A multilinear model for parameter identification of partially known systems

A parameter identification problem which arises in adaptive control for partially known systems is studied is this paper. The systems under consideration are linear and time invariant, but they can be represented by a nonlinear parametric model which is polynomial in unknown physical parameters, as opposed to the linear parametric model used in most black-box identification problem. A multilinear parametrization approach is proposed and a identification algorithm based on the multilinear model is developed. The properties of the multilinear identification algorithm are explored and analyzed. Simulation results are also presented to demonstrate the effectiveness of the proposed algorithm.<>