Optimization by Vector Space Methods
Optimization by Vector Space Methods
System identification-A survey
Automatica (Journal of IFAC)
Parameter estimation for continuous-time models-A survey
Automatica (Journal of IFAC)
Paper: Nonlinear system identification with limited time data
Automatica (Journal of IFAC)
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A deterministic least squares formulation is given for identifying the parameters of a class of linear multivariable differential systems based on input-output data observed over a finite time interval which circumvents the need for estimating the initial state of the system. The formulation allows for unknown disturbances to the extent that such disturbances can be modeled by the free response of a linear differential equation. It is shown that a unique solution to the normal equations is obtained if the component functions of the input-output data, together with a certain number of their derivatives, are linearly independent on the observation interval. Results are summarized of a computer simulation of the method. These results indicate that good accuracy can be achieved even for very small signal to noise ratios when the disturbances can be modeled by uncontrollable modes on the observation interval.