Add to ORKGA common approach for modeling LPV systems is to interpolate between local LTI models, often obtained by system identification methods. We study the results of interpolating in different domains, the so called I/O domain and the state-space domain. It is shown that significant differences can occur between the interpolated models, due to differences in time propagation of the (scheduling) parameter. We introduce canonical representations for LPV state-space realizations similar to the LTV framework and derive exact formulas for the connection between I/O and state-space based LPV models
State-space identification of Linear Parameter-Varying (LPV) models using local data still represent...
State-space identification of Linear Parameter-Varying (LPV) models using local data still represent...
A common problem in the context of linear parameter-varying (LPV) systems is how input-output (IO) m...
A common approach for modeling LPV systems is to interpolate between local LTI models, often obtaine...
A common approach for modeling LPV systems is to interpolate between local LTI models, often obtaine...
A common approach for modeling LPV systems is to interpolate between local LTI models, often obtaine...
A common approach for modeling LPV systems is to interpolate between local LTI models, often obtaine...
A common approach for modeling LPV systems is to interpolate between local LTI models, often obtaine...
A common approach for modeling LPV systems is to interpolate between local LTI models, often obtaine...
Identification of Linear Parameter-Varying (LPV) systems is often accomplished via Input-Output (IO)...
Identification of Linear Parameter-Varying (LPV) systems is often accomplished via Input-Output (IO)...
Identification of Linear Parameter-Varying (LPV) systems is often accomplished via Input-Output (IO)...
Identification of Linear Parameter-Varying (LPV) systems is often accomplished via Input-Output (IO)...
Identification of Linear Parameter-Varying (LPV) systems is often accomplished via Input-Output (IO)...
A common problem in the context of linear parameter-varying (LPV) systems is how input-output (IO) m...
State-space identification of Linear Parameter-Varying (LPV) models using local data still represent...
State-space identification of Linear Parameter-Varying (LPV) models using local data still represent...
A common problem in the context of linear parameter-varying (LPV) systems is how input-output (IO) m...
A common approach for modeling LPV systems is to interpolate between local LTI models, often obtaine...
A common approach for modeling LPV systems is to interpolate between local LTI models, often obtaine...
A common approach for modeling LPV systems is to interpolate between local LTI models, often obtaine...
A common approach for modeling LPV systems is to interpolate between local LTI models, often obtaine...
A common approach for modeling LPV systems is to interpolate between local LTI models, often obtaine...
A common approach for modeling LPV systems is to interpolate between local LTI models, often obtaine...
Identification of Linear Parameter-Varying (LPV) systems is often accomplished via Input-Output (IO)...
Identification of Linear Parameter-Varying (LPV) systems is often accomplished via Input-Output (IO)...
Identification of Linear Parameter-Varying (LPV) systems is often accomplished via Input-Output (IO)...
Identification of Linear Parameter-Varying (LPV) systems is often accomplished via Input-Output (IO)...
Identification of Linear Parameter-Varying (LPV) systems is often accomplished via Input-Output (IO)...
A common problem in the context of linear parameter-varying (LPV) systems is how input-output (IO) m...
State-space identification of Linear Parameter-Varying (LPV) models using local data still represent...
State-space identification of Linear Parameter-Varying (LPV) models using local data still represent...
A common problem in the context of linear parameter-varying (LPV) systems is how input-output (IO) m...