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Optimal control of a nonlinear cryogenic separation process via SDRE method
Tamba T.A.a, Nazaruddin Y.Y.b
a Department of Electrical Engineering, Parahyangan Catholic University, Indonesia
b Instrumentation and Control Research Group, Institut Teknologi 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]© 2017 IEEE.The cryogenic separation process is an air separation technology which is used to produce specific components of the air in gases or liquid form with high purity. This technology is frequently used in liquified natural gas (LNG) industries, nuclear isotopes separation and cryogenic fuels production for space shuttle. This paper proposes an optimal control design method for a nonlinear model of a cryogenic separation process. The method combines the state-dependent Riccati equation (SDRE) method and the sum of squares (SOS) optimization technique. The paper first characterizes a stabilizing control law which minimizes a quadratic performance index of the process in an exact manner. Due to the difficulties in synthesizing such an exact optimal control (i.e. due to the need to solve the SDRE), the use SOS optimization techniques for computing sub-optimal control laws is then introduced. The proposed method is illustrated through the design of a controller which maximizes the fraction of a particular isotope production in a cryogenic separation process plant.[/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]Cryogenic separation,Liquified natural gas,Optimal control design,Optimal controls,Optimization techniques,Quadratic performance indices,Stabilizing control law,State-dependent Riccati equation[/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]Cryogenic separation process,optimal control,state-dependent Riccati equation[/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]The authors gratefully acknowledge financial support from the Osaka Gas Foundation of International Cultural Exchange (OGFICE) program under project no. 3395a/ I1.C06.2/PL/2016, Institut Teknologi Bandung, 2017.[/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.2017.8068429[/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]