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Design and implementation of MPC for energy optimization of boiler in batch distillation column

Harjamulya H.a,b, Rusmin P.H.a,b, Hidayat E.M.I.a,b, Syaichu-Rohman A.a,b

a Control and Computer Systems Research Group, Bandung, Indonesia
b School of Electrical Engineering and Informatics, 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]© 2019, Institute of Advanced Engineering and Science. All rights reserved.A competency in the industrial world depends on several aspects, that is cost, delivery, flexibility, and quality. The smart industrial system/Smart Manufacturing System (SMS) tries to improve those aspects using the latest technology that encourages the use of digital information widely and quickly in industrial systems. Development of SM in industry 4.0, pushing the change of industrial pyramids into Cyber-Physical System (CPS). CPS has begun to be applied widely in process industries nowadays, i.e., distillation process industry. In distillation process, boiler has the important role to separate 2 different components using the difference of its boiling point. In this paper, the alcohol distillation plant is used to purify 30% of alcohol solution. The modelling of boiler, simulation, and implementation of boiler control system are presented to get the desired temperature. The temperature reference is roughly 85oC. Predictive Model Controller (MPC) and Kalman Filter is proposed to control the temperature of boiler by adjusting the PWM of on-off time and to deal with the disturbance and sensor noise. The IAE, ISE, and ITAE is analyzed to obtain the error of control system and energy usage per operation is also calculated to find out the effect of MPC controller in energy optimization.[/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][/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]Batch Distillation Column,CPS,Energy Optimization,Kalman Filter,Model Predictive Control[/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/10.23919/EECSI48112.2019.8977079[/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]