Advanced control system for nonlinear processes

In this paper, a fuzzy model predictive control (FMPC) approach is introduced to design a control system for a highly nonlinear process. In this approach, the process is described by a fuzzy convolution model that consists of a number of quasi-linear fuzzy implications (FI). In controller design, prediction errors and control energy are minimized through a two-layered iterative optimization process. Furthermore, fuzzy model based fault detection methods are elaborated envisaging fault tolerant control. Results from validation of the advanced control system are presented. A new concept of modular advanced control system designed for a seamless and gradual integration into the existing distributed control system is proposed.