Pub Date : 2016-10-01DOI: 10.1080/23335777.2016.1244562
T. Yucelen, W. Haddad, E. Feron
The accuracy of sensor measurements is critical to the design of high performance control systems since sensor uncertainties can significantly deteriorate achievable closed-loop dynamical system performance. Sensor uncertainty can arise due to low sensor quality, sensor failure, or detrimental environmental conditions. For example, relatively cheap sensor suites are used for low-cost, small-scale unmanned vehicle applications that can result in inaccurate sensor measurements. Alternatively, sensor measurements can also be corrupted by malicious attacks if dynamical systems are controlled through large-scale, multilayered communication networks as is the case in cyber-physical systems. This paper presents several adaptive control architectures for stabilization of linear dynamical systems in the presence of sensor uncertainty and sensor attacks. Specifically, we propose new and novel adaptive controllers for state-independent and state-dependent sensor uncertainties. In particular, we show that the proposed controllers guarantee asymptotic stability of the closed-loop dynamical system when the sensor uncertainties are time-invariant and uniform ultimate boundedness when the uncertainties are time-varying. We further discuss the practicality of the proposed approaches and provide a numerical example to illustrate the efficacy of the proposed adaptive control architectures.
{"title":"Adaptive control architectures for mitigating sensor attacks in cyber-physical systems","authors":"T. Yucelen, W. Haddad, E. Feron","doi":"10.1080/23335777.2016.1244562","DOIUrl":"https://doi.org/10.1080/23335777.2016.1244562","url":null,"abstract":"The accuracy of sensor measurements is critical to the design of high performance control systems since sensor uncertainties can significantly deteriorate achievable closed-loop dynamical system performance. Sensor uncertainty can arise due to low sensor quality, sensor failure, or detrimental environmental conditions. For example, relatively cheap sensor suites are used for low-cost, small-scale unmanned vehicle applications that can result in inaccurate sensor measurements. Alternatively, sensor measurements can also be corrupted by malicious attacks if dynamical systems are controlled through large-scale, multilayered communication networks as is the case in cyber-physical systems. This paper presents several adaptive control architectures for stabilization of linear dynamical systems in the presence of sensor uncertainty and sensor attacks. Specifically, we propose new and novel adaptive controllers for state-independent and state-dependent sensor uncertainties. In particular, we show that the proposed controllers guarantee asymptotic stability of the closed-loop dynamical system when the sensor uncertainties are time-invariant and uniform ultimate boundedness when the uncertainties are time-varying. We further discuss the practicality of the proposed approaches and provide a numerical example to illustrate the efficacy of the proposed adaptive control architectures.","PeriodicalId":137983,"journal":{"name":"2016 American Control Conference (ACC)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115700006","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 : 2016-08-03DOI: 10.1109/ACC.2016.7526829
B. Postlethwaite
PISim is a new piece of software for process control teaching and learning. The software allows control structures to be designed on a piping and instrumentation diagram and, as the structure is created, the software automatically spawns device mimics representing the real physical HMIs that operators would see. These can be placed on a control panel and a simulation of the process can be operated using the student's control scheme. The use of PISim in an introductory control class at Strathclyde University is described and student feedback is presented.
{"title":"The use of simulation in chemical process control learning and the development of PISim","authors":"B. Postlethwaite","doi":"10.1109/ACC.2016.7526829","DOIUrl":"https://doi.org/10.1109/ACC.2016.7526829","url":null,"abstract":"PISim is a new piece of software for process control teaching and learning. The software allows control structures to be designed on a piping and instrumentation diagram and, as the structure is created, the software automatically spawns device mimics representing the real physical HMIs that operators would see. These can be placed on a control panel and a simulation of the process can be operated using the student's control scheme. The use of PISim in an introductory control class at Strathclyde University is described and student feedback is presented.","PeriodicalId":137983,"journal":{"name":"2016 American Control Conference (ACC)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116797270","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 : 2016-08-01DOI: 10.1109/ACC.2016.7525344
H. Pfifer, T. Péni
A model-reduction method for linear, parameter-varying (LPV) systems based on parameter-varying balanced realizations is proposed. In general, this requires the solution of a large set of linear matrix inequalities, leading to numerical issues and high computational cost. It has been recognized recently that semidefinite optimization problems (SDP) can be cast into second order cone programs (SOCP) by replacing the positive definiteness constraints with stronger, scaled diagonal dominance conditions. Since the scalability of SOCP solvers is much better than that of the SDPs, the new formulation allows solving large scale model reduction problems more efficiently. A numerical example is provided to demonstrate the efficiency of the approach.
