- 02 Identification of Disturbance Covariances Using Maximum Likelihood Estimation ∗

@inproceedings{Zagrobelny20140I,
  title={- 02 Identification of Disturbance Covariances Using Maximum Likelihood Estimation ∗},
  author={Megan Zagrobelny and James B. Rawlings},
  year={2014}
}
Disturbance model identification is necessary both for estimator design and controller performance monitoring. Here we present a maximum likelihood estimation (MLE) method to identify process and measurement noise covariances. By writing the outputs in terms of the process and measurement noises, we form a normal distribution for the sequence of… CONTINUE READING