Improving Flexibility of Multivariate Spline Model Structures for Aerodynamic Modeling
AbstractRecently, multivariate simplex B-splines (MVSB) function approximators have been investigated with the aim of providing accurate global aerodynamic models for use in adaptive flight control systems. In this paper, a new approach for constructing multivariate spline models is presented in the...
Ausführliche Beschreibung
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| Autor*in: |
Chu, Qiping [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2017 |
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| Rechteinformationen: |
Nutzungsrecht: © 2017 American Society of Civil Engineers |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Journal of aerospace engineering - New York, NY : Soc., 1988, 30(2017), 5 |
|---|---|
| Übergeordnetes Werk: |
volume:30 ; year:2017 ; number:5 |
| Links: |
|---|
| DOI / URN: |
10.1061/(ASCE)AS.1943-5525.0000755 |
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OLC199508171X |
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| 520 | |a AbstractRecently, multivariate simplex B-splines (MVSB) function approximators have been investigated with the aim of providing accurate global aerodynamic models for use in adaptive flight control systems. In this paper, a new approach for constructing multivariate spline models is presented in the form of the tensor-product MVSB (TP-MVSB) that consists of tensor products of ordinary MVSB. The key advantage of this new approach is that it provides more flexibility in the definition of the spline model structure than the standard multivariate spline approach. This flexibility allows the user to include a priori (expert) knowledge of the system in the definition of the spline model structure leading to more efficient and physically meaningful models. The TP-MVSB maintains the desirable properties of the MVSB in the sense that the global B-form regression vector is normalized, each basis polynomial is guaranteed to be well-conditioned numerically, and differentiability is maintained along each input dimension. The new approach is validated using data obtained from a nonlinear F-16 model. Simulation results show that the new approach can achieve a higher level of approximation accuracy using fewer parameters when modeling the aerodynamic moment coefficients, and in addition can provide accurate estimations of the control effectiveness matrix in cases where the system is affine in the inputs. | ||
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10.1061/(ASCE)AS.1943-5525.0000755 doi PQ20170901 (DE-627)OLC199508171X (DE-599)GBVOLC199508171X (PRQ)a766-7fac2e8e83e10f8003b2968dd99a6815315f555682b26e07f988a8c95d8fe66a0 (KEY)0165901420170000030000500000improvingflexibilityofmultivariatesplinemodelstruc DE-627 ger DE-627 rakwb eng 620 ZDB Chu, Qiping verfasserin aut Improving Flexibility of Multivariate Spline Model Structures for Aerodynamic Modeling 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier AbstractRecently, multivariate simplex B-splines (MVSB) function approximators have been investigated with the aim of providing accurate global aerodynamic models for use in adaptive flight control systems. In this paper, a new approach for constructing multivariate spline models is presented in the form of the tensor-product MVSB (TP-MVSB) that consists of tensor products of ordinary MVSB. The key advantage of this new approach is that it provides more flexibility in the definition of the spline model structure than the standard multivariate spline approach. This flexibility allows the user to include a priori (expert) knowledge of the system in the definition of the spline model structure leading to more efficient and physically meaningful models. The TP-MVSB maintains the desirable properties of the MVSB in the sense that the global B-form regression vector is normalized, each basis polynomial is guaranteed to be well-conditioned numerically, and differentiability is maintained along each input dimension. The new approach is validated using data obtained from a nonlinear F-16 model. Simulation results show that the new approach can achieve a higher level of approximation accuracy using fewer parameters when modeling the aerodynamic moment coefficients, and in addition can provide accurate estimations of the control effectiveness matrix in cases where the system is affine in the inputs. Nutzungsrecht: © 2017 American Society of Civil Engineers Technical Papers Sun, Liguo oth Wang, Yanyang oth de Visser, Coen oth Enthalten in Journal of aerospace engineering New York, NY : Soc., 1988 30(2017), 5 (DE-627)130680117 (DE-600)885027-6 (DE-576)016221990 0893-1321 nnns volume:30 year:2017 number:5 http://dx.doi.org/10.1061/(ASCE)AS.1943-5525.0000755 Volltext http://ascelibrary.org/doi/abs/10.1061/(ASCE)AS.1943-5525.0000755 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2006 AR 30 2017 5 |
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10.1061/(ASCE)AS.1943-5525.0000755 doi PQ20170901 (DE-627)OLC199508171X (DE-599)GBVOLC199508171X (PRQ)a766-7fac2e8e83e10f8003b2968dd99a6815315f555682b26e07f988a8c95d8fe66a0 (KEY)0165901420170000030000500000improvingflexibilityofmultivariatesplinemodelstruc DE-627 ger DE-627 rakwb eng 620 ZDB Chu, Qiping verfasserin aut Improving Flexibility of Multivariate Spline Model Structures for Aerodynamic Modeling 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier AbstractRecently, multivariate simplex B-splines (MVSB) function approximators have been investigated with the aim of providing accurate global aerodynamic models for use in adaptive flight control systems. In this paper, a new approach for constructing multivariate spline models is presented in the form of the tensor-product MVSB (TP-MVSB) that consists of tensor