Design and Development of an Optimized Fuzzy Proportional-Integral-Derivative Controller using Genetic Algorithm

The polymerization of resin adhesives, which is highly nonlinear, is chosen as a control process in this paper. When phenol and formaldehyde are mixed, a sudden and unpredictable heat is produced due to an exothermic reaction, which could cause the deviation of process temperature and hence diminish the product quality. Therefore, temperature control is necessitated for exothermic batch reactor. The most common approach used in industries is proportional-integral-derivative (PID) controller, which is tuned by the operators based on their experience and knowledge on the process, and hence, may not be precise in control since the process dynamic is changing rapidly. Therefore, this paper aims to design an auto-tuning PID controller for nonlinear exothermic process control. This paper presents fuzzy PID (FPID) and Genetic Algorithm-optimized fuzzy PID (GAFPID) controllers. In FPID controller, PID gains are tuned by fuzzy system. In GAFPID controller, the inner loop is a FPID controller and the outer loop is GA controller, which is used to optimize the fuzzy membership functions. The performances of these controllers are investigated in MATLAB-SIMULINK. From the results, it can be concluded that GAFPID controller provides a better control in the nonlinear exothermic process due to its robustness against the variable time delay and inconsistent exothermic heat.