Feedforward control design for nonlinear stable minimum phase systems using a new state space model structure

2007 ◽  
Author(s):  
K. Smolders ◽  
P. Sas ◽  
J. Swevers
Keyword(s):  
State Space ◽  
Feedforward Control ◽  
State Space Model ◽  
Control Design ◽  
Model Structure ◽  
Minimum Phase ◽  
Space Model ◽  
Phase Systems

State-Space Model and Kalman Filter Gain Identification by a Kalman Filter of a Kalman Filter

2017 ◽  
Vol 140 (3) ◽  
Author(s):  
Minh Q. Phan ◽  
Francesco Vicario ◽  
Richard W. Longman ◽  
Raimondo Betti
Keyword(s):  
Kalman Filter ◽  
Steady State ◽  
State Space ◽  
Kalman Filters ◽  
State Space Model ◽  
Model Structure ◽  
System State ◽  
Input Output ◽  
Output Data ◽  
Space Model

This paper describes an algorithm that identifies a state-space model and an associated steady-state Kalman filter gain from noise-corrupted input–output data. The model structure involves two Kalman filters where a second Kalman filter accounts for the error in the estimated residual of the first Kalman filter. Both Kalman filter gains and the system state-space model are identified simultaneously. Knowledge of the noise covariances is not required.

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