko Tanaskovic, M. Lauricella
The application of a novel approach to the routing control problem of a real de-manufacturing plant is presented. Named Hierarchical Predictive Routing Control (HPRC) and recently proposed in the literature, the approach deals with large number of integer inputs and complex temporal-logic constraints by adopting a low-level path-following strategy and a high-level predictive path allocation. Several improvements are presented, including a novel search tree exploration method, lockout detection routines, and plant-specific handling constraints. Simulation results show very good performance and small computational times even with high number of pallets and long prediction horizon values.
{"title":"Advanced Hierarchical Predictive Routing Control of a smart de-manufacturing plant","authors":"R. Boffadossi, L. Fagiano, A. Cataldo, Marko Tanaskovic, M. Lauricella","doi":"10.23919/ecc54610.2021.9655105","DOIUrl":"https://doi.org/10.23919/ecc54610.2021.9655105","url":null,"abstract":"The application of a novel approach to the routing control problem of a real de-manufacturing plant is presented. Named Hierarchical Predictive Routing Control (HPRC) and recently proposed in the literature, the approach deals with large number of integer inputs and complex temporal-logic constraints by adopting a low-level path-following strategy and a high-level predictive path allocation. Several improvements are presented, including a novel search tree exploration method, lockout detection routines, and plant-specific handling constraints. Simulation results show very good performance and small computational times even with high number of pallets and long prediction horizon values.","PeriodicalId":105499,"journal":{"name":"2021 European Control Conference (ECC)","volume":"171 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133333954","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 : 2021-06-29DOI: 10.23919/ecc54610.2021.9655037
Francesco Trotti, Eros Ghignoni, Riccardo Muradore
Planning collision-free trajectories for robotic manipulators is a quite old problem that has recently re-gained importance thanks to collaborative robotics. In scenarios where a robot is moving close to an operator, it is of paramount importance to detect obstacles (e.g. human’ arms) that must be avoided. When the environment is dynamic this problem is still challenging. In this paper we integrate a recent collision avoidance algorithm based on the efficient computation of distances between capsules and the environment into the well-known recursive Newton-Euler algorithm for computing the inverse dynamics of serial-link manipulators. This approach allows to compute repulsive torques at the joint level that guarantee collision-free motion at run-time. The proposed approach has been validated on a simulated environment using a six degrees of freedom UR5 robot.
{"title":"A Modified Recursive Newton-Euler Algorithm Embedding a Collision Avoidance Module","authors":"Francesco Trotti, Eros Ghignoni, Riccardo Muradore","doi":"10.23919/ecc54610.2021.9655037","DOIUrl":"https://doi.org/10.23919/ecc54610.2021.9655037","url":null,"abstract":"Planning collision-free trajectories for robotic manipulators is a quite old problem that has recently re-gained importance thanks to collaborative robotics. In scenarios where a robot is moving close to an operator, it is of paramount importance to detect obstacles (e.g. human’ arms) that must be avoided. When the environment is dynamic this problem is still challenging. In this paper we integrate a recent collision avoidance algorithm based on the efficient computation of distances between capsules and the environment into the well-known recursive Newton-Euler algorithm for computing the inverse dynamics of serial-link manipulators. This approach allows to compute repulsive torques at the joint level that guarantee collision-free motion at run-time. The proposed approach has been validated on a simulated environment using a six degrees of freedom UR5 robot.","PeriodicalId":105499,"journal":{"name":"2021 European Control Conference (ECC)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133932803","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 : 2021-06-29DOI: 10.23919/ecc54610.2021.9654959
B. Sulikowski, K. Gałkowski, Daniel Trzciński, E. Rogers, A. Kummert
This paper develops a class of iterative learning control (ILC) laws for a subclass of uncertain spatially interconnected systems. Model uncertainties appear both in the state and the output equation of the dynamics modeled in the 2D systems setting to which existing results are not applicable. The first stage is to write the dynamics in 2D model form. Then the stability theory for a distinct class of 2D systems known as repetitive processes is used to develop the ILC law in the case of differential dynamics. This analysis results in a design algorithm that can be applied using linear matrix inequalities.
