Seo, JahoKhajepour, AmirHuissoon, Jan P.2017-04-032017-04-032014-08-01https://doi.org/10.1007/s12555-013-0348-6http://hdl.handle.net/10012/11621This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Control, Automation and Systems on August 2014, available online: http://dx.doi.org/10.1007/s12555-013-0348-6The thermal control of a die is crucial for the development of high efficiency injection moulds. For an effective thermal management, this research provides a strategy to identify a thermal dynamic model and to design a controller. The neural network techniques and finite element analysis enable modeling to deal with various cycle-times for moulding process and uncertain dynamics of a die. Based on the system identification which is experimentally validated using a real system, controllers are designed using fuzzy-logic and self-tuning PID methods with backpropagation and radial basis function neural networks to tune control parameters. Through a comparative study, each controller’s performance is verified in terms of response time and tracking accuracy under different moulding processes with multiple cycle-times.enFuzzy logicLaminated diePlastic injection mouldingSelf-tuning PID controlSystem identificationVarious cycle-timesArticle