Soft Computing Based Cavity Temperature Control of Plastic Injection Molding system

Abstract

The plastic parts having complex three dimensional structures are produced by Plastic injection molding system. Thequality of the product is determined by controlling the temperature of the mold cavity. The mold cavity temperature controlwith the conventional ON/OFF, PI, and PID controllers have several disadvantages. This paper proposes the method toreduce settling time and undershoot in cavity temperature control with selected evolutionary algorithms. The controllerparameters are optimized with Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) Algorithm for PID and I-PDcontrollers by considering Mean Square Error (MSE) as fitness function. Compared to conventional methods theparameter optimization using soft computing methods such as GA and PSO improves the performance indices of PID andI-PD controllers.