Modelling and control of laboratory scale conveyor belt type grain dryer plant - Mansor, Hasmah; Khan, Sheroz; Gunawan, Teddy Surya (WFL Publisher Ltd, 2012)

(untitled)
This paper presents a modelling and control of conveyor belt type grain dryer plant using system identification and Quantitative Feedback Theory (QFT) technique. Modelling and control of grain dryer plant has been in dilemma due to the complexity in the process and uncertainty exists in the plant. Most existing models are inaccurate and consists of very complex equations which require considerable computational time to resolve. In this research, system identification is proposed as a method to model a conveyor belt type grain dryer. This approach is practically new as it has never been used as an identification method for conveyor belt type grain dryer. The process model is computed based on the input/output data collected from real-time experiment, instantaneously avoids inaccuracy in deriving model from first principle that normally involves assumptions and estimations. A robust controller, known as QFT has been used to control the complex grain drying process. Although QFT has been successfully applied to many plants with uncertainty, none of those applications involved any types of grain dryer. A comprehensive study on the application of QFT on a new plant, particularly grain dryer is beneficial in agricultural sector as well as control engineering. The non-linearity behaviour, delay and discrepancies of the process model are taken account as parameter uncertainty. Test results showed that the grain dryer plant with QFT-based controller meets the desired performance specifications. The superiority, efficiency and robustness of QFT-based controller are revealed when comparison test between QFT and PID controllers are performed.