The optimum "ltering results of Kalman "ltering for linear dynamic systems require an exact knowledge of the process noise covariance matrix Q I , the measurement noise covariance matrix R I and the initial error covariance matrix P . In a number of practical solutions, Q I , R I and P , are either
Smoothing properties of discrete-time zero-lag Kalman filter
✍ Scribed by Henryk Rubinstein
- Publisher
- Elsevier Science
- Year
- 1978
- Tongue
- English
- Weight
- 432 KB
- Volume
- 14
- Category
- Article
- ISSN
- 0005-1098
No coin nor oath required. For personal study only.
📜 SIMILAR VOLUMES
A comparison 1s performed between the discrete and contmuous lmplementatlon of Kalman filtenng and optimal control for a stationary process Theoretical resdts for a pilot-plant fixed-bed reactor are provided as an example It is demonstrated that the computational effort for the two implementations d
## Discrete tune hnear quadratlcoptlmalcontrol IS investigated experimentally on a catalytic fixedbed reactor with stochastic upstream disturbances It IS demonstrated that the discrete time vanance evaluated with time intervals equal to the control intervals oscillates along the reactor axis due t