products of ordinary MVSB. The key advantage of this new approach is that it provides more flexibility in the definition of the spline model structure than the standard multivariate spline approach. This flexibility allows the user to include a priori (expert) knowledge of the system in the definition of the spline model structure leading to more efficient and physically meaningful models. The TP-MVSB maintains the desirable properties of the MVSB in the sense that the global B-form regression vector is normalized, each basis polynomial is guaranteed to be well-conditioned numerically, and differentiability is maintained along each input dimension. The new approach is validated using data obtained from a nonlinear F-16 model. Simulation results show that the new approach can achieve a higher level of approximation accuracy using fewer parameters when modeling the aerodynamic moment coefficients, and in addition can provide accurate estimations of the control effectiveness matrix in cases where the system is affine in the inputs. Nutzungsrecht: © 2017 American Society of Civil Engineers Technical Papers Sun, Liguo oth Wang, Yanyang oth de Visser, Coen oth Enthalten in Journal of aerospace engineering New York, NY : Soc., 1988 30(2017), 5 (DE-627)130680117 (DE-600)885027-6 (DE-576)016221990 0893-1321 nnns volume:30 year:2017 number:5 http://dx.doi.org/10.1061/(ASCE)AS.1943-5525.0000755 Volltext http://ascelibrary.org/doi/abs/10.1061/(ASCE)AS.1943-5525.0000755 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2006 AR 30 2017 5 |
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10.1061/(ASCE)AS.1943-5525.0000755 doi PQ20170901 (DE-627)OLC199508171X (DE-599)GBVOLC199508171X (PRQ)a766-7fac2e8e83e10f8003b2968dd99a6815315f555682b26e07f988a8c95d8fe66a0 (KEY)0165901420170000030000500000improvingflexibilityofmultivariatesplinemodelstruc DE-627 ger DE-627 rakwb eng 620 ZDB Chu, Qiping verfasserin aut Improving Flexibility of Multivariate Spline Model Structures for Aerodynamic Modeling 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier AbstractRecently, multivariate simplex B-splines (MVSB) function approximators have been investigated with the aim of providing accurate global aerodynamic models for use in adaptive flight control systems. In this paper, a new approach for constructing multivariate spline models is presented in the form of the tensor-product MVSB (TP-MVSB) that consists of tensor products of ordinary MVSB. The key advantage of this new approach is that it provides more flexibility in the definition of the spline model structure than the standard multivariate spline approach. This flexibility allows the user to include a priori (expert) knowledge of the system in the definition of the spline model structure leading to more efficient and physically meaningful models. The TP-MVSB maintains the desirable properties of the MVSB in the sense that the global B-form regression vector is normalized, each basis polynomial is guaranteed to be well-conditioned numerically, and differentiability is maintained along each input dimension. The new approach is validated using data obtained from a nonlinear F-16 model. Simulation results show that the new approach can achieve a higher level of approximation accuracy using fewer parameters when modeling the aerodynamic moment coefficients, and in addition can provide accurate estimations of the control effectiveness matrix in cases where the system is affine in the inputs. Nutzungsrecht: © 2017 American Society of Civil Engineers Technical Papers Sun, Liguo oth Wang, Yanyang oth de Visser, Coen oth Enthalten in Journal of aerospace engineering New York, NY : Soc., 1988 30(2017), 5 (DE-627)130680117 (DE-600)885027-6 (DE-576)016221990 0893-1321 nnns volume:30 year:2017 number:5 http://dx.doi.org/10.1061/(ASCE)AS.1943-5525.0000755 Volltext http://ascelibrary.org/doi/abs/10.1061/(ASCE)AS.1943-5525.0000755 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2006 AR 30 2017 5 |
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10.1061/(ASCE)AS.1943-5525.0000755 doi PQ20170901 (DE-627)OLC199508171X (DE-599)GBVOLC199508171X (PRQ)a766-7fac2e8e83e10f8003b2968dd99a6815315f555682b26e07f988a8c95d8fe66a0 (KEY)0165901420170000030000500000improvingflexibilityofmultivariatesplinemodelstruc DE-627 ger DE-627 rakwb eng 620 ZDB Chu, Qiping verfasserin aut Improving Flexibility of Multivariate Spline Model Structures for Aerodynamic Modeling 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier AbstractRecently, multivariate simplex B-splines (MVSB) function approximators have been investigated with the aim of providing accurate global aerodynamic models for use in adaptive flight control systems. In this paper, a new approach for constructing multivariate spline models is presented in the form of the tensor-product MVSB (TP-MVSB) that consists of tensor products of ordinary MVSB. The key advantage of this new approach is that it provides more flexibility in the definition of the spline model structure than the standard multivariate spline approach. This flexibility allows the user to include a priori (expert) knowledge of the system in the definition of the spline model structure leading to more efficient and physically meaningful models. The TP-MVSB maintains the desirable properties of the MVSB in the sense that the global B-form regression vector is normalized, each basis polynomial is guaranteed to be well-conditioned numerically, and differentiability is maintained along each input dimension. The new approach is validated using data obtained from a nonlinear F-16 model. Simulation results show that the new approach can achieve a higher level of approximation accuracy using fewer parameters when modeling the aerodynamic moment coefficients, and in addition can provide accurate estimations of the control effectiveness matrix in cases where the system is affine in the inputs. Nutzungsrecht: © 2017 American Society of Civil Engineers Technical Papers Sun, Liguo oth Wang, Yanyang oth de Visser, Coen oth Enthalten in Journal of aerospace engineering New York, NY : Soc., 1988 30(2017), 5 (DE-627)130680117 (DE-600)885027-6 (DE-576)016221990 0893-1321 nnns volume:30 year:2017 number:5 http://dx.doi.org/10.1061/(ASCE)AS.1943-5525.0000755 Volltext http://ascelibrary.org/doi/abs/10.1061/(ASCE)AS.1943-5525.0000755 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2006 AR 30 2017 5 |
