|Maximum likelihood estimation method for dual-rate Hammerstein systems
Dong-Qing Wang*, Zhen Zhang and Jin-Yun Yuan
International Journal of Control, Automation, and Systems, vol. 15, no. 2, pp.698-705, 2017
Abstract : "For a dual-rate sampled Hammerstein controlled autoregressive moving average (CARMA) system, this
paper uses the polynomial transformation technology to obtain its dual-rate bilinear identification model which
is suitable for the available dual-rate sampled-data, uses the maximum likelihood principle to construct a unified
parameter vector of all parameters and an information vector formed by the derivative of the noise variable to
the unified parameter vector, and directly identifies the parameters of the linear block and the nonlinear block
for the dual-rate Hammerstein CARMA system. The unified parameter vector contains the minimum number of
the unknown parameters, and the proposed maximum likelihood estimation algorithm has higher computational
efficiency than the over-parameterization model based least squares algorithm"
Dual-rate sampled system, Hammerstein system, maximum likelihood, polynomial transformation,system identification.