Abstract
This paper deals with different aspects of modeling of a neutralization reaction and control of pH in a chemical pilot plant. The issue of modeling is significant for the design of controllers. The influence of different factors on the neutralization process has been analized and compared with the behaviour of the theoretical input/output representations. Finally, we propose a reduced, nonlinear dynamical model of the reactor. The design of control law is based on the decoupling and pole placement theories. Than a quadratic optimization control law with reference model has been proposed for the resulting linear subsystems. However, estimation in real time of one parameter is necessary to assure the efficient non interacting control. In order to make the optimal control law more robust a self-adaptive policy with fuzzy set theory has been designed in such a way that the parameters of the regulator determined by quadratic optimization can be adjusted according to dynamics of the process. A series of experiments is described. They show the efficiency of the decoupling control law based on parameter estimation and demonstrate the robustness of the fuzzy self-adaptive controller
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