SLICOT System Identification Toolbox includes SLICOT-based MATLAB and Fortran tools for linear and Wiener-type, time-invariant discrete-time multivariable systems. Subspace-based approaches MOESP - Multivariable Output-Error state SPace identification, N4SID - Numerical algorithms for Subspace State Space System IDentification, and their combination, are used to identify linear systems, and to initialize the parameters of the linear part of a Wiener system. All parameters of a Wiener system are then estimated using a specialized Levenberg-Marquardt algorithm.
The main functionalities of the toolbox include:
- identification of linear discrete-time state space systems (A, B, C, D)
- identification of state and output (cross-)covariance matrices for such systems
- estimation of the associated Kalman gain matrix
- estimation of the initial state
- conversion from/to a state-space representation to/from the output normal form parameterization
- identification of discrete-time Wiener systems
- computation of the output response of Wiener systems.
The toolbox main features are:
- computational reliability
- high numerical efficiency, using structure exploiting algorithms and dedicated linear algebra tools
- possible speed-up factors larger then 10 in comparison with the commonly used software tools
- flexibility and easy-of-use
- ability to process multiple (possibly connected) data batches
- standardized interfaces
The programs have been extensively tested on various test examples and are fully documented.
SLICOT Toolboxes for MATLAB are subject to a license fee and require an individual license agreement.Find detailed information here or contact the SLICOT Administration directly.
Vasile Sima, February 2, 2005
