Fault tolerant control based on adaptive LQG and fuzzy controllers

Carla Viveiros, Luis Brito Palma, José Manuel Igreja

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

Abstract

This paper describes a fault tolerant switching loop control study