Nonlinear Model Predictive Control Based on Stable Wiener and Hammerstein Models

The presented Nonlinear Model Predictive Control (NMPC) scheme based on stable Wiener and Hammerstein models retains the characteristics of conventional linear Model Predictive Control (MPC) including capabilities to control stable nonlinear processes. The future process behavior is predicted by the q-th degree Wiener and Hammerstein model represented by Volterra-series. The optimal manipulated variable is calculated minimizing a quadratic cost function depending on the nonlinear predictor subject to input and output constraints.