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Model predictive control design and performance analysis of a pasteurization process plant
Ananga, Hadisupadmo S.a, Leksono E.a
a Department of Engineering Physiscs, Faculty of Industrial Technology, Bandung Institute of Technology, Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2016 IEEE.Pasteurization is a process of heating food products at a specified temperature to eliminate micro bacteria contaminants that may endanger consumer health. In dairy food industries, the pasteurization process often set to achieve products’ temperature between 70°C to 75°C during 15 seconds. This paper reports the development of control system for a lab scale pasteurization process plant Armfield PCT23MKII which is equipped with programmable logic controller (PLC) Allen Bradley SLC 5/02 and OPC KepServer5 real time interface. A MATLAB based model predictive control (MPC) algorithm is developed for the mini plant and its performance is compared to standard PID and PID cascade controllers. Based on the experimental results, it was found that the developed MPC was capable of eliminating over shoot, achieve a fast settling time with an integral absolute error (IAE) of 3884 and energy consumption 613.2 kJ. In comparison with both the PID and PID cascade controllers, it is also shown that the proposed MPC algorithm has better performance in terms of adapting to load change and mitigating disturbances.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Cascade controller,Consumer healths,Food industries,Integral absolute errors,Performance analysis,Process plants,Programmable logic controllers (PLC),Real time interfaces[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Heat exchangers,Model predictive control,Pasteurization,PID control,Programmable logic controller[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/ICA.2016.7811480[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]