Title :
A Method for Nonlinear Least Squares With Structured Residuals
Author :
Shaw, Steven R. ; Laughman, Christopher R.
Author_Institution :
Dept. of Electr. & Comput. Eng., Montana State Univ., Bozeman, MT
Abstract :
This note develops a modification of standard nonlinear least squares methods with reduced sensitivity to the quality of the initial guess. The technique is presented in the context of least squares fitting of dynamic system models, but may apply to other kinds of problems. The performance of the technique is compared to standard methods for a variety of test problems
Keywords :
least squares approximations; reduced order systems; sensitivity analysis; time-varying systems; dynamic system model; nonlinear least squares method; reduced sensitivity; structured residuals; Computer architecture; Context modeling; Convergence; Electronic mail; Gaussian processes; Least squares methods; Nonlinear dynamical systems; Standards development; System identification; Testing; Nonlinear least squares; optimization; system identification;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.2006.883036
