Load balancing of dynamical distribution networks with flow constraints and unknown in/outflows
We consider a basic model of a dynamical distribution network, modeled as a directed graph with storage variables corresponding to every vertex and flow inputs corresponding to every edge, subject to unknown but constant inflows and outflows. As a preparatory result it is shown how a distributed pro...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Wei, J. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2013transfer abstract |
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| Schlagwörter: |
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| Umfang: |
8 |
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| Übergeordnetes Werk: |
Enthalten in: Generalized Malkmus line intensity distribution for CO2 infrared radiation in Doppler broadening regime - 2011transfer abstract, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:62 ; year:2013 ; number:11 ; pages:1001-1008 ; extent:8 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.sysconle.2013.08.001 |
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ELV038607573 |
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| 520 | |a We consider a basic model of a dynamical distribution network, modeled as a directed graph with storage variables corresponding to every vertex and flow inputs corresponding to every edge, subject to unknown but constant inflows and outflows. As a preparatory result it is shown how a distributed proportional–integral controller structure, associating with every edge of the graph a controller state, will regulate the state variables of the vertices, irrespective of the unknown constant inflows and outflows, in the sense that the storage variables converge to the same value (load balancing or consensus). This will be proved by identifying the closed-loop system as a port-Hamiltonian system, and modifying the Hamiltonian function into a Lyapunov function, dependent on the value of the vector of constant inflows and outflows. In the main part of the paper the same problem will be addressed for the case that the input flow variables are constrained to take value in an arbitrary interval. We will derive sufficient and necessary conditions for load balancing, which only depend on the structure of the network in relation with the flow constraints. | ||
| 520 | |a We consider a basic model of a dynamical distribution network, modeled as a directed graph with storage variables corresponding to every vertex and flow inputs corresponding to every edge, subject to unknown but constant inflows and outflows. As a preparatory result it is shown how a distributed proportional–integral controller structure, associating with every edge of the graph a controller state, will regulate the state variables of the vertices, irrespective of the unknown constant inflows and outflows, in the sense that the storage variables converge to the same value (load balancing or consensus). This will be proved by identifying the closed-loop system as a port-Hamiltonian system, and modifying the Hamiltonian function into a Lyapunov function, dependent on the value of the vector of constant inflows and outflows. In the main part of the paper the same problem will be addressed for the case that the input flow variables are constrained to take value in an arbitrary interval. We will derive sufficient and necessary conditions for load balancing, which only depend on the structure of the network in relation with the flow constraints. | ||
| 650 | 7 | |a Flow constraints |2 Elsevier | |
| 650 | 7 | |a Directed graphs |2 Elsevier | |
| 650 | 7 | |a Consensus algorithms |2 Elsevier | |
| 650 | 7 | |a Lyapunov stability |2 Elsevier | |
| 650 | 7 | |a PI controllers |2 Elsevier | |
| 650 | 7 | |a Port-Hamiltonian systems |2 Elsevier | |
| 700 | 1 | |a van der Schaft, A.J. |4 oth | |
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10.1016/j.sysconle.2013.08.001 doi GBVA2013004000026.pica (DE-627)ELV038607573 (ELSEVIER)S0167-6911(13)00171-0 DE-627 ger DE-627 rakwb eng 620 620 DE-600 530 VZ 004 VZ 54.72 bkl Wei, J. verfasserin aut Load balancing of dynamical distribution networks with flow constraints and unknown in/outflows 2013transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier We consider a basic model of a dynamical distribution network, modeled as a directed graph with storage variables corresponding to every vertex and flow inputs corresponding to every edge, subject to unknown but constant inflows and outflows. As a preparatory result it is shown how a distributed proportional–integral controller structure, associating with every edge of the graph a controller state, will regulate the state variables of the vertices, irrespective of the unknown constant inflows and outflows, in the sense that the storage variables converge to the same value (load balancing or consensus). This will be proved by identifying the closed-loop system as a port-Hamiltonian system, and modifying the Hamiltonian function into a Lyapunov function, dependent on the value of the vector of constant inflows and outflows. In the main part of the paper the same problem will be addressed for the case that the input flow variables are constrained to take value in an arbitrary interval. We