Theoretical and empirical study of various problems in system identification. Particular attention is paid to robust estimation of Multivariable and Nonlinear systems, and to error quantification.
Sub-Projects
This toolbox is a MATLAB-based software package for the estimation of dynamic systems. A wide range of standard estimation approaches are supported. These include the use of non-parametric, subspace-based and prediction-error algorithms coupled (in the latter case) with either MIMO state space or MISO polynomial model structures.
This project offers a collection of quadratic programming routines, which are written in C and callable from Matlab. These routines cover a range of problem structures from simply bounded strictly convex quadratic programmes to the more general case. Furthermore, a range of approaches are used including active-set, interior-point and a branch and bound approach.