A least-parameterized method for subspace identification of Hammerstein systems

This paper is motivated by a dimension problem associated with the existing subspace identification methods (SIMs) for Hammerstein systems. The dimension problem is essentially caused by ignoring a rank constraint and may result in a low numerical efficiency. To resolve the dimension problem, we propose a new subspace-based method, named as the least-parameterized method (LPM), for identification of Hammerstein systems. Simulation results are provided to demonstrate the superior performance of the LPM, and to show the necessity of considering the rank constraint to improve the numerical efficiency.