will derive sufficient and necessary conditions for load balancing, which only depend on the structure of the network in relation with the flow constraints. We consider a basic model of a dynamical distribution network, modeled as a directed graph with storage variables corresponding to every vertex and flow inputs corresponding to every edge, subject to unknown but constant inflows and outflows. As a preparatory result it is shown how a distributed proportional–integral controller structure, associating with every edge of the graph a controller state, will regulate the state variables of the vertices, irrespective of the unknown constant inflows and outflows, in the sense that the storage variables converge to the same value (load balancing or consensus). This will be proved by identifying the closed-loop system as a port-Hamiltonian system, and modifying the Hamiltonian function into a Lyapunov function, dependent on the value of the vector of constant inflows and outflows. In the main part of the paper the same problem will be addressed for the case that the input flow variables are constrained to take value in an arbitrary interval. We will derive sufficient and necessary conditions for load balancing, which only depend on the structure of the network in relation with the flow constraints. Flow constraints Elsevier Directed graphs Elsevier Consensus algorithms Elsevier Lyapunov stability Elsevier PI controllers Elsevier Port-Hamiltonian systems Elsevier van der Schaft, A.J. oth Enthalten in Elsevier Generalized Malkmus line intensity distribution for CO2 infrared radiation in Doppler broadening regime 2011transfer abstract Amsterdam [u.a.] (DE-627)ELV026145170 volume:62 year:2013 number:11 pages:1001-1008 extent:8 https://doi.org/10.1016/j.sysconle.2013.08.001 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_74 54.72 Künstliche Intelligenz VZ AR 62 2013 11 1001-1008 8 045F 620 |
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10.1016/j.sysconle.2013.08.001 doi GBVA2013004000026.pica (DE-627)ELV038607573 (ELSEVIER)S0167-6911(13)00171-0 DE-627 ger DE-627 rakwb eng 620 620 DE-600 530 VZ 004 VZ 54.72 bkl Wei, J. verfasserin aut Load balancing of dynamical distribution networks with flow constraints and unknown in/outflows 2013transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier We consider a basic model of a dynamical distribution network, modeled as a directed graph with storage variables corresponding to every vertex and flow inputs corresponding to every edge, subject to unknown but constant inflows and outflows. As a preparatory result it is shown how a distributed proportional–integral controller structure, associating with every edge of the graph a controller state, will regulate the state variables of the vertices, irrespective of the unknown constant inflows and outflows, in the sense that the storage variables converge to the same value (load balancing or consensus). This will be proved by identifying the closed-loop system as a port-Hamiltonian system, and modifying the Hamiltonian function into a Lyapunov function, dependent on the value of the vector of constant inflows and outflows. In the main part of the paper the same problem will be addressed for the case that the input flow variables are constrained to take value in an arbitrary interval. We will derive sufficient and necessary conditions for load balancing, which only depend on the structure of the network in relation with the flow constraints. We consider a basic model of a dynamical distribution network, modeled as a directed graph with storage variables corresponding to every vertex and flow inputs corresponding to every edge, subject to unknown but constant inflows and outflows. As a preparatory result it is shown how a distributed proportional–integral controller structure, associating with every edge of the graph a controller state, will regulate the state variables of the vertices, irrespective of the unknown constant inflows and outflows, in the sense that the storage variables converge to the same value (load balancing or consensus). This will be proved by identifying the closed-loop system as a port-Hamiltonian system, and modifying the Hamiltonian function into a Lyapunov function, dependent on the value of the vector of constant inflows and outflows. In the main part of the paper the same problem will be addressed for the case that the input flow variables are constrained to take value in an arbitrary interval. We will derive sufficient and necessary conditions for load balancing, which only depend on the structure of the network in relation with the flow constraints. Flow constraints Elsevier Directed graphs Elsevier Consensus algorithms Elsevier Lyapunov stability Elsevier PI controllers Elsevier Port-Hamiltonian systems Elsevier van der Schaft, A.J. oth Enthalten in Elsevier Generalized Malkmus line intensity distribution for CO2 infrared radiation in Doppler broadening regime 2011transfer abstract Amsterdam [u.a.] (DE-627)ELV026145170 volume:62 year:2013 number:11 pages:1001-1008 extent:8 https://doi.org/10.1016/j.sysconle.2013.08.001 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_74 54.72 Künstliche Intelligenz VZ AR 62 2013 11 1001-1008 8 045F 620 |
