Adaptive control design under structured model information limitation: A cost-biased maximum-likelihood approach
Networked control strategies based on limited information about the plant model usually result in worse closed-loop performance than optimal centralized control with full plant model information. Recently, this fact has been established by utilizing the concept of competitive ratio, which is defined...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Farokhi, Farhad [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2015 |
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| Übergeordnetes Werk: |
Enthalten in: Systems & control letters - Amsterdam [u.a.] : Elsevier, 1981, 75(2015), Seite 8-13 |
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| Übergeordnetes Werk: |
volume:75 ; year:2015 ; pages:8-13 |
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10.1016/j.sysconle.2014.10.010 |
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| 520 | |a Networked control strategies based on limited information about the plant model usually result in worse closed-loop performance than optimal centralized control with full plant model information. Recently, this fact has been established by utilizing the concept of competitive ratio, which is defined as the worst-case ratio of the cost of a control design with limited model information to the cost of the optimal control design with full model information. We show that an adaptive controller, inspired by a controller proposed by Campi and Kumar, with limited plant model information, asymptotically achieves the closed-loop performance of the optimal centralized controller with full model information for almost any plant. Therefore, there exists, at least, one adaptive control design strategy with limited plant model information that can achieve a competitive ratio equal to one. The plant model considered in the paper belongs to a compact set of stochastic linear time-invariant systems and the closed-loop performance measure is the ergodic mean of a quadratic function of the state and control input. | ||
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10.1016/j.sysconle.2014.10.010 doi PQ20160617 (DE-627)OLC1968536140 (DE-599)GBVOLC1968536140 (PRQ)c1452-68b6f27a5a42d441227d4bdcda29cc0e914f8c904c8fcbe764c0418f9e1d72b20 (KEY)0104696920150000075000000008adaptivecontroldesignunderstructuredmodelinformati DE-627 ger DE-627 rakwb eng 620 DNB Farokhi, Farhad verfasserin aut Adaptive control design under structured model information limitation: A cost-biased maximum-likelihood approach 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Networked control strategies based on limited information about the plant model usually result in worse closed-loop performance than optimal centralized control with full plant model information. Recently, this fact has been established by utilizing the concept of competitive ratio, which is defined as the worst-case ratio of the cost of a control design with limited model information to the cost of the optimal control design with full model information. We show that an adaptive controller, inspired by a controller proposed by Campi and Kumar, with limited plant model information, asymptotically achieves the closed-loop performance of the optimal centralized controller with full model information for almost any plant. Therefore, there exists, at least, one adaptive control design strategy with limited plant model information that can achieve a competitive ratio equal to one. The plant model considered in the paper belongs to a compact set of stochastic linear time-invariant systems and the closed-loop performance measure is the ergodic mean of a quadratic function of the state and control input. Johansson, Karl H oth Enthalten in Systems & control letters Amsterdam [u.a.] : Elsevier, 1981 75(2015), Seite 8-13 (DE-627)129098825 (DE-600)8427-X (DE-576)014435705 0167-6911 nnns volume:75 year:2015 pages:8-13 http://dx.doi.org/10.1016/j.sysconle.2014.10.010 Volltext http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-160763 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_21 GBV_ILN_70 AR 75 2015 8-13 |
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Adaptive control design under structured model information limitation: A cost-biased maximum-likelihood approach |
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Networked control strategies based on limited information about the plant model usually result in worse closed-loop performance than optimal centralized control with full plant model information. Recently, this fact has been established by utilizing the concept of competitive ratio, which is defined as the worst-case ratio of the cost of a control design with limited model information to the cost of the optimal control design with full model information. We show that an adaptive controller, inspired by a controller proposed by Campi and Kumar, with limited plant model information, asymptotically achieves the closed-loop performance of the optimal centralized controller with full model information for almost any plant. Therefore, there exists, at least, one adaptive control design strategy with limited plant model information that can achieve a competitive ratio equal to one. The plant model considered in the paper belongs to a compact set of stochastic linear time-invariant systems and the closed-loop performance measure is the ergodic mean of a quadratic function of the state and control input. |
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Networked control strategies based on limited information about the plant model usually result in worse closed-loop performance than optimal centralized control with full plant model information. Recently, this fact has been established by utilizing the concept of competitive ratio, which is defined as the worst-case ratio of the cost of a control design with limited model information to the cost of the optimal control design with full model information. We show that an adaptive controller, inspired by a controller proposed by Campi and Kumar, with limited plant model information, asymptotically achieves the closed-loop performance of the optimal centralized controller with full model information for almost any plant. Therefore, there exists, at least, one adaptive control design strategy with limited plant model information that can achieve a competitive ratio equal to one. The plant model considered in the paper belongs to a compact set of stochastic linear time-invariant systems and the closed-loop performance measure is the ergodic mean of a quadratic function of the state and control input. |
| abstract_unstemmed |
Networked control strategies based on limited information about the plant model usually result in worse closed-loop performance than optimal centralized control with full plant model information. Recently, this fact has been established by utilizing the concept of competitive ratio, which is defined as the worst-case ratio of the cost of a control design with limited model information to the cost of the optimal control design with full model information. We show that an adaptive controller, inspired by a controller proposed by Campi and Kumar, with limited plant model information, asymptotically achieves the closed-loop performance of the optimal centralized controller with full model information for almost any plant. Therefore, there exists, at least, one adaptive control design strategy with limited plant model information that can achieve a competitive ratio equal to one. The plant model considered in the paper belongs to a compact set of stochastic linear time-invariant systems and the closed-loop performance measure is the ergodic mean of a quadratic function of the state and control input. |
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Adaptive control design under structured model information limitation: A cost-biased maximum-likelihood approach |
| url |
http://dx.doi.org/10.1016/j.sysconle.2014.10.010 http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-160763 |
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false |
| author2 |
Johansson, Karl H |
| author2Str |
Johansson, Karl H |
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129098825 |
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| doi_str |
10.1016/j.sysconle.2014.10.010 |
| up_date |
2024-07-04T03:37:00.393Z |
| _version_ |
1803618059979587584 |
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