Title :
Regularized robust filters for time-varying uncertain discrete-time systems
Author :
Subramanian, Ananth ; Sayed, Ali H.
Author_Institution :
Electr. Eng. Dept., Univ. of California, Los Angeles, CA, USA
fDate :
6/1/2004 12:00:00 AM
Abstract :
This note develops robust filters for time-varying uncertain discrete-time systems. The developed filters are based on a data regularization solution and they enforce a minimum state-error variance property. Simulation results confirm their superior performance over other robust filter designs.
Keywords :
convex programming; discrete time systems; filtering theory; least mean squares methods; robust control; state-space methods; time-varying systems; uncertain systems; minimum state-error variance property; regularized robust filters; regularized weighted recursive least square problem; state-space estimation; time-varying uncertain discrete-time systems; Boolean functions; Circuit analysis; Digital circuits; Eigenvalues and eigenfunctions; Equations; Filters; Robustness; Testing; Time varying systems; Timing; Convex optimization; least-squares; parametric uncertainty; regularization; robust filter;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.2004.829609