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10.1016/j.sysconle.2013.08.001 doi GBVA2013004000026.pica (DE-627)ELV038607573 (ELSEVIER)S0167-6911(13)00171-0 DE-627 ger DE-627 rakwb eng 620 620 DE-600 530 VZ 004 VZ 54.72 bkl Wei, J. verfasserin aut Load balancing of dynamical distribution networks with flow constraints and unknown in/outflows 2013transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier We consider a basic model of a dynamical distribution network, modeled as a directed graph with storage variables corresponding to every vertex and flow inputs corresponding to every edge, subject to unknown but constant inflows and outflows. As a preparatory result it is shown how a distributed proportional–integral controller structure, associating with every edge of the graph a controller state, will regulate the state variables of the vertices, irrespective of the unknown constant inflows and outflows, in the sense that the storage variables converge to the same value (load balancing or consensus). This will be proved by identifying the closed-loop system as a port-Hamiltonian system, and modifying the Hamiltonian function into a Lyapunov function, dependent on the value of the vector of constant inflows and outflows. In the main part of the paper the same problem will be addressed for the case that the input flow variables are constrained to take value in an arbitrary interval. We will derive sufficient and necessary conditions for load balancing, which only depend on the structure of the network in relation with the flow constraints. We consider a basic model of a dynamical distribution network, modeled as a directed graph with storage variables corresponding to every vertex and flow inputs corresponding to every edge, subject to unknown but constant inflows and outflows. As a preparatory result it is shown how a distributed proportional–integral controller structure, associating with every edge of the graph a controller state, will regulate the state variables of the vertices, irrespective of the unknown constant inflows and outflows, in the sense that the storage variables converge to the same value (load balancing or consensus). This will be proved by identifying the closed-loop system as a port-Hamiltonian system, and modifying the Hamiltonian function into a Lyapunov function, dependent on the value of the vector of constant inflows and outflows. In the main part of the paper the same problem will be addressed for the case that the input flow variables are constrained to take value in an arbitrary interval. We will derive sufficient and necessary conditions for load balancing, which only depend on the structure of the network in relation with the flow constraints. Flow constraints Elsevier Directed graphs Elsevier Consensus algorithms Elsevier Lyapunov stability Elsevier PI controllers Elsevier Port-Hamiltonian systems Elsevier van der Schaft, A.J. oth Enthalten in Elsevier Generalized Malkmus line intensity distribution for CO2 infrared radiation in Doppler broadening regime 2011transfer abstract Amsterdam [u.a.] (DE-627)ELV026145170 volume:62 year:2013 number:11 pages:1001-1008 extent:8 https://doi.org/10.1016/j.sysconle.2013.08.001 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_74 54.72 Künstliche Intelligenz VZ AR 62 2013 11 1001-1008 8 045F 620 |
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10.1016/j.sysconle.2013.08.001 doi GBVA2013004000026.pica (DE-627)ELV038607573 (ELSEVIER)S0167-6911(13)00171-0 DE-627 ger DE-627 rakwb eng 620 620 DE-600 530 VZ 004 VZ 54.72 bkl Wei, J. verfasserin aut Load balancing of dynamical distribution networks with flow constraints and unknown in/outflows 2013transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier We consider a basic model of a dynamical distribution network, modeled as a directed graph with storage variables corresponding to every vertex and flow inputs corresponding to every edge, subject to unknown but constant inflows and outflows. As a preparatory result it is shown how a distributed proportional–integral controller structure, associating with every edge of the graph a controller state, will regulate the state variables of the vertices, irrespective of the unknown constant inflows and outflows, in the sense that the storage variables converge to the same value (load balancing or consensus). This will be proved by identifying the closed-loop system as a port-Hamiltonian system, and modifying the Hamiltonian function into a Lyapunov function, dependent on the value of the vector of constant inflows and outflows. In the main part of the paper the same problem will be addressed for the case that the input flow variables are constrained to take value in an arbitrary interval. We will derive sufficient and necessary conditions for load balancing, which only depend on the structure of the network in relation with the flow constraints. We consider a basic model of a dynamical distribution network, modeled as a directed graph with storage variables corresponding to every vertex and flow inputs corresponding to every edge, subject to unknown but constant inflows and outflows. As a preparatory result it is shown how a distributed proportional–integral controller structure, associating with every edge of the graph a controller state, will regulate the state variables of the vertices, irrespective