A model-based control system design for a coffee roasting process

Abstract

Coffee roasting is both a science and an art. Various models have been proposed in order to model the coffee roasting process. A model developed by Schwartzberg (2002) and validated by Vosloo (2016) is used in this study to develop a control strategy for a batch rotating-drum coffee roaster. The control strategy is based on experimentally determined parameters, and validated by simulated data. In addition to the control strategy the controllability of the process is investigated. It was experimentally determined that there is an initial time frame (90 seconds) during the roasting process that is deemed uncontrollable, most likely due to evaporative cooling taking place during the initial drying phase of the roasting process. The coffee roasting process was determined to be a lag-dominant first-order plus time delay process which may be approximated, and therefore modelled as a pure integrating system with an average dead-time of 20 seconds. This is in accordance with Hugo (2017) and Ruscio (2010). Initially a relative gain array (RGA) analysis was conducted based on simulated data to determine the best pairing of manipulated and controlled variables, in order to meet the control objective which is the recreating of a roast profile (i.e. the time vs. temperature plot of the roasted bean batch). The final control strategy is based on the RGA results recommending a single-input single-output (SISO) control system utilising the derivative of the roast profile as controlled variable, and the liquid petroleum gas (LPG) flow to the system as manipulated variable. A possible threshold control strategy to be used in combination with the developed control strategy is discussed qualitatively. The control design methods used were the internal model control (IMC) (based on the pure integrating approximation of the process), the Cohen and Coon and integral of the time-weighted absolute error (ITAE) methods (based on the actual lag-dominant first-order plus time delay behaviour of the process). The best performing controller was determined to be an IMC-based PI controller that utilises the average determined process parameters. This controller was fine-tuned in order to enhance its performance. The stability margins of the final controller were analysed using Bode plots. Keywords: Model-based control, pure integrator, coffee roasting, roast profile, roast profile derivative, parameter scheduling.