LAPSE:2023.27670
Published Article
LAPSE:2023.27670
Super-Twisting Algorithm Applied to Velocity Control of DC Motor without Mechanical Sensors Dependence
April 4, 2023
Abstract
A DC motor velocity control in feedback systems usually requires a velocity sensor, which increases the controller cost. Additionally, the velocity sensor used in industrial applications presents several disadvantages such as maintenance requirements and signal conditioning. In this work, we propose a robust velocity control scheme applied to a DC motor based on estimation strategies using a sliding-mode observer. This means that measurements with mechanical sensors are not required in the controller design. The proposed observer estimates the rotational velocity and load torque of the motor. The controller design applies the exact-linearization technique combined with the super-twisting algorithm to achieve robust performance in the closed-loop system. The controller validation was carried out by experimental tests using a workbench, which is composed of a control and data acquisition Digital Signal Proccessor board, a DC-DC electronic converter, an interface board for signals conditioning, and a DC electric generator connected to an adjustable resistive load. The simulation and experimental results show a significant performance of the proposed control scheme. During tests, the accuracy, robustness, and speed response on the controller were evaluated and the experimental results were compared with a classic proportional-integral controller, which uses a conventional encoder.
Keywords
DC motor, sensorless, super-twisting, velocity control
Suggested Citation
Valenzuela FA, Ramírez R, Martínez F, Morfín OA, Castañeda CE. Super-Twisting Algorithm Applied to Velocity Control of DC Motor without Mechanical Sensors Dependence. (2023). LAPSE:2023.27670
Author Affiliations
Valenzuela FA: División Académica de Ingeniería y Arquitectura, Universidad Juárez Autónoma de Tabasco, Cunduacán 86040, Mexico [ORCID]
Ramírez R: División Académica de Ingeniería y Arquitectura, Universidad Juárez Autónoma de Tabasco, Cunduacán 86040, Mexico [ORCID]
Martínez F: División Académica de Ingeniería y Arquitectura, Universidad Juárez Autónoma de Tabasco, Cunduacán 86040, Mexico [ORCID]
Morfín OA: Departamento de Ingeniería Eléctrica y Computación, Instituto de Ingeniería y Tecnología, Universidad Autónoma de Ciudad Juárez, Chihuahua 32310, Mexico [ORCID]
Castañeda CE: Centro Universitario de los Lagos, Universidad de Guadalajara, Lagos de Moreno 47460, Mexico [ORCID]
Journal Name
Energies
Volume
13
Issue
22
Article Number
E6041
Year
2020
Publication Date
2020-11-19
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en13226041, Publication Type: Journal Article
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LAPSE:2023.27670
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https://doi.org/10.3390/en13226041
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Apr 4, 2023
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