Modeling and controller design of a hot air blower system

• Main Author: Wan Salihin Wong, Khairul Nizar Syazwan
• Format: Thesis
• Language: English
• Published: 2014
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utm.my/id/eprint/48824/25/KhairulNizarSyazwanMFKE2014.pdf; http://eprints.utm.my/id/eprint/48824/; http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:83688

This research describes the modeling and controller design of a hot air blower system (HABS). The purpose of this research is to obtain model estimation best fit over 90%. Furthermore, the purpose of this research is to design controllers which the overshoot percentage close to zero percent and obtain a shorter rise time compare to current hot air blower system. The research divided into 3 area of focus, first focus on the development of Pseudo-Random Binary Sequences (PRBS) controller prototype to use as a System Identification Tool. The development of the controller was designed using PIC controllers. Testing was being conducted to ensure the controller is fully operational. Next, the output data from the hot air blower system (HABS) was captured for analysis. Second, the research focused on the modeling of a hot air blower system using System Identification and Estimation approach. By obtaining the mathematical model of a hot air blower system, tuning can be made possible. The output data was being run on MATLAB to compare between several of model structures. Model structures selected for this research are Auto-Regressive with eXogeneous inputs (ARX), Auto-Regressive Moving-Average with eXogeneous inputs (ARMAX), Output Error (OE) and Box–Jenkins (BJ). Result shows the eXogeneous inputs (ARX) obtained the highest best fit which best resemble the dynamic system of a hot air blower system (HABS) and was selected to be implemented in the controllers. Third area of focus is the simulation design of controllers; controllers which were selected for this research were PID controllers, Self-tuning controllers and Fuzzy controllers. The result obtained are shown in the Result and Analysis chapter, all controllers obtained zero overshoot percentage and have a shorter rise time then the current hot air blower system. Results showed the different in rise time, peak time, delay time and percentage overshoot varies depending on the controller. So, depending on the purpose in the industrial application, engineers can pick any controller to meet their desire task.