Decoupled Parameter Estimation Methods for Hammerstein Systems by Using Filtering Technique

The implementation of parameter estimation of Hammerstein systems is much difficult due to the existing parameter products from the nonlinear block and the linear block. This paper directly decomposes the parameter coupling between the nonlinear part and the linear part in a Hammerstein system by using the estimated parameter polynomial of the coupled linear part to filter the Hammerstein system, transforms the Hammerstein system into two forms, and investigates two decoupled parameter estimation methods: the one-step decoupled least squares estimation method and the two-step decoupled least squares estimation method corresponding to the two forms. Furthermore, the computational complexity is compared between the proposed two estimation algorithms. The simulation results show the effectiveness of the proposed two estimation methods with a similar estimation accuracy.

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