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Nonlinear tracking control of a cryogenic separation process
Tamba T.A.a, Nazaruddin Y.Y.b
a Dept. of Electrical Engineering (Mechatronics), 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 typically used to extract specific components of the air in high purity gas or liquid forms. This paper proposes a computational approach for synthesizing optimal and suboptimal tracking controllers for a nonlinear model of a cryogenic isotope separation process. The proposed method esssentially formulates a sum of squares (SOS) optimization problem for solving the state-dependent Riccati equation (SDRE) which arises in the considered nonlinear tracking control problem. More specifically, the paper first characterizes an optimal control law which forces the closed loop state trajectories to track a given reference signal and at the same time minimizes a quadratic performance index in an exact manner. Due to a computational issue which arises in synthesizing such an exact control law (i.e. the need to solve the SDRE), the paper then formulates SOS optimization problems for computing sub-optimal tracking control laws. A simulation example describing the design of a tracking controller for the cryogenic isotope separation process plant is then presented to illustrate the effectiveness of the proposed method.[/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]Computational approach,Cryogenic isotope separation,Cryogenic separation,Non-linear tracking control,Optimization problems,Quadratic performance indices,State-dependent Riccati equation,Sub-optimal tracking[/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][/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]*This work was supported by OGFICE 2017 program 1T. A. Tamba is with Dept. of Electrical Engineering (Mechatronics), Parahyangan Catholic University, Indonesia ttamba@unpar.ac.id 2Y. Y. Nazaruddin is with Instrumentation & Control Research Group, Institut Teknologi Bandung, Indonesia yul@tf.itb.ac.id[/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/ASCC.2017.8287610[/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]