Identification of Volterra kernels of nonlinear systems by separating overlapped kernel slices

This paper describes a method for identifying and separating Volterra kernels of nonlinear control systems by use of pseudorandom M-sequence and correlation technique. By use of this method, we can obtain Volterra kernels of up to 3rd order of a nonlinear system. M-sequence is applied to a nonlinear system and the crosscorrelation function between the input and output is calculated. Then the crosscorrelation function includes all the crosssections of Volterra kernels of the nonlinear system. The problem is how to separate these crosssections from each other. This paper proposes two methods for this purpose. One is the method of suitable selection of M-sequence which enables us to separate crosssections each other. The other is the use of amplitude variation method. Computer simulations show that this method for identification and separation of Volterra kernels of nonlinear system is very effective for identifying nonlinear control systems.