Fuzzy controller for a pneumatic positioning nonlinear system

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2 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publicationNature-Inspired Computation and Machine Learning - 13th Mexican International Conference on Artificial Intelligence, MICAI 2014, Proceedings
EditorsAlexander Gelbukh, Félix A. Castro-Espinoza, Sofía N. Galicia-Haro
PublisherSpringer Verlag
Pages370-381
Number of pages12
ISBN (Electronic)9783319136493
DOIs
StatePublished - 2014
Externally publishedYes
Event13th Mexican International Conference on Artificial Intelligence, MICAI 2014 - Tuxtla Gutiérrez, Mexico
Duration: 16 Nov 201422 Nov 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8857
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference13th Mexican International Conference on Artificial Intelligence, MICAI 2014
Country/TerritoryMexico
CityTuxtla Gutiérrez
Period16/11/1422/11/14

Keywords

  • Control of non-linear uncertain systems
  • Fuzzy controller
  • PID controller
  • Performance index
  • Rule base

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