Pub Date : 2018-08-01DOI: 10.1109/CCTA.2018.8511402
Daniele Di Vito, E. Cataldi, P. D. Lillo, G. Antonelli
This paper investigates the effects of including the thruster dynamics within the full-dimensional adaptive control of an underwater vehicle. In particular, the intervention case, i.e., small movements around a steady reference trajectory and the presence of the ocean current, are of interest. The thruster dynamics influences the closed loop causing undesirable effects if not properly taken into account. Furthermore, as known, the adaptive control can fail if the performed trajectory is not sufficiently exciting causing eventually the dynamic parameters drift and bursting phenomena. Therefore, for the intervention case, these drawbacks of the adaptive control have to be considered. In particular, a reduced version of the controller, taking into account only the persistent dynamic effects, is implemented. Finally, numerical simulations validate the discussion made.
{"title":"Vehicle Adaptive Control for Underwater Intervention Including Thrusters Dynamics","authors":"Daniele Di Vito, E. Cataldi, P. D. Lillo, G. Antonelli","doi":"10.1109/CCTA.2018.8511402","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511402","url":null,"abstract":"This paper investigates the effects of including the thruster dynamics within the full-dimensional adaptive control of an underwater vehicle. In particular, the intervention case, i.e., small movements around a steady reference trajectory and the presence of the ocean current, are of interest. The thruster dynamics influences the closed loop causing undesirable effects if not properly taken into account. Furthermore, as known, the adaptive control can fail if the performed trajectory is not sufficiently exciting causing eventually the dynamic parameters drift and bursting phenomena. Therefore, for the intervention case, these drawbacks of the adaptive control have to be considered. In particular, a reduced version of the controller, taking into account only the persistent dynamic effects, is implemented. Finally, numerical simulations validate the discussion made.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116117258","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 : 2018-08-01DOI: 10.1109/CCTA.2018.8511524
E. Mojica-Nava, Christian Feudjio, A. Wouwer
The activated sludge process is a complex microbial system used for biological wastewater treatment, i.e., carbon and ammonium removal. The main control objective is to regulate the outflow water quality despite disturbances in the inflow, such as influent flow, or influent concentration. The alternate phase process consists of a single bioreactor where oxygen is supplied intermittently to create nitrification and denitrification conditions while the biomass is recycled continuously from a settler. In this study, a switched affine model is first derived from an existing dynamic model. Then, a switching signal law and a feedback control are developed to reduce the ammonium concentration while keeping the closed-loop system stable. The proposed control strategy is validated in simulation with MATLAB/Simulink considering several influent scenarios such as dry, rainy, and stormy weather conditions.
{"title":"Switching Control of an Activated Sludge Process","authors":"E. Mojica-Nava, Christian Feudjio, A. Wouwer","doi":"10.1109/CCTA.2018.8511524","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511524","url":null,"abstract":"The activated sludge process is a complex microbial system used for biological wastewater treatment, i.e., carbon and ammonium removal. The main control objective is to regulate the outflow water quality despite disturbances in the inflow, such as influent flow, or influent concentration. The alternate phase process consists of a single bioreactor where oxygen is supplied intermittently to create nitrification and denitrification conditions while the biomass is recycled continuously from a settler. In this study, a switched affine model is first derived from an existing dynamic model. Then, a switching signal law and a feedback control are developed to reduce the ammonium concentration while keeping the closed-loop system stable. The proposed control strategy is validated in simulation with MATLAB/Simulink considering several influent scenarios such as dry, rainy, and stormy weather conditions.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"24 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120987799","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 : 2018-08-01DOI: 10.1109/CCTA.2018.8511096
F. Walz, Tobias Schucht, J. Reger, S. Hohmann
With automated driving, new challenges for vehicle longitudinal motion control arise. The precise control of speed and acceleration requires knowledge of the torques acting at the wheels. In this work we present an observer that estimates the shaft torques of an all-wheel-drive vehicle and pay attention to the especially challenging use case of driving over large obstacles like curb stones. The performance of our observer is compared with two other approaches and verified using realworld measurement data. The results show that the observer provides good estimates and cooperates well with the switching system. The all-wheel-drive specific, fundamental reallocation of drive torque due to the differential lock in the transfer case is also covered.