{"title":"Model reduction for linear parameter varying systems using scaled diagonal dominance","authors":"H. Pfifer, T. Péni","doi":"10.1109/ACC.2016.7525344","DOIUrl":"https://doi.org/10.1109/ACC.2016.7525344","url":null,"abstract":"A model-reduction method for linear, parameter-varying (LPV) systems based on parameter-varying balanced realizations is proposed. In general, this requires the solution of a large set of linear matrix inequalities, leading to numerical issues and high computational cost. It has been recognized recently that semidefinite optimization problems (SDP) can be cast into second order cone programs (SOCP) by replacing the positive definiteness constraints with stronger, scaled diagonal dominance conditions. Since the scalability of SOCP solvers is much better than that of the SDPs, the new formulation allows solving large scale model reduction problems more efficiently. A numerical example is provided to demonstrate the efficiency of the approach.","PeriodicalId":137983,"journal":{"name":"2016 American Control Conference (ACC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132680911","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 : 2016-08-01DOI: 10.1109/ACC.2016.7525159
D. Opila
This paper incorporates uncertain future route predictions, destinations, and charging locations with associated speed and grade profiles into the energy management control of alternative powertrains like hybrid, plug-in, electric, and fuel cell vehicles. The method allows the combination of other sources of uncertain information like markov driver models, historic speed information, and real-time traffic predictions. This flexibility allows the consideration of a variety of information cases like uncertain traffic/speed and route information, multiple possible destinations, stopping points, and charging locations, simple range estimates to the destination, and no future knowledge at all. The model can be used with any vehicle type and stochastic control method, and is suitable for real-time calculations either on the vehicle or a server. Two techniques are also presented to reduce the computational complexity of the problem. This approach is demonstrated on a simulated trip with two possible destinations using the stochastic dynamic programming algorithm.
{"title":"Uncertain route, destination, and traffic predictions in energy management for hybrid, plug-in, and fuel-cell vehicles","authors":"D. Opila","doi":"10.1109/ACC.2016.7525159","DOIUrl":"https://doi.org/10.1109/ACC.2016.7525159","url":null,"abstract":"This paper incorporates uncertain future route predictions, destinations, and charging locations with associated speed and grade profiles into the energy management control of alternative powertrains like hybrid, plug-in, electric, and fuel cell vehicles. The method allows the combination of other sources of uncertain information like markov driver models, historic speed information, and real-time traffic predictions. This flexibility allows the consideration of a variety of information cases like uncertain traffic/speed and route information, multiple possible destinations, stopping points, and charging locations, simple range estimates to the destination, and no future knowledge at all. The model can be used with any vehicle type and stochastic control method, and is suitable for real-time calculations either on the vehicle or a server. Two techniques are also presented to reduce the computational complexity of the problem. This approach is demonstrated on a simulated trip with two possible destinations using the stochastic dynamic programming algorithm.","PeriodicalId":137983,"journal":{"name":"2016 American Control Conference (ACC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127841943","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 : 2016-08-01DOI: 10.1109/ACC.2016.7526126
Ruzhou Yang, M. Queiroz
This paper considers the lower leg limb motion tracking problem that is inherent to neuromuscular electrical stimulation systems. We propose an adaptive controller that compensates for the unknown parameters that appear nonlinearly in the mechanical dynamics. This is accomplished by exploiting the Lipschitzian properties of nonlinearly parameterized functions. The resulting discontinuous control law ensures asymptotic tracking for the lower leg limb angular position without violating its physical limits. Simulations demonstrate the control performance.
{"title":"Adaptive control of the nonlinearly parameterized limb dynamics with application to neuromuscular electrical stimulation","authors":"Ruzhou Yang, M. Queiroz","doi":"10.1109/ACC.2016.7526126","DOIUrl":"https://doi.org/10.1109/ACC.2016.7526126","url":null,"abstract":"This paper considers the lower leg limb motion tracking problem that is inherent to neuromuscular electrical stimulation systems. We propose an adaptive controller that compensates for the unknown parameters that appear nonlinearly in the mechanical dynamics. This is accomplished by exploiting the Lipschitzian properties of nonlinearly parameterized functions. The resulting discontinuous control law ensures asymptotic tracking for the lower leg limb angular position without violating its physical limits. Simulations demonstrate the control performance.","PeriodicalId":137983,"journal":{"name":"2016 American Control Conference (ACC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134498175","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 : 2016-08-01DOI: 10.1109/ACC.2016.7525583
Dezong Zhao, E. Winward, Zhijia Yang, R. Stobart, T. Steffen
Engine electrification is a critical technology in the promotion of engine fuel efficiency, among which the electrified turbocharger is regarded as a promising solution for its advantages in engine downsizing and exhaust gas energy recovery. By installing electrical devices on the turbocharger, the excess energy can be captured, stored, and re-used. The control of the energy flows in an electrified turbocharged diesel engine (ETDE) is still in its infancy. Developing a promising multi-input multi-output (MIMO) control strategy is essential in exploring the maximum benefits of electrified turbocharger. In this paper, the dynamics in an ETDE, especially the couplings among multiple loops in the air path are analyzed. Based on the analysis, a model-based MIMO decoupling control framework is designed to regulate the air path dynamics. The proposed control strategy can achieve fast and accurate tracking on selected control variables and is successfully validated on a physical model in simulations.
