Filtering-Based Accelerated Estimation Approach for Generalized Time-Varying Systems With Disturbances and Colored Noises

This brief studies the parameter estimation problem of a generalized time-varying system by using a novel gradient descent algorithm. The time-varying parameters are estimated by the accelerating gradient descent algorithm under considering the measurable disturbance factors. The proposed algorithm increases the convergence rate by adding a momentum term to the correction of the parameter updated estimates. In addition, a data filter is introduced to filter the input and output data, so as to eliminate the interference of colored noise to the accuracy of parameter estimation. A numerical example shows the effectiveness of the proposed algorithm.