of the unknown constant inflows and outflows, in the sense that the storage variables converge to the same value (load balancing or consensus). This will be proved by identifying the closed-loop system as a port-Hamiltonian system, and modifying the Hamiltonian function into a Lyapunov function, dependent on the value of the vector of constant inflows and outflows. In the main part of the paper the same problem will be addressed for the case that the input flow variables are constrained to take value in an arbitrary interval. We will derive sufficient and necessary conditions for load balancing, which only depend on the structure of the network in relation with the flow constraints. Flow constraints Elsevier Directed graphs Elsevier Consensus algorithms Elsevier Lyapunov stability Elsevier PI controllers Elsevier Port-Hamiltonian systems Elsevier van der Schaft, A.J. oth Enthalten in Elsevier Generalized Malkmus line intensity distribution for CO2 infrared radiation in Doppler broadening regime 2011transfer abstract Amsterdam [u.a.] (DE-627)ELV026145170 volume:62 year:2013 number:11 pages:1001-1008 extent:8 https://doi.org/10.1016/j.sysconle.2013.08.001 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_74 54.72 Künstliche Intelligenz VZ AR 62 2013 11 1001-1008 8 045F 620 |
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10.1016/j.sysconle.2013.08.001 doi GBVA2013004000026.pica (DE-627)ELV038607573 (ELSEVIER)S0167-6911(13)00171-0 DE-627 ger DE-627 rakwb eng 620 620 DE-600 530 VZ 004 VZ 54.72 bkl Wei, J. verfasserin aut Load balancing of dynamical distribution networks with flow constraints and unknown in/outflows 2013transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier We consider a basic model of a dynamical distribution network, modeled as a directed graph with storage variables corresponding to every vertex and flow inputs corresponding to every edge, subject to unknown but constant inflows and outflows. As a preparatory result it is shown how a distributed proportional–integral controller structure, associating with every edge of the graph a controller state, will regulate the state variables of the vertices, irrespective of the unknown constant inflows and outflows, in the sense that the storage variables converge to the same value (load balancing or consensus). This will be proved by identifying the closed-loop system as a port-Hamiltonian system, and modifying the Hamiltonian function into a Lyapunov function, dependent on the value of the vector of constant inflows and outflows. In the main part of the paper the same problem will be addressed for the case that the input flow variables are constrained to take value in an arbitrary interval. We will derive sufficient and necessary conditions for load balancing, which only depend on the structure of the network in relation with the flow constraints. We consider a basic model of a dynamical distribution network, modeled as a directed graph with storage variables corresponding to every vertex and flow inputs corresponding to every edge, subject to unknown but constant inflows and outflows. As a preparatory result it is shown how a distributed proportional–integral controller structure, associating with every edge of the graph a controller state, will regulate the state variables of the vertices, irrespective of the unknown constant inflows and outflows, in the sense that the storage variables converge to the same value (load balancing or consensus). This will be proved by identifying the closed-loop system as a port-Hamiltonian system, and modifying the Hamiltonian function into a Lyapunov function, dependent on the value of the vector of constant inflows and outflows. In the main part of the paper the same problem will be addressed for the case that the input flow variables are constrained to take value in an arbitrary interval. We will derive sufficient and necessary conditions for load balancing, which only depend on the structure of the network in relation with the flow constraints. Flow constraints Elsevier Directed graphs Elsevier Consensus algorithms Elsevier Lyapunov stability Elsevier PI controllers Elsevier Port-Hamiltonian systems Elsevier van der Schaft, A.J. oth Enthalten in Elsevier Generalized Malkmus line intensity distribution for CO2 infrared radiation in Doppler broadening regime 2011transfer abstract Amsterdam [u.a.] (DE-627)ELV026145170 volume:62 year:2013 number:11 pages:1001-1008 extent:8 https://doi.org/10.1016/j.sysconle.2013.08.001 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_74 54.72 Künstliche Intelligenz VZ AR 62 2013 11 1001-1008 8 045F 620 |
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Enthalten in Generalized Malkmus line intensity distribution for CO2 infrared radiation in Doppler broadening regime Amsterdam [u.a.] volume:62 year:2013 number:11 pages:1001-1008 extent:8 |
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Generalized Malkmus line intensity distribution for CO2 infrared radiation in Doppler broadening regime |