{"title":"Decoupling control of electrified turbocharged diesel engines","authors":"Dezong Zhao, E. Winward, Zhijia Yang, R. Stobart, T. Steffen","doi":"10.1109/ACC.2016.7525583","DOIUrl":"https://doi.org/10.1109/ACC.2016.7525583","url":null,"abstract":"Engine electrification is a critical technology in the promotion of engine fuel efficiency, among which the electrified turbocharger is regarded as a promising solution for its advantages in engine downsizing and exhaust gas energy recovery. By installing electrical devices on the turbocharger, the excess energy can be captured, stored, and re-used. The control of the energy flows in an electrified turbocharged diesel engine (ETDE) is still in its infancy. Developing a promising multi-input multi-output (MIMO) control strategy is essential in exploring the maximum benefits of electrified turbocharger. In this paper, the dynamics in an ETDE, especially the couplings among multiple loops in the air path are analyzed. Based on the analysis, a model-based MIMO decoupling control framework is designed to regulate the air path dynamics. The proposed control strategy can achieve fast and accurate tracking on selected control variables and is successfully validated on a physical model in simulations.","PeriodicalId":137983,"journal":{"name":"2016 American Control Conference (ACC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115096203","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 : 2016-08-01DOI: 10.1109/ACC.2016.7526816
K. Kashima
The practical applicability of control theoretic model reduction methods is still limited to linear middle-scale systems. This shows a clear contrast to the Proper Orthogonal Decomposition (POD), which is a simulation-based model reduction method that has been widely applied to nonlinear large-scale systems, but with no theoretical underpinnings for its application to controlled systems. In this paper, we show that these controllability-based and simulation-based methodologies are equivalent when the input port is open to a noisy environment.
{"title":"Optimality of simulation-based nonlinear model reduction: Stochastic controllability perspective","authors":"K. Kashima","doi":"10.1109/ACC.2016.7526816","DOIUrl":"https://doi.org/10.1109/ACC.2016.7526816","url":null,"abstract":"The practical applicability of control theoretic model reduction methods is still limited to linear middle-scale systems. This shows a clear contrast to the Proper Orthogonal Decomposition (POD), which is a simulation-based model reduction method that has been widely applied to nonlinear large-scale systems, but with no theoretical underpinnings for its application to controlled systems. In this paper, we show that these controllability-based and simulation-based methodologies are equivalent when the input port is open to a noisy environment.","PeriodicalId":137983,"journal":{"name":"2016 American Control Conference (ACC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129041691","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 : 2016-08-01DOI: 10.1109/ACC.2016.7526560
A. Satici, Fabio Ruggiero, V. Lippiello, B. Siciliano
Research on bipedal locomotion has shown that a dynamic walking gait is energetically more efficient than a statically stable one. Analogously, even though statically stable multi-wheeled robots are easier to control, they are energetically less efficient and have low accelerations to avoid tipping over. In contrast, the ballbot is an underactuated, nonholonomically constrained mobile robot, upward equilibrium point of whose body has to stabilized by active controls. In this work, we derive coordinate-invariant equations of motion for the ballbot. We present the linearized equations of motion followed by its controllability analysis. Excluding the rotary degree of freedom of the ball in the inertial vertical direction, the linear system turns out to be controllable. It follows that the nonlinear system is locally controllable and we provide a proportional-derivative type controller that locally exponentially stabilizes the upward equilibrium point as well as the translation of the ball. The basin of attraction turns out to be large in the simulation studies.
{"title":"Intrinsic Euler-Lagrange dynamics and control analysis of the ballbot","authors":"A. Satici, Fabio Ruggiero, V. Lippiello, B. Siciliano","doi":"10.1109/ACC.2016.7526560","DOIUrl":"https://doi.org/10.1109/ACC.2016.7526560","url":null,"abstract":"Research on bipedal locomotion has shown that a dynamic walking gait is energetically more efficient than a statically stable one. Analogously, even though statically stable multi-wheeled robots are easier to control, they are energetically less efficient and have low accelerations to avoid tipping over. In contrast, the ballbot is an underactuated, nonholonomically constrained mobile robot, upward equilibrium point of whose body has to stabilized by active controls. In this work, we derive coordinate-invariant equations of motion for the ballbot. We present the linearized equations of motion followed by its controllability analysis. Excluding the rotary degree of freedom of the ball in the inertial vertical direction, the linear system turns out to be controllable. It follows that the nonlinear system is locally controllable and we provide a proportional-derivative type controller that locally exponentially stabilizes the upward equilibrium point as well as the translation of the ball. The basin of attraction turns out to be large in the simulation studies.","PeriodicalId":137983,"journal":{"name":"2016 American Control Conference (ACC)","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115215009","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 : 2016-08-01DOI: 10.1109/ACC.2016.7524943
W. Paszke, E. Rogers, K. Gałkowski
This paper considers the design of iterative learning control laws for systems whose state-space model matrices are functions of a vector of varying parameters. The repetitive process setting is exploited to develop a linear matrix inequality based procedure for computing gain-scheduling feedback and feedforward (learning) controllers. These controllers guarantee acceptable dynamics along the trials and ensure monotonic convergence of the trial-to-trial error dynamics, respectively. A simulation example is given to illustrate the theoretical developments.
