Unbiased minimum variance estimation for systems with unknown exogenous inputs
نویسندگان
چکیده
A new method is developed for the state estimation of linear discrete-time stochastic system in the presence of unknown disturbance. The obtained filter is optimal in the unbiased minimum variance sense. The necessary and sufficient conditions for the existence and the stability of the filter are given.
منابع مشابه
A Unified Solution to Unbiased Minimum-Variance Estimation for Systems with Unknown Inputs
A parameterized three-stage Kalman filter (PTSKF) is proposed, serving as a unified solution to unbiased minimum-variance estimation for systems with unknown inputs that affect both the system and the outputs. The PTSKF is characterized by two design parameters and includes three parts: one is for the main system state estimate, the second is for the optimal unknown inputs estimate, and the las...
متن کاملA Unified Framework for Simultaneous Input and State Estimation of Linear Discrete-time Stochastic Systems
In this paper, we present a unified optimal and exponentially stable filter for linear discrete-time stochastic systems that simultaneously estimates the states and unknown inputs in an unbiased minimum-variance sense, without making any assumptions on the direct feedthrough matrix. We also provide the connection between the stability of the estimator and a system property known as strong detec...
متن کاملA Unified Filter for Simultaneous Input and State Estimation of Linear Discrete-time Stochastic Systems
In this paper, we present a unified optimal and exponentially stable filter for linear discrete-time stochastic systems that simultaneously estimates the states and unknown inputs in an unbiased minimum-variance sense, without making any assumptions on the direct feedthrough matrix. We also provide the connection between the stability of the estimator and a system property known as strong detec...
متن کاملThree-stage Kalman filter for state and fault estimation of linear stochastic systems with unknown inputs
The paper studies the problem of simultaneously estimating the state and the fault of linear stochastic discrete-time varying systems with unknown inputs. The fault and the unknown inputs affect both the system state and output. However, if the dynamical evolution models of the fault and the unknown inputs are available the filtering problem is solved by the Optimal Three-Stage Kalman Filter (O...
متن کاملUnbiased Inversion-Based Fault Estimation of Systems with Non-Minimum Phase Fault-to-Output Dynamics
We propose a framework for inversion-based estimation of certain categories of faults in discrete-time linear systems. First, we develop a novel methodology for direct estimation of unknown inputs by using only measurements of either minimum or non-minimum phase systems as well as systems with transmission zeros on the unit circle. The unknown input is reconstructed from its projections onto tw...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Automatica
دوره 33 شماره
صفحات -
تاریخ انتشار 1997