Title :
LMI-based state estimator design for discrete-time stochastic systems with quadratic sum constraints
Author :
Yaz, Edwin Engin ; Yaz, Yvonne Ilke
Author_Institution :
Dept. of Electr. Eng., Arkansas Univ., Fayetteville, AR, USA
Abstract :
A general class of discrete-time uncertain nonlinear stochastic systems with quadratic sum constraints is considered. A linear full-order state estimator design is presented for various estimation error performance criteria in a unified framework. These performance criteria include guaranteed-cost suboptimal versions of estimation objectives like H2, H∞, stochastic passivity, etc. The design of linear state estimators that satisfy these criteria are given using a common linear matrix inequality (LMI) formulation
Keywords :
H∞ control; constraint theory; control system synthesis; discrete time systems; errors; matrix algebra; nonlinear systems; performance index; state estimation; stochastic systems; suboptimal control; uncertain systems; H∞ control; H2 control; discrete-time uncertain nonlinear stochastic systems; estimation error performance criteria; guaranteed-cost suboptimal estimation objectives; linear full-order state estimator design; linear matrix inequalities; quadratic sum constraints; state estimator design; stochastic passivity; Educational institutions; Equations; Estimation error; Linear matrix inequalities; Mathematics; Noise measurement; Power system modeling; State estimation; Stochastic processes; Stochastic systems;
Conference_Titel :
American Control Conference, 2001. Proceedings of the 2001
Conference_Location :
Arlington, VA
Print_ISBN :
0-7803-6495-3
DOI :
10.1109/ACC.2001.945517
