Unbiased minimum-variance estimation for systems with measurement-delay and unknown inputs
- Resource Type
- Conference
- Authors
- Cui, Beibei; Song, Xinmin; Tian, Lin
- Source
- 2018 Chinese Automation Congress (CAC) Automation Congress (CAC), 2018 Chinese. :514-519 Nov, 2018
- Subject
- Aerospace
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Delays
State estimation
Technological innovation
Mathematical model
Covariance matrices
- Language
This paper considers the problem of simultaneously estimating the state and the unknown input for linear discrete-time systems with measurement delay. Firstly, the reorganized innovation analysis approach is applied to deal with measurement delay and the measurement delay model is converted into a measurement delay free model. A recursive filter where the estimation of the state and the input are interconnected is proposed. Then we utilize the innovation to obtain the unknown input estimator by least-squares estimation and the optimal state estimator is constructed by transforming into a standard Kalman filtering in terms of two Riccati equations with the same dimension as the state model. Finally we give a numerical example to show that our estimation approach is effective.