Combined Estimation of the Parameters and States for a Multivariable State-Space System in Presence of Colored Noise
This article addresses the combined estimation issues of parameters and states for multivariable systems in the state-space form disturbed by colored noises. By utilizing the Kalman filtering principle and the coupling identification concept, we derive a Kalman filtering based partially coupled recursive generalized extended least squares (KF-PC-RGELS) algorithm to jointly estimate the parameters and the states. Using the past and the current data in parameter estimation, we propose a Kalman filtering based multi-innovation partially coupled recursive generalized extended least-squares algorithm to enhance the parameter estimation accuracy of the KF-PC-RGELS algorithm. Finally, a simulation example is provided to test and compare the performance of the proposed algorithms.
International Journal of Adaptive Control and Signal Processing
Pre-print, post-print (12 month embargo)
Open Access Status
Cui, T., Chen, F., Ding, F., & Sheng, J. (2020). Combined Estimation of the Parameters and States for a Multivariable State-Space System in Presence of Colored Noise. International Journal of Adaptive Control and Signal Processing, n/a(n/a). https://doi.org/10.1002/acs.3101