The Gradient-Based Iterative Estimation Algorithms for Bilinear Systems with Autoregressive Noise

摘要

This paper considers the parameter identification problem of bilinear systems, which are a special class of nonlinear systems. The basic idea is giving the input-output representation of the bilinear system through eliminating the state variables in the system. By using the hierarchical identification principle and the data filtering technique, we derive a gradient-based iterative (GI) algorithm, a hierarchical GI algorithm and a filtering-based GI algorithm for identifying the parameters of bilinear systems with colored noises. The simulation results indicate that the proposed algorithms are effective for identifying bilinear systems.