{"title":"LMI-based gain scheduled ILC design for linear parameter-varying systems","authors":"W. Paszke, E. Rogers, K. Gałkowski","doi":"10.1109/ACC.2016.7524943","DOIUrl":"https://doi.org/10.1109/ACC.2016.7524943","url":null,"abstract":"This paper considers the design of iterative learning control laws for systems whose state-space model matrices are functions of a vector of varying parameters. The repetitive process setting is exploited to develop a linear matrix inequality based procedure for computing gain-scheduling feedback and feedforward (learning) controllers. These controllers guarantee acceptable dynamics along the trials and ensure monotonic convergence of the trial-to-trial error dynamics, respectively. A simulation example is given to illustrate the theoretical developments.","PeriodicalId":137983,"journal":{"name":"2016 American Control Conference (ACC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130935974","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 : 2016-08-01DOI: 10.1109/ACC.2016.7525488
Amit P. Pandey, Martin A. Sehr, M. D. Oliveira
We revisit the issue of gain-scheduled versus robust control with a focus on matrix inequalities. It has been established that for uncertain continuous-time linear systems that depend affinely on the uncertainty, gain-scheduled stabilizability implies robust stabilizability. That is, as far as stabilizability is concerned, using a more complex gain-scheduled controller brings no advantage. In the case of performance and discrete-time systems, counter-examples exist that show that gain-scheduling can indeed be advantageous. These proof are unfortunately not constructive, and the associated necessary and sufficient conditions are hard to verify even in low dimensions. In practice, conditions based on Linear Matrix Inequalities (LMIs) are widely used to design robust and gain scheduled controllers at the expense of some conservatism. The main goal of the present paper is to explore to what extent solvability of certain LMIs for gain-scheduled control also implies solvability of the corresponding robust control inequalities. One issue investigated in detail is that of using pre-filters to handle uncertainty appearing in the input matrix. Our results show that this technique, which has been used since the 80s is rarely productive in the sense that solvability of certain gain-scheduled control design problems for the original system augmented with a pre-filter often implies existence of a robust control for the original system, which we calculate explicitly using a projection. One exception seem to be the LMIs based on the condition of Daafouz and Bernussou (2001) for discrete-time systems. A series of examples illustrate the results.
{"title":"Pre-filtering in gain-scheduled and robust control","authors":"Amit P. Pandey, Martin A. Sehr, M. D. Oliveira","doi":"10.1109/ACC.2016.7525488","DOIUrl":"https://doi.org/10.1109/ACC.2016.7525488","url":null,"abstract":"We revisit the issue of gain-scheduled versus robust control with a focus on matrix inequalities. It has been established that for uncertain continuous-time linear systems that depend affinely on the uncertainty, gain-scheduled stabilizability implies robust stabilizability. That is, as far as stabilizability is concerned, using a more complex gain-scheduled controller brings no advantage. In the case of performance and discrete-time systems, counter-examples exist that show that gain-scheduling can indeed be advantageous. These proof are unfortunately not constructive, and the associated necessary and sufficient conditions are hard to verify even in low dimensions. In practice, conditions based on Linear Matrix Inequalities (LMIs) are widely used to design robust and gain scheduled controllers at the expense of some conservatism. The main goal of the present paper is to explore to what extent solvability of certain LMIs for gain-scheduled control also implies solvability of the corresponding robust control inequalities. One issue investigated in detail is that of using pre-filters to handle uncertainty appearing in the input matrix. Our results show that this technique, which has been used since the 80s is rarely productive in the sense that solvability of certain gain-scheduled control design problems for the original system augmented with a pre-filter often implies existence of a robust control for the original system, which we calculate explicitly using a projection. One exception seem to be the LMIs based on the condition of Daafouz and Bernussou (2001) for discrete-time systems. A series of examples illustrate the results.","PeriodicalId":137983,"journal":{"name":"2016 American Control Conference (ACC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126455670","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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