Title :
Suboptimal robust asymptotic observer for stochastic continuous time nonlinear system: numerical procedure and convergence analysis
Author :
Poznyak, Alex ; Nazin, Alexander ; Murano, Daishi
Author_Institution :
Dept. of Autom. Control, CINVESTAV-IPN, Mexico City, Mexico
Abstract :
In this paper we show that for stationary stochastic nonlinear systems (satisfying a Globally Lipschitz Condition) the high-gain observer with a constant gain matrix may guarantee an upper bound for the averaged quadratic error of state estimation. The nonlinearities are assumed to be a priory known. The main contribution of this paper consists in the designing of a numerical procedure for the optimal gain matrix minimizing this upper bound. The convergence analysis of this procedure is presented as well as an example illustrating its finite steps workability: it is shown that within a neighborhood of the optimal matrix gain the others provide less estimation performance.
Keywords :
continuous time systems; observers; robust control; state estimation; suboptimal control; averaged quadratic error; constant gain matrix; convergence analysis; globally Lipschitz condition; high-gain observer; numerical procedure; optimal gain matrix; state estimation; stationary stochastic nonlinear systems; stochastic continuous time nonlinear system; suboptimal robust asymptotic observer; upper bound; Convergence of numerical methods; Nonlinear systems; Observers; Performance analysis; Performance gain; Robustness; State estimation; Stochastic systems; Upper bound; Workability;
Conference_Titel :
Decision and Control, 2002, Proceedings of the 41st IEEE Conference on
Print_ISBN :
0-7803-7516-5
DOI :
10.1109/CDC.2002.1184228