Optimal Fuzzy Control Of Batch Polymerization Reactors: Application To Pmma Production For Biomedical Purposes

The use of polymers in the biomedical field requires that such materials have a high degree of purity and specific properties, so that their production processes must be continuously monitored and manipulated. However, the control of polymerization reactors is considered a challenging task since such systems present non-linear and transient behaviour. In this study, in order to produce poly(methyl methacrylate) scaffolds for bone tissue engineering applications, an advanced control methodology based on fuzzy models and genetic algorithms (GA) was developed to control the temperature of a pilot-scale jacketed batch reactor in which methyl methacrylate polymerization takes place. Firstly, an optimal temperature trajectory was estimated using GA. Then, a fuzzy controller was designed and applied to adjust the reactor temperature to the instantaneous profile previously calculated. The proposed control algorithm was compared to conventional PID controller, proving to be robust and more suitable and reliable for such process type.