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Description: Design of 5.4.2 Kalman filter
This section will discuss how to use the control system toolbox to design and simulate Kalman filters. Consider the following discrete systems:
X [n+1] =Ax [n] +B (u [n] +w [n]) (5.9)
Y [n] =Cx [n] (5.10)
Among them, w [n] is the Gauss noise added at the input end. State matrix parameters are respectively
A = [1.1269-0.49400.1129
1
1];
B = [-0.3832
Zero point five nine one nine
0.5191];
C = [100];
Our goal is to design Kalman filters at given input u [n] and noise output measurements.
The output of the system is estimated in the case of YV [n] =Cx [n] +v [n]. Among them, v [n] is Gauss white noise.
1) discrete Kalman filter
The steady-state Kalman filter equations for the above problems are as follows:
Correction calculation of measurement value
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| kalman滤波的仿真\kalman.doc | 301568 | 2018-01-31
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