AbstractThe motivation for the work reported in this paper accrues from the necessity of finding stabilizing control laws for systems with randomly varying bounded sensor delay. It reports the development of reduced-order linear unbiased estimators for discrete-time stochastic parameter systems and shows how to parametrize the estimator gains to achieve a certain estimation error covariance Both finite-time and steady-state estimators are considered. The results are potentially applicable to state estimation for stabilizing output feedback control systems
The optimal least-squares linear estimation problem is addressed for a class of discrete-time multis...
Linear minimum variance unbiased state estimation is considered for systems with uncertain parameter...
This thesis is concerned with estimation and control of linear distributed parameter systems. For t...
The motivation for the work reported in this paper accrues from the necessity of finding stabilizing...
AbstractThe motivation for the work reported in this paper accrues from the necessity of finding sta...
AbstractLinear unbiased full-order state estimation problem for discrete-time models with stochastic...
Linear unbiased full-order state estimation problem for discrete-time models with stochastic paramet...
This paper addresses the state estimation problem for stochastic systems with unknown measurement di...
The state estimation problem is studied for networked control systems (NCSs) subject to random commu...
This paper studies an optimal state estimation (Kalman filtering) problem under the assumption that ...
AbstractLinear unbiased full-order state estimation problem for discrete-time models with stochastic...
In this paper, we consider the robust filtering problem for discrete time-varying systems with delay...
In this paper, linear minimum variance unbiased state estimation is considered for signals with sens...
This paper is concerned with the linear unbiased minimum variance estimation problem for discrete-ti...
In this note, we study optimal estimation design for sampled linear systems where the sensors measur...
The optimal least-squares linear estimation problem is addressed for a class of discrete-time multis...
Linear minimum variance unbiased state estimation is considered for systems with uncertain parameter...
This thesis is concerned with estimation and control of linear distributed parameter systems. For t...
The motivation for the work reported in this paper accrues from the necessity of finding stabilizing...
AbstractThe motivation for the work reported in this paper accrues from the necessity of finding sta...
AbstractLinear unbiased full-order state estimation problem for discrete-time models with stochastic...
Linear unbiased full-order state estimation problem for discrete-time models with stochastic paramet...
This paper addresses the state estimation problem for stochastic systems with unknown measurement di...
The state estimation problem is studied for networked control systems (NCSs) subject to random commu...
This paper studies an optimal state estimation (Kalman filtering) problem under the assumption that ...
AbstractLinear unbiased full-order state estimation problem for discrete-time models with stochastic...
In this paper, we consider the robust filtering problem for discrete time-varying systems with delay...
In this paper, linear minimum variance unbiased state estimation is considered for signals with sens...
This paper is concerned with the linear unbiased minimum variance estimation problem for discrete-ti...
In this note, we study optimal estimation design for sampled linear systems where the sensors measur...
The optimal least-squares linear estimation problem is addressed for a class of discrete-time multis...
Linear minimum variance unbiased state estimation is considered for systems with uncertain parameter...
This thesis is concerned with estimation and control of linear distributed parameter systems. For t...