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A Sensorless Inverse Optimal Control plus Integral Action to Regulate the Output Voltage in a Boost Converter Supplying an Unknown DC Load

This study utilizes inverse optimal control (IOC) theory to address the issue of output voltage regulation in a boost converter feeding an unknown direct current (DC) load. The proposed approach involves developing a general feedback control law through IOC to ensure asymptotic stability in closed-l...

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Bibliographic Details
Published in:IEEE access 2023-01, Vol.11, p.1-1
Main Authors: Montoya, Oscar Danilo, Gil-Gonzalez, Walter, Riffo, Sebastian, Restrepo, Carlos, Gonzalez-Castano, Catalina
Format: Article
Language:English
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Summary:This study utilizes inverse optimal control (IOC) theory to address the issue of output voltage regulation in a boost converter feeding an unknown direct current (DC) load. The proposed approach involves developing a general feedback control law through IOC to ensure asymptotic stability in closed-loop operation, with the added advantage of incorporating an integral gain without compromising stability. Two estimators are introduced to minimize the number of sensors required for implementing the IOC controller with integral action. The first estimator, based on the immersion and invariance (I&I) method, determines the current demand of the DC load by measuring the boost converter's output voltage. While the second estimator, using the disturbance observer (DO) method, estimates the voltage input value by measuring the inductor's current flow. Both methods guarantee exponential convergence to the precise value of the estimated variable, irrespective of the initial estimation points. Experimental validation using varying DC loads and estimation techniques confirms the proposed IOC approach's effectiveness and robustness in regulating voltage for DC loads connected to a boost converter. Furthermore, the proposed controller is compared to the sliding mode control and presents a better performance with a more straightforward design, and the stability in closed-loop ensured.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2023.3277750