{"title":"Robust Iterative Learning Control for Spatially Interconnected Systems using 2D Control Theory*","authors":"B. Sulikowski, K. Gałkowski, Daniel Trzciński, E. Rogers, A. Kummert","doi":"10.23919/ecc54610.2021.9654959","DOIUrl":"https://doi.org/10.23919/ecc54610.2021.9654959","url":null,"abstract":"This paper develops a class of iterative learning control (ILC) laws for a subclass of uncertain spatially interconnected systems. Model uncertainties appear both in the state and the output equation of the dynamics modeled in the 2D systems setting to which existing results are not applicable. The first stage is to write the dynamics in 2D model form. Then the stability theory for a distinct class of 2D systems known as repetitive processes is used to develop the ILC law in the case of differential dynamics. This analysis results in a design algorithm that can be applied using linear matrix inequalities.","PeriodicalId":105499,"journal":{"name":"2021 European Control Conference (ECC)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132274176","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 : 2021-06-29DOI: 10.23919/ecc54610.2021.9654884
M. Tantau, Lars Perner, M. Wielitzka
Physically motivated models of electromechanical motion systems enable model-based control theory and facilitate system interpretation. Unfortunately, the effort of modelling restricts the usage of model-based methods in many applications. Some approaches to automatically generate models from measurements choose the best model based on minimizing the residual. These model selection attempts are limited due to ambiguities in reconstructing the internal structure from the input-output behaviour because usually motion systems have only one actuator and one sensor. Often, it is unknown if the resulting model is unique or if other models with different structure would fit equally well. The set of candidate models should be designed to contain only distinguishable models but ambiguities are often unknown to the experimenter. In this paper distinguishability is investigated systematically for a class of multiple mass models representing servo positioning systems. In the analysis a new criterion for indistinguishability is used. The benefit of additional, structural sensors on distinguishability of models is demonstrated which suggests to mount them temporarily for the commissioning phase in order to facilitate the model selection. It turns out that the best results can be achieved if synergies among sensor signals are utilized.
{"title":"Distinguishability Analysis for Multiple Mass Models of Servo Systems with Commissioning Sensors","authors":"M. Tantau, Lars Perner, M. Wielitzka","doi":"10.23919/ecc54610.2021.9654884","DOIUrl":"https://doi.org/10.23919/ecc54610.2021.9654884","url":null,"abstract":"Physically motivated models of electromechanical motion systems enable model-based control theory and facilitate system interpretation. Unfortunately, the effort of modelling restricts the usage of model-based methods in many applications. Some approaches to automatically generate models from measurements choose the best model based on minimizing the residual. These model selection attempts are limited due to ambiguities in reconstructing the internal structure from the input-output behaviour because usually motion systems have only one actuator and one sensor. Often, it is unknown if the resulting model is unique or if other models with different structure would fit equally well. The set of candidate models should be designed to contain only distinguishable models but ambiguities are often unknown to the experimenter. In this paper distinguishability is investigated systematically for a class of multiple mass models representing servo positioning systems. In the analysis a new criterion for indistinguishability is used. The benefit of additional, structural sensors on distinguishability of models is demonstrated which suggests to mount them temporarily for the commissioning phase in order to facilitate the model selection. It turns out that the best results can be achieved if synergies among sensor signals are utilized.","PeriodicalId":105499,"journal":{"name":"2021 European Control Conference (ECC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134303834","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 : 2021-06-29DOI: 10.23919/ecc54610.2021.9655045
Marco Baur, L. Bascetta
The AFI model is an effective representation of vehicle lateral dynamics, particularly suitable to design linear model-based trajectory tracking controllers. As already observed in the literature, however, controllers designed on the AFI model are affected at high speed by poorly damped yaw rate oscillations, that severely hamper passenger riding comfort and safety. This paper proposes a system-theoretical analysis that explains the cause of these oscillations, and opens the way to the design of an advanced gain-scheduling controller that keeps a constant desired damping ratio independently of vehicle velocity. This controller can be used as an ADAS to increase the safety and comfort of a human driven vehicle, or as the inner loop of a cascaded control architecture in an autonomous vehicle. Simulations demonstrate the effectiveness and robustness of the proposal in damping yaw rate oscillations during a critical manoeuvre, like double-lane-change, performed at different velocities.
