Full State Feedback of DC-Motor Position and Speed Control Using LQR and Kalman Filter
DC motors are used in various industrial, robotic and motion control applications, and generally angular position and speed are used as the main control variables. This paper presents the design of an LQR controller with a Kalman Filter (KF) for state estimation during position and speed control of...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Estado: | Versión borrador |
| Fecha de publicación: | 2022 |
| País: | Colombia |
| Institución: | Universidad Tecnológica de Bolívar |
| Repositorio: | Repositorio Institucional UTB |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.utb.edu.co:20.500.12585/12227 |
| Acceso en línea: | https://hdl.handle.net/20.500.12585/12227 |
| Access Level: | acceso abierto |
| Palabra clave: | PID Controller; Voltage Regulators; Particle Swarm Optimization LEMB |
| Sumario: | DC motors are used in various industrial, robotic and motion control applications, and generally angular position and speed are used as the main control variables. This paper presents the design of an LQR controller with a Kalman Filter (KF) for state estimation during position and speed control of a DC motor. The proposed controller is evaluated for low and high speed reference profiles to demonstrate its efficiency in different types of applications. This approach is compared with the classical control method using a PID controller. From the results, it is observed that the settling time of the LQR-KF method is less, being 30% more efficient than the PID. In addition, the use of LQR provides an optimal state feedback control that minimizes the quadratic state error and control effort. The experimental results demonstrate the feasibility of the controller design for high precision applications. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. |
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