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As a preparatory result it is shown how a distributed proportional–integral controller structure, associating with every edge of the graph a controller state, will regulate the state variables of the vertices, irrespective of the unknown constant inflows and outflows, in the sense that the storage variables converge to the same value (load balancing or consensus). This will be proved by identifying the closed-loop system as a port-Hamiltonian system, and modifying the Hamiltonian function into a Lyapunov function, dependent on the value of the vector of constant inflows and outflows. In the main part of the paper the same problem will be addressed for the case that the input flow variables are constrained to take value in an arbitrary interval. We will derive sufficient and necessary conditions for load balancing, which only depend on the structure of the network in relation with the flow constraints.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">We consider a basic model of a dynamical distribution network, modeled as a directed graph with storage variables corresponding to every vertex and flow inputs corresponding to every edge, subject to unknown but constant inflows and outflows. As a preparatory result it is shown how a distributed proportional–integral controller structure, associating with every edge of the graph a controller state, will regulate the state variables of the vertices, irrespective of the unknown constant inflows and outflows, in the sense that the storage variables converge to the same value (load balancing or consensus). 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load balancing of dynamical distribution networks with flow constraints and unknown in/outflows |
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Load balancing of dynamical distribution networks with flow constraints and unknown in/outflows |
| abstract |
We consider a basic model of a dynamical distribution network, modeled as a directed graph with storage variables corresponding to every vertex and flow inputs corresponding to every edge, subject to unknown but constant inflows and outflows. As a preparatory result it is shown how a distributed proportional–integral controller structure, associating with every edge of the graph a controller state, will regulate the state variables of the vertices, irrespective of the unknown constant inflows and outflows, in the sense that the storage variables converge to the same value (load balancing or consensus). This will be proved by identifying the closed-loop system as a port-Hamiltonian system, and modifying the Hamiltonian function into a Lyapunov function, dependent on the value of the vector of constant inflows and outflows. In the main part of the paper the same problem will be addressed for the case that the input flow variables are constrained to take value in an arbitrary interval. We will derive sufficient and necessary conditions for load balancing, which only depend on the structure of the network in relation with the flow constraints. |
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We consider a basic model of a dynamical distribution network, modeled as a directed graph with storage variables corresponding to every vertex and flow inputs corresponding to every edge, subject to unknown but constant inflows and outflows. As a preparatory result it is shown how a distributed proportional–integral controller structure, associating with every edge of the graph a controller state, will regulate the state variables of the vertices, irrespective of the unknown constant inflows and outflows, in the sense that the storage variables converge to the same value (load balancing or consensus). This will be proved by identifying the closed-loop system as a port-Hamiltonian system, and modifying the Hamiltonian function into a Lyapunov function, dependent on the value of the vector of constant inflows and outflows. In the main part of the paper the same problem will be addressed for the case that the input flow variables are constrained to take value in an arbitrary interval. We will derive sufficient and necessary conditions for load balancing, which only depend on the structure of the network in relation with the flow constraints. |
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We consider a basic model of a dynamical distribution network, modeled as a directed graph with storage variables corresponding to every vertex and flow inputs corresponding to every edge, subject to unknown but constant inflows and outflows. As a preparatory result it is shown how a distributed proportional–integral controller structure, associating with every edge of the graph a controller state, will regulate the state variables of the vertices, irrespective of the unknown constant inflows and outflows, in the sense that the storage variables converge to the same value (load balancing or consensus). This will be proved by identifying the closed-loop system as a port-Hamiltonian system, and modifying the Hamiltonian function into a Lyapunov function, dependent on the value of the vector of constant inflows and outflows. In the main part of the paper the same problem will be addressed for the case that the input flow variables are constrained to take value in an arbitrary interval. We will derive sufficient and necessary conditions for load balancing, which only depend on the structure of the network in relation with the flow constraints. |
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