The paper presents a parameters estimation procedure for physical systems modeled using the POG (Power-Oriented Graphs) technique. The coefficients defining the constitutive relation for both static and dynamic physical elements within the system can be estimated, as well as the coefficients describing energy conversions taking place either within the same energetic domain or between two different energetic domains. The evolution of the state vector over time is supposed to be known, whereas its first derivative is supposed to be unknown and is obtained by using a new algorithm for computing the discrete-time derivative of a sampled signal, which is effective even in presence of disturbances affecting the signal samples. As long as the unknown parameters appear linearly within the system differential equations, the system is allowed to exhibit any nonlinear function of the state vector and its first derivative. The procedure is finally applied to two different case studies: a linear one and a nonlinear one.
Estimation of Physical Parameters Using a New Discrete-time Derivative Algorithm / Tebaldi, Davide; Morselli, Riccardo; Zanasi, Roberto. - 53:2(2020), pp. 2367-2372. (Intervento presentato al convegno 21st IFAC World Congress 2020 tenutosi a Berlin, Germany nel 11-17 July 2020) [10.1016/j.ifacol.2020.12.033].
Estimation of Physical Parameters Using a New Discrete-time Derivative Algorithm
Davide Tebaldi
;Roberto Zanasi
2020
Abstract
The paper presents a parameters estimation procedure for physical systems modeled using the POG (Power-Oriented Graphs) technique. The coefficients defining the constitutive relation for both static and dynamic physical elements within the system can be estimated, as well as the coefficients describing energy conversions taking place either within the same energetic domain or between two different energetic domains. The evolution of the state vector over time is supposed to be known, whereas its first derivative is supposed to be unknown and is obtained by using a new algorithm for computing the discrete-time derivative of a sampled signal, which is effective even in presence of disturbances affecting the signal samples. As long as the unknown parameters appear linearly within the system differential equations, the system is allowed to exhibit any nonlinear function of the state vector and its first derivative. The procedure is finally applied to two different case studies: a linear one and a nonlinear one.File | Dimensione | Formato | |
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