{"title":"High speed driving with the Affine in the Force Input model","authors":"Marco Baur, L. Bascetta","doi":"10.23919/ecc54610.2021.9655045","DOIUrl":"https://doi.org/10.23919/ecc54610.2021.9655045","url":null,"abstract":"The AFI model is an effective representation of vehicle lateral dynamics, particularly suitable to design linear model-based trajectory tracking controllers. As already observed in the literature, however, controllers designed on the AFI model are affected at high speed by poorly damped yaw rate oscillations, that severely hamper passenger riding comfort and safety. This paper proposes a system-theoretical analysis that explains the cause of these oscillations, and opens the way to the design of an advanced gain-scheduling controller that keeps a constant desired damping ratio independently of vehicle velocity. This controller can be used as an ADAS to increase the safety and comfort of a human driven vehicle, or as the inner loop of a cascaded control architecture in an autonomous vehicle. Simulations demonstrate the effectiveness and robustness of the proposal in damping yaw rate oscillations during a critical manoeuvre, like double-lane-change, performed at different velocities.","PeriodicalId":105499,"journal":{"name":"2021 European Control Conference (ECC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134154513","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 : 2021-06-29DOI: 10.23919/ecc54610.2021.9655047
Ahmad Al-Mohamad, V. Puig, G. Hoblos
A robust set-membership Prognostics and Health Management (PHM) methodology is presented in this paper. The key advantages of the set-membership approach for states and parameters estimation are enhanced by employing zonotopes that are less conservative and computationally complex than other sets. The optimal tuning of the proposed observer is formulated using the Linear Matrix Inequality (LMI) approach. Moreover, the Joint Estimation of States and Parameters (JESP) leads to a non-linear representation of a monitored system that is transformed into a Linear Parameter-Varying (LPV) system by means of the non-linear embedding approach. The considered case study is based on a slowly degraded DC-DC converter. The aim of the proposed PHM approach is to forecast the Remaining Useful Life (RUL) on a system level. Additionally, the proposed RUL forecasting approach is independent of previous knowledge of the degradation behaviors being only dependent on the estimated zonotopic parameters. Finally, the obtained results demonstrate the efficiency of the proposed approach.
{"title":"Robust Zonotopic Set-Membership Approach for Model-Based Prognosis: Application on Linear Parameter-Varying Systems","authors":"Ahmad Al-Mohamad, V. Puig, G. Hoblos","doi":"10.23919/ecc54610.2021.9655047","DOIUrl":"https://doi.org/10.23919/ecc54610.2021.9655047","url":null,"abstract":"A robust set-membership Prognostics and Health Management (PHM) methodology is presented in this paper. The key advantages of the set-membership approach for states and parameters estimation are enhanced by employing zonotopes that are less conservative and computationally complex than other sets. The optimal tuning of the proposed observer is formulated using the Linear Matrix Inequality (LMI) approach. Moreover, the Joint Estimation of States and Parameters (JESP) leads to a non-linear representation of a monitored system that is transformed into a Linear Parameter-Varying (LPV) system by means of the non-linear embedding approach. The considered case study is based on a slowly degraded DC-DC converter. The aim of the proposed PHM approach is to forecast the Remaining Useful Life (RUL) on a system level. Additionally, the proposed RUL forecasting approach is independent of previous knowledge of the degradation behaviors being only dependent on the estimated zonotopic parameters. Finally, the obtained results demonstrate the efficiency of the proposed approach.","PeriodicalId":105499,"journal":{"name":"2021 European Control Conference (ECC)","volume":"86 18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133831585","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 : 2021-06-29DOI: 10.23919/ecc54610.2021.9655150
P. Chanfreut, A. Sánchez-Amores, J. Maestre, E. Camacho
This work deals with the application of neural networks to speed up the convergence of a distributed model predictive control (DMPC) algorithm based on dual decomposition. While dual decomposition methods are known to converge to the centralized MPC solution, numerous iterations may be required before convergence is attained, thus increasing computation and communication burden. In this paper, a database containing system states and optimal Lagrange multipliers is created offline to train a neural network, which is incorporated into the online operation of the distributed system. Numerical results on an input-coupled 16 tanks benchmark are provided.
{"title":"Distributed Model Predictive Control based on Dual Decomposition with Neural-Network-based Warm Start","authors":"P. Chanfreut, A. Sánchez-Amores, J. Maestre, E. Camacho","doi":"10.23919/ecc54610.2021.9655150","DOIUrl":"https://doi.org/10.23919/ecc54610.2021.9655150","url":null,"abstract":"This work deals with the application of neural networks to speed up the convergence of a distributed model predictive control (DMPC) algorithm based on dual decomposition. While dual decomposition methods are known to converge to the centralized MPC solution, numerous iterations may be required before convergence is attained, thus increasing computation and communication burden. In this paper, a database containing system states and optimal Lagrange multipliers is created offline to train a neural network, which is incorporated into the online operation of the distributed system. Numerical results on an input-coupled 16 tanks benchmark are provided.","PeriodicalId":105499,"journal":{"name":"2021 European Control Conference (ECC)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115216311","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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