{"title":"Shaft Torque and Backlash Estimation for Longitudinal Motion Control of All-Wheel-Drive Vehicles","authors":"F. Walz, Tobias Schucht, J. Reger, S. Hohmann","doi":"10.1109/CCTA.2018.8511096","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511096","url":null,"abstract":"With automated driving, new challenges for vehicle longitudinal motion control arise. The precise control of speed and acceleration requires knowledge of the torques acting at the wheels. In this work we present an observer that estimates the shaft torques of an all-wheel-drive vehicle and pay attention to the especially challenging use case of driving over large obstacles like curb stones. The performance of our observer is compared with two other approaches and verified using realworld measurement data. The results show that the observer provides good estimates and cooperates well with the switching system. The all-wheel-drive specific, fundamental reallocation of drive torque due to the differential lock in the transfer case is also covered.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116740787","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 : 2018-08-01DOI: 10.1109/CCTA.2018.8511513
T. Jensen, C. Kallesøe, J. Bendtsen, R. Wisniewski
Proper management of pressure in water distribution networks is important, since leakages are more likely to occur if the pressure in the network is unnecessarily high with the consequence that the produced water is wasted. Furthermore, too low pressure will lead to reduced comfort of end-users and a potential increased risk of pollutants entering the network. In this paper, we investigate control actions for management of pressure in water distribution networks with multiple inlets. In particular, the problem of controlling the pressure at the network inlets to accommodate pressure requirements at designated network vertices, where the pressure is measured, is addressed. In this paper, we propose an Iterative Learning type control structure, as the behaviour of the consumers in water distribution networks is typically periodic in nature. Numerical and experimental results show that the proposed controller is able to fulfil the requirements.
{"title":"Iterative Learning Pressure Control in Water Distribution Networks","authors":"T. Jensen, C. Kallesøe, J. Bendtsen, R. Wisniewski","doi":"10.1109/CCTA.2018.8511513","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511513","url":null,"abstract":"Proper management of pressure in water distribution networks is important, since leakages are more likely to occur if the pressure in the network is unnecessarily high with the consequence that the produced water is wasted. Furthermore, too low pressure will lead to reduced comfort of end-users and a potential increased risk of pollutants entering the network. In this paper, we investigate control actions for management of pressure in water distribution networks with multiple inlets. In particular, the problem of controlling the pressure at the network inlets to accommodate pressure requirements at designated network vertices, where the pressure is measured, is addressed. In this paper, we propose an Iterative Learning type control structure, as the behaviour of the consumers in water distribution networks is typically periodic in nature. Numerical and experimental results show that the proposed controller is able to fulfil the requirements.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124921713","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 : 2018-08-01DOI: 10.1109/CCTA.2018.8511338
S. H. Kamali, M. Moallem, S. Arzanpour
In this paper, an electromechanical actuator is utilized for bidirectional power flow in a tuned mass damper (TMD). The actuator force is controlled to achieve desired mechanical damping and stiffness values for the whole system by controlling the current using a power electronic converter. The resulting TMD can autonomously change its damping and stiffness values to minimize a host structure's displacement under different excitation frequencies. A multi-variable sliding mode extremum-seeking algorithm is used to tune the TMD damping and stiffness levels to optimal values. Analytic and simulation results show that the active TMD exhibits better performance when compared to non-adaptive and robust TMDs.
{"title":"Self-Tuning Active Tuned Mass Damper Utilizing Constrained Multi-Variable Sliding Mode Extremum-Seeking","authors":"S. H. Kamali, M. Moallem, S. Arzanpour","doi":"10.1109/CCTA.2018.8511338","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511338","url":null,"abstract":"In this paper, an electromechanical actuator is utilized for bidirectional power flow in a tuned mass damper (TMD). The actuator force is controlled to achieve desired mechanical damping and stiffness values for the whole system by controlling the current using a power electronic converter. The resulting TMD can autonomously change its damping and stiffness values to minimize a host structure's displacement under different excitation frequencies. A multi-variable sliding mode extremum-seeking algorithm is used to tune the TMD damping and stiffness levels to optimal values. Analytic and simulation results show that the active TMD exhibits better performance when compared to non-adaptive and robust TMDs.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125113025","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 : 2018-08-01DOI: 10.1109/CCTA.2018.8511553
P. Segovia, L. Rajaoarisoa, F. Nejjari, E. Duviella, V. Puig
Inland waterways are large-scale systems, generally characterized by negligible bottom slopes and large time delays. These features pose challenging problems at the modeling and controller design stages. A control-oriented model is derived in this work, which allows to handle these issues in a suitable manner. A predictive control scheme is developed to ensure the coordination of the control actions and their delayed effects in the system. The proposed approach is tested on a case study to highlight its performance, and it is shown that it is possible to guarantee the navigability condition of the waterways as well as other operational goals.
