Actuators (Apr 2022)

PI Speed Control with Reverse Motion of a Series DC Motor Based on the Noise Reduction Disturbance Observer

  • Jesús Ulises Liceaga-Castro,
  • Irma Irasema Siller-Alcalá,
  • Jesús Daniel González-San Román,
  • Roberto Alfonso Alcántara-Ramírez

DOI
https://doi.org/10.3390/act11050117
Journal volume & issue
Vol. 11, no. 5
p. 117

Abstract

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In this paper, the speed control of a series DC motor is presented together with the electronics necessary to ensure inverse motion. The control law is based on the classical PI controller and the noise reduction disturbance observer (NRDOB). This control strategy allows the use of a linear approximation of the motor dynamics due to its excellent properties regarding model uncertainties, sensor noise, and external perturbations. Consequently, a linear model based on the nonlinear modelling with magnetic saturation of the motor is also presented. The NRDOB-based control frequency-domain approach allows for the treating of structured and unstructured disturbances in the spirit of classical control theory. Although PI controllers have proved to provide excellent performance and robustness for the speed control of series DC motor, it cannot cope, without affecting or reducing the performance, with the effects of sensor noise; moreover, to further improve the performance, especially in tracking conditions, it is necessary to design and implement a power driver capable of generating inverse motion. In addition, because NRDOB is in fact an internal model control strategy, a perfect match between process and model is not required. That is, contrary to the common belief that the NRDOB is a 2-DOF, it is in fact a 3-DOF control scheme. Based on these characteristics, it was possible to design and implement a robust high-performance speed control system with reverse motion for the non-linear series DC motor with not well-defined relative degree, together with the electronics required for the reverse motion which is fully described. This results in a control system capable of overcoming the problems generated by input disturbances and sensor noise, ensuring robustness and performance in tracking and regulation conditions. Real-time experimental results are included in support of the approach presented here.

Keywords