Inversion of nonlinear stochastic models for parameter estimation

• Prediction error and maximum likelihood estimation of nonlinear stochastic models requires inversion of the model, a step which may require substantial efforts, either in terms of manual calculations or through the use of software capable of symbolic computations. In this paper we show that model inversion can be easily implemented in numerical software such as, e.g., Simulink and Matrixx, by means of a feedback connection based on the model. We derive sufficient conditions for the existence of a stable causal inverse as well as sufficient conditions for the initial transient to decay. These conditions are given in terms of properties for a linear time-varying system associated with the nonlinear model. The method is illustrated on a numerical example.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Reglerteknik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Control Engineering (hsv//eng)

Nyckelord

Discrete time control systems

Mathematical models

Maximum likelihood estimation

Nonlinear control systems

Probability density function

Stochastic control systems

Model inversion

Nonlinear stochastic models

Parameter estimation

SRA - ICT

SRA - Informations- och kommunikationsteknik

Publikations- och innehållstyp

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