Robust controller design for a nonlinear chemical process

In chemical industry most processes modeled by nonlinear equations, to design high-performance nonlinear controllers for efficient control of nonlinear processes to achieve closed-loop system’s stability and high performance. Design procedures proposed in this work rely strongly on the process model, difficulty addressed is identification of relatively simple model of nonlinear processes. The nonlinearity of the processes makes it difficult to obtain first-principles model used for analysis and design of the controller. Simple empirical models are chosen to represent nonlinear process for the design of controllers. The second difficulty is analysis of stability and performance for such models using nonlinear control theory is not straightforward. It is proposed in this study to investigate the stability and performance using a robust control approach. Nonlinear model is approximated by a nominal linear model combined with a mathematical description of model error to be referred to, in this work, as model uncertainty, with respect to the nominal linear model is due to the system nonlinearity. Then robust control theoretical tools applied for the design of controllers.