Combined state and parameter estimation for Hammerstein systems with time-delay using the Kalman filtering

Ma, Junxia and Ding, Feng and Xiong, Weili and Yang, Erfu (2017) Combined state and parameter estimation for Hammerstein systems with time-delay using the Kalman filtering. International Journal of Adaptive Control and Signal Processing, 31 (8). pp. 1139-1151. ISSN 0890-6327

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    Abstract

    This paper discusses the state and parameter estimation problem for a class of Hammerstein state space systems with time-delay. Both the process noise and the measurement noise are considered in the system. Based on the observable canonical state space form and the key term separation, a pseudo-linear regressive identification model is obtained. For the unknown states in the information vector, the Kalman filter is used to search for the optimal state estimates. A Kalman-filter based least squares iterative and a recursive least squares algorithms are proposed. Extending the information vector to include the latest information terms which are missed for the time-delay, the Kalman-filter based recursive extended least squares algorithm is derived to obtain the estimates of the unknown time-delay, parameters and states. The numerical simulation results are given to illustrate the effectiveness of the proposed algorithms.

    ORCID iDs

    Ma, Junxia, Ding, Feng, Xiong, Weili and Yang, Erfu ORCID logoORCID: https://orcid.org/0000-0003-1813-5950;