Real-time control systems rely on reliable estimates of states and parameters in order to
provide accurate and safe control of electro-mechanical systems. The task of extracting state …

An elementary introduction to Kalman filtering Page 1 122 COMMUNICATIONS OF THE ACM |
NOVEMBER 2019 | VOL. 62 | NO. 11 review articles KALMAN FILTERING IS a state estimation …

A dual implementation of the Kalman filter is proposed for estimating the unknown input and
states of a linear state-space model by using sparse noisy acceleration measurements. The …

This paper addresses the problem of simultaneously estimating the state and the input of a
linear discrete-time system. A recursive filter, optimal in the minimum-variance unbiased …

This paper extends previous work on joint input and state estimation to systems with direct
feedthrough of the unknown input to the output. Using linear minimum-variance unbiased …

An algorithm is presented for jointly estimating the input and state of a structure from a
limited number of acceleration measurements. The algorithm extends an existing joint input …

Industrial cyber-physical systems (ICPSs) are widely applied in critical infrastructures such
as chemical plants, water distribution networks, and power grids. However, they face various …

A method is developed for the state estimation of linear time-varying discrete systems with
unknown inputs. By making use of the two-stage Kalman filtering technique and a proposed …

A new method is developed for the state estimation of linear discrete-time stochastic systems
in the presence of an unknown disturbance. The filter obtained is optimal in the unbiased …

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 …