Control of nonlinear systems using polynomial ARMA models

Most of the advanced nonlinear control algorithms require a model of the system to be controlled. Unfortunately, most of the processes in the chemical industry are nonlinear, and fundamental models describing them are lacking. Thus there is a need for the identification and control of nonlinear systems through available inputoutput data. In this article, we briefly introduce the input‐output model used (polynomial ARMA models), and analyze its stability and invertibility. This paves the way to the development of a nonlinear‐model‐predictive controller. Implementation issues such as modeling of disturbance, state and parameter estimation are discussed. The theory presented is illustrated through examples.