Nonlinear Internal Model Control for Miso Systems Based on Local Linear Neuro-fuzzy Models

The internal model control (IMC) scheme has been widely applied in the field of process control. So far, IMC has been mainly applied to linear processes. This paper discusses the extension of the IMC scheme to nonlinear processes based on local linear models where the properties of linear design procedures can be exploited. The IMC scheme results in controllers that are comparable to gain-scheduled PI or PID controllers which are the standard controllers in process industry. In practice, the tuning of conventional PI or PID controllers can be very time-consuming whereas the IMC design procedure is very simple and reliable. In this paper, the design effort of the IMC and conventional controller design methods will be discussed and control results will be compared by application to nonlinear control of an industrial-scale heat exchanger. Copyright c © 2002 IFAC