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Improving Flexibility of Multivariate Spline Model Structures for Aerodynamic Modeling |
| abstract |
AbstractRecently, multivariate simplex B-splines (MVSB) function approximators have been investigated with the aim of providing accurate global aerodynamic models for use in adaptive flight control systems. In this paper, a new approach for constructing multivariate spline models is presented in the form of the tensor-product MVSB (TP-MVSB) that consists of tensor products of ordinary MVSB. The key advantage of this new approach is that it provides more flexibility in the definition of the spline model structure than the standard multivariate spline approach. This flexibility allows the user to include a priori (expert) knowledge of the system in the definition of the spline model structure leading to more efficient and physically meaningful models. The TP-MVSB maintains the desirable properties of the MVSB in the sense that the global B-form regression vector is normalized, each basis polynomial is guaranteed to be well-conditioned numerically, and differentiability is maintained along each input dimension. The new approach is validated using data obtained from a nonlinear F-16 model. Simulation results show that the new approach can achieve a higher level of approximation accuracy using fewer parameters when modeling the aerodynamic moment coefficients, and in addition can provide accurate estimations of the control effectiveness matrix in cases where the system is affine in the inputs. |
| abstractGer |
AbstractRecently, multivariate simplex B-splines (MVSB) function approximators have been investigated with the aim of providing accurate global aerodynamic models for use in adaptive flight control systems. In this paper, a new approach for constructing multivariate spline models is presented in the form of the tensor-product MVSB (TP-MVSB) that consists of tensor products of ordinary MVSB. The key advantage of this new approach is that it provides more flexibility in the definition of the spline model structure than the standard multivariate spline approach. This flexibility allows the user to include a priori (expert) knowledge of the system in the definition of the spline model structure leading to more efficient and physically meaningful models. The TP-MVSB maintains the desirable properties of the MVSB in the sense that the global B-form regression vector is normalized, each basis polynomial is guaranteed to be well-conditioned numerically, and differentiability is maintained along each input dimension. The new approach is validated using data obtained from a nonlinear F-16 model. Simulation results show that the new approach can achieve a higher level of approximation accuracy using fewer parameters when modeling the aerodynamic moment coefficients, and in addition can provide accurate estimations of the control effectiveness matrix in cases where the system is affine in the inputs. |
| abstract_unstemmed |
AbstractRecently, multivariate simplex B-splines (MVSB) function approximators have been investigated with the aim of providing accurate global aerodynamic models for use in adaptive flight control systems. In this paper, a new approach for constructing multivariate spline models is presented in the form of the tensor-product MVSB (TP-MVSB) that consists of tensor products of ordinary MVSB. The key advantage of this new approach is that it provides more flexibility in the definition of the spline model structure than the standard multivariate spline approach. This flexibility allows the user to include a priori (expert) knowledge of the system in the definition of the spline model structure leading to more efficient and physically meaningful models. The TP-MVSB maintains the desirable properties of the MVSB in the sense that the global B-form regression vector is normalized, each basis polynomial is guaranteed to be well-conditioned numerically, and differentiability is maintained along each input dimension. The new approach is validated using data obtained from a nonlinear F-16 model. Simulation results show that the new approach can achieve a higher level of approximation accuracy using fewer parameters when modeling the aerodynamic moment coefficients, and in addition can provide accurate estimations of the control effectiveness matrix in cases where the system is affine in the inputs. |
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GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2006 |
| container_issue |
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| title_short |
Improving Flexibility of Multivariate Spline Model Structures for Aerodynamic Modeling |
| url |
http://dx.doi.org/10.1061/(ASCE)AS.1943-5525.0000755 http://ascelibrary.org/doi/abs/10.1061/(ASCE)AS.1943-5525.0000755 |
| remote_bool |
false |
| author2 |
Sun, Liguo Wang, Yanyang de Visser, Coen |
| author2Str |
Sun, Liguo Wang, Yanyang de Visser, Coen |
| ppnlink |
130680117 |
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oth oth oth |
| doi_str |
10.1061/(ASCE)AS.1943-5525.0000755 |
| up_date |
2024-07-03T20:23:30.089Z |
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7.403078 |