Fuzzy controller for a pneumatic positioning nonlinear system

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2 Citas (Scopus)

Resumen

The design of controllers for nonlinear uncertain dynamical systems is one of the most important challenging tasks in control engineering. In this paper, we propose a fuzzy system for controlling a nonlinear uncertain plant. We show that alternative techniques of fuzzy control can improve or complement conventional techniques in these kind of plants.

The case of use is a real pneumatic positioning system with no mechanically coupling with the final effector, and with nonlinearities and uncertainties. We used a webcam as a feedback sensor with an image processing algorithm.

Conventional control techniques for linear systems such as proportional-derivative (PD), proportional-integral (PI), and proportional-integral-derivative (PID), can be applied to control the pneumatic levitation system. However, its response is uncertain for the case of vertical position setpoint variations (due to different indices of turbulence along the tube) and in object characteristics (weight, shape, roughness and size). To overcome that problem, we designed a set of fuzzy control rules considering response of the system under conventional controllers and considering the non-linear dynamics of the plant. The optimal parameters of the conventional controllers were estimated through ITAE performance index. We show the performance of a PD, PI, PID and a fuzzy controller under the same operating conditions with a fixed set point. The results obtained for the proposed fuzzy control system, demonstrates good performance in rising time, settling time, reduced overshoot and greater flexibility than conventional (PD, PI and PID) controllers.

Idioma originalInglés
Título de la publicación alojadaNature-Inspired Computation and Machine Learning - 13th Mexican International Conference on Artificial Intelligence, MICAI 2014, Proceedings
EditoresAlexander Gelbukh, Félix A. Castro-Espinoza, Sofía N. Galicia-Haro
EditorialSpringer Verlag
Páginas370-381
Número de páginas12
ISBN (versión digital)9783319136493
DOI
EstadoPublicada - 2014
Publicado de forma externa
Evento13th Mexican International Conference on Artificial Intelligence, MICAI 2014 - Tuxtla Gutiérrez, México
Duración: 16 nov. 201422 nov. 2014

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen8857
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia13th Mexican International Conference on Artificial Intelligence, MICAI 2014
País/TerritorioMéxico
CiudadTuxtla Gutiérrez
Período16/11/1422/11/14

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