Title :
Nonlinear reduced-order state and parameter observer
Author :
Haessig, David A. ; Friedland, Bernard
Author_Institution :
Dept. of Electr. & Comput. Eng., New Jersey Inst. of Technol., Newark, NJ, USA
Abstract :
A globally stable algorithm for jointly estimating the state and parameters in deterministic nonlinear dynamic systems is developed. This is accomplished by combining the concepts developed by Raghavan (1992) for the design of a full-order adaptive observer with the techniques used by Friedland (1997) for development of reduced-order estimators. The result is a method whose applicability exceeds that of many existing techniques in that it can accommodate multi-output systems. Several previously developed methods applicable to the same class of nonlinear system are restricted to single-output systems. In addition, the new method is shown to have some computational, advantages
Keywords :
MIMO systems; nonlinear dynamical systems; observers; parameter estimation; reduced order systems; uncertain systems; deterministic nonlinear dynamic systems; full-order adaptive observer; globally stable algorithm; multi-output systems; reduced-order estimators; reduced-order parameter observer; reduced-order state observer; Controllability; Equations; Filters; Jacobian matrices; Nonlinear systems; Observability; Observers; Parameter estimation; State estimation; Vectors;
Conference_Titel :
American Control Conference, 2001. Proceedings of the 2001
Conference_Location :
Arlington, VA
Print_ISBN :
0-7803-6495-3
DOI :
10.1109/ACC.2001.946031