Combined state and multi-innovation parameter estimation for an input non-linear state-space system using the key term separation

摘要

In this study, the authors study the state and parameter estimation problem for an input non-linear system consisting of a static non-linear block and a linear time-invariant state space subsystem. Using the filtering technique, a filtering based multi-innovation generalised stochastic gradient (SG) algorithm is proposed for avoiding estimating the redundant parameters based on the key term separation technique. Compared with the multi-innovation generalised SG algorithm, the proposed algorithm has higher parameter estimation accuracy. Two simulation examples are provided to show that the proposed algorithm works well.