Knowledge of the process noise covariance matrix

is essential for the application of Kalman filtering. However,

it is usually a difficult task to obtain an explicit expression of

for large time varying systems. This paper looks at an adaptive

Kalman filter method for dynamic harmonic state estimation and

harmonic injection tracking.-Knowledge of the process noise covariance matrix is essential for the application of Kalm an filtering. However, it is usually a difficult task to obtain an expli cit for large expression of time varying system s. This paper looks at an adaptive Kalman filter method for dynamic estimation a harmonic state nd harmonic injection tracking.