Konferensartikel

The paper is focused on practical aspects of advanced nonlinear identi?cation method applied to a real industrial process. Fuzzy identi?cation is used to model the air preparation stage within a system for reducing nitrogen oxides (NOx) emissions in exhaust air from the dryers and ovens in a factory of automotive catalytic converters. The system for NOx emissions reduction operates ef?ciently in predetermined temperature and air ?ow ranges of the exhaust air only. Due to those conditions, exhaust air from the dryers and ovens must be prepared in advance by controlling the ventilator speed and fresh air and exhaust air dampers positions. At the same time operating conditions of dryers and ovens have to be maintained within de?ned ranges. Currently used control system of the exhaust air preparation shows some de?ciencies, so a feasibility study of possible improvements has been carried out. Modelling presented in this paper has been used to evaluate and compare control solutions. The results show such an improvement is feasible. The proposed control system can be ready for implementation in the real process with minor changes of the controller parameters and supervisory logic settings.

fuzzy logic, Takagi-Sugeno model, catalytic converter, emission reduction, process control