{"title":"Input-Delay Model Predictive Control of Inland Waterways Considering the Backwater Effect","authors":"P. Segovia, L. Rajaoarisoa, F. Nejjari, E. Duviella, V. Puig","doi":"10.1109/CCTA.2018.8511553","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511553","url":null,"abstract":"Inland waterways are large-scale systems, generally characterized by negligible bottom slopes and large time delays. These features pose challenging problems at the modeling and controller design stages. A control-oriented model is derived in this work, which allows to handle these issues in a suitable manner. A predictive control scheme is developed to ensure the coordination of the control actions and their delayed effects in the system. The proposed approach is tested on a case study to highlight its performance, and it is shown that it is possible to guarantee the navigability condition of the waterways as well as other operational goals.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125098562","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 : 2018-08-01DOI: 10.1109/CCTA.2018.8511428
T. Besselmann, Pieder Jorg, Sture Van de Moortel
This paper is concerned with the control and operation of load commutated inverter-fed synchronous machines, and in particular with the selection of the firing angles on the machine side of the load commutated inverter. An extension to the previously published Model Predictive Torque Control was developed, which improves the operation of load commutated inverters at steady state. The main benefits of applying this control method are an improved power factor and reduced reactive power consumption, with a simultaneous increase of drive efficiency and reduction of the harmonic content of the line side currents and of the air gap torque. Further, the stator and field currents are reduced, reducing the temperatures in the machine and the transformer, which ultimately increases the lifetime of the equipment. Alternatively, the power factor improvements can be utilized for increasing the output power of the synchronous machines. The findings are validated on a reference industrial site comprising three load commutated inverter-fed synchronous machines with a nominal shaft power of 7.5 MW each.
{"title":"Power Factor Improvements for Load Commutated Inverters","authors":"T. Besselmann, Pieder Jorg, Sture Van de Moortel","doi":"10.1109/CCTA.2018.8511428","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511428","url":null,"abstract":"This paper is concerned with the control and operation of load commutated inverter-fed synchronous machines, and in particular with the selection of the firing angles on the machine side of the load commutated inverter. An extension to the previously published Model Predictive Torque Control was developed, which improves the operation of load commutated inverters at steady state. The main benefits of applying this control method are an improved power factor and reduced reactive power consumption, with a simultaneous increase of drive efficiency and reduction of the harmonic content of the line side currents and of the air gap torque. Further, the stator and field currents are reduced, reducing the temperatures in the machine and the transformer, which ultimately increases the lifetime of the equipment. Alternatively, the power factor improvements can be utilized for increasing the output power of the synchronous machines. The findings are validated on a reference industrial site comprising three load commutated inverter-fed synchronous machines with a nominal shaft power of 7.5 MW each.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125601914","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 : 2018-08-01DOI: 10.1109/CCTA.2018.8511410
C. Mandrioli, A. Leva, M. Maggio
Big Data Applications (BDAs) manage so much data to require a cluster of machines for computation and storage. Their execution often has temporal constraints, such as deadlines to process the data. BDAs are executed within Big Data Frameworks (BDFs), that provide mechanisms to automatically manage the complexity of the computation distribution. For a BDA to fulfill its deadline when executed in a BDF, online dynamic resource allocation policies should be in place. The introduction of control for such resource allocation calls for formal verification of the closed-loop system. Model checkers verify the correct behaviour of programs, and in principle they could be used to prove properties on the BDF execution. However, the complexity of BDFs makes it infeasible to directly model the BDAs and BDFs. We propose a formalism to associate the execution of a BDA with afirst-principle dynamic simulation model that can be used for model checking in the place of the real application, making the verification viable in practice. We introduce our formalism, apply it to a well assessed framework, and test its capabilities. We show that our solution is able to capture the dynamics and prove properties of the BDA execution using a stochastic model checker.
{"title":"Dynamic Models for the Formal Verification of Big Data Applications Via Stochastic Model Checking","authors":"C. Mandrioli, A. Leva, M. Maggio","doi":"10.1109/CCTA.2018.8511410","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511410","url":null,"abstract":"Big Data Applications (BDAs) manage so much data to require a cluster of machines for computation and storage. Their execution often has temporal constraints, such as deadlines to process the data. BDAs are executed within Big Data Frameworks (BDFs), that provide mechanisms to automatically manage the complexity of the computation distribution. For a BDA to fulfill its deadline when executed in a BDF, online dynamic resource allocation policies should be in place. The introduction of control for such resource allocation calls for formal verification of the closed-loop system. Model checkers verify the correct behaviour of programs, and in principle they could be used to prove properties on the BDF execution. However, the complexity of BDFs makes it infeasible to directly model the BDAs and BDFs. We propose a formalism to associate the execution of a BDA with afirst-principle dynamic simulation model that can be used for model checking in the place of the real application, making the verification viable in practice. We introduce our formalism, apply it to a well assessed framework, and test its capabilities. We show that our solution is able to capture the dynamics and prove properties of the BDA execution using a stochastic model checker.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"189 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113982006","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 : 2018-08-01DOI: 10.1109/CCTA.2018.8511637
Rin Takano, M. Yamakita
A lot of kinds of constraints must be considered to control real systems. In particular, state constraints are closely related to safety and stability of systems. Therefore, many researchers have proposed controllers to achieve good control performances without violating given state constraints. Recently, a new method to solve such constraint control problems has been proposed, which is called Control Lyapunov Function and Control Barrier Function based Quadratic Programs (CLF-CBF-QP). This method calculates an optimal control input by solving a quadratic problem under two kinds of constraints for output zeroing control and satisfying given constraints. It can achieve good control performances in the nominal case, however it is impossible to achieve good results in the presence of disturbances. This paper proposes a robust CLF-CBF -QP controller with Unscented Kalman Filter (UKF) which has an ability to attenuate effects of state disturbances and measurement noises.
{"title":"Robust Constrained Stabilization Control Using Control Lyapunov and Control Barrier Function in the Presence of Measurement Noises","authors":"Rin Takano, M. Yamakita","doi":"10.1109/CCTA.2018.8511637","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511637","url":null,"abstract":"A lot of kinds of constraints must be considered to control real systems. In particular, state constraints are closely related to safety and stability of systems. Therefore, many researchers have proposed controllers to achieve good control performances without violating given state constraints. Recently, a new method to solve such constraint control problems has been proposed, which is called Control Lyapunov Function and Control Barrier Function based Quadratic Programs (CLF-CBF-QP). This method calculates an optimal control input by solving a quadratic problem under two kinds of constraints for output zeroing control and satisfying given constraints. It can achieve good control performances in the nominal case, however it is impossible to achieve good results in the presence of disturbances. This paper proposes a robust CLF-CBF -QP controller with Unscented Kalman Filter (UKF) which has an ability to attenuate effects of state disturbances and measurement noises.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"68 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132359054","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 : 2018-08-01DOI: 10.1109/CCTA.2018.8511456
Sayak Mukherjee, Nan Xue, A. Chakrabortty
The majority of control designs for wind power systems rest upon the simplifying assumption that every wind turbine and generator (WTG) inside a wind farm has identical dynamics, and, hence, can be aggregated into a single WTG admitting a single controller. In reality, however, this assumption does not hold because of wake effect due to which the small-signal models of turbines in a given row may be similar, but those between different rows can be significantly dissimilar. In this paper we propose a hierarchical control design to address these types of heterogeneous models of WTGs in a wind farm. Our approach is to group all turbines in a row as a cluster, design a cluster-level aggregate controller by averaging of states, make these aggregate controllers exchange average state information through a local communication network, and thereafter project the aggregate controller back to the original WTGs for implementation. Simulations validating the effectiveness of this hierarchical controller are shown for the IEEE 68-bus benchmark power system with one wind farm.
{"title":"A Hierarchical Design for Damping Control of Wind-Integrated Power Systems Considering Heterogeneous Wind Farm Dynamics","authors":"Sayak Mukherjee, Nan Xue, A. Chakrabortty","doi":"10.1109/CCTA.2018.8511456","DOIUrl":"https://doi.org/10.1109/CCTA.2018.8511456","url":null,"abstract":"The majority of control designs for wind power systems rest upon the simplifying assumption that every wind turbine and generator (WTG) inside a wind farm has identical dynamics, and, hence, can be aggregated into a single WTG admitting a single controller. In reality, however, this assumption does not hold because of wake effect due to which the small-signal models of turbines in a given row may be similar, but those between different rows can be significantly dissimilar. In this paper we propose a hierarchical control design to address these types of heterogeneous models of WTGs in a wind farm. Our approach is to group all turbines in a row as a cluster, design a cluster-level aggregate controller by averaging of states, make these aggregate controllers exchange average state information through a local communication network, and thereafter project the aggregate controller back to the original WTGs for implementation. Simulations validating the effectiveness of this hierarchical controller are shown for the IEEE 68-bus benchmark power system with one wind farm.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132656115","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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