Susana Haydee Sainz-García

Ms. Susana Haydee Sainz-García

Centro Nacional de Investigación y Desarrollo Tecnológico, Cuernavaca, Morelos, Mexico
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Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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6 September 2022 in Mathematics
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Journal Article
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Susana Haydee Sainz-GarcíaSusana Haydee Sainz-García
Susana Haydee Sainz-García
GLGuadalupe Lopez Lopez
Guadalupe Lopez Lopez
VAVictor Alvarado
Victor Alvarado
Jesse Yoe Rumbo MoralesJesse Yoe Rumbo Morales
Jesse Yoe Rumbo Morales
ESEstela Sarmiento-Bustos
Estela Sarmiento-Bustos
Omar Ali ZatarainOmar Ali Zatarain
Omar Ali Zatarain
This paper presents an adaptive control scheme to face the challenge of rejecting input and output disturbances. The research is put on a layer of the design and start-up of chemical plants. The emphasis is on handling disturbances appearing in a narrow band of frequencies, which illustrates standard forms of disturbances in the alluded kind of systems. The controller is made up of a central RS structure that stabilizes the closed-loop plant. A second layer boosts the control law performance by adding the Youla–Kucera (YK) filter or Q parametrization and taking advantage of the internal model principle (IMP). This practice aids in modeling unknown disturbances with online control adjustment. We probe the resultant compensator for three non-isothermal continuous stirred tank reactors connected in series. The plant should conduct a first-order exothermic reaction consuming reactant A, while an isothermal operation stays and the outlet concentration is close to its nominal value. The primary concerns are open-loop instability and steady-state multiplicity in the plant’s first unit. The control objective is to reject input and output disturbances in a band of frequencies of 0.0002Hz to 0.007Hz, whether there are variants or not in time. We test the controller with input signals depicting both variations in the auxiliary services and abrupt changes. We then compare the executions of the resultant control law with a model-based predictive control (MPC). We find comparable responses to multiple disturbances. However, the adaptive control offers an effortless control input. We also conclude that the adaptive controller responds well to reference changes, while the MPC fails due to input constraints.