| Design Case Studies | ![]() |
This final case study illustrates the use of the Control System Toolbox for Kalman filter design and simulation. Both steady-state and time-varying Kalman filters are considered.
with additive Gaussian noise
on the input
and data
A = [1.1269 -0.4940 0.1129
1.0000 0 0
0 1.0000 0];
B = [-0.3832
0.5919
0.5191];
C = [1 0 0];
Our goal is to design a Kalman filter that estimates the output
given the inputs
and the noisy output measurements
where
is some Gaussian white noise.
| MIMO LQG Design | Discrete Kalman Filter | ![]() |