Twin Support Vector Machine Method for Identification of Wiener Models

Abstract EN

Twin support vector regression is applied to identify nonlinearWiener system, consisting of a linear dynamic block in series with static nonlinearity.

The linear block is expanded in terms of basis functions, such as Laguerre or Kautzfilters, and the static nonlinear block is determined using twin support vector machineregression.

Simulation of a control valve model and pH neutralization process have beenpresented to show the features of the proposed algorithm over support vector machinebased algorithm.