MPC Relevant Identification Method for Hammerstein Models

MPC Controllers are widely applied in the process industry, notably in Oil Refining and Petrochemical processes. MPC Relevant Identification (MRI) methods have been developed to identify models suitable for linear MPC controllers. However, most chemical processes exhibit nonlinear dynamics, for which linear MPC controllers are suitable only for a limited operating range. This paper presents an MRI method for obtaining nonlinear models with polynomial Hammerstein structure. The algorithm is applied in the identification of data from an electric heater. The obtained results indicate that the proposed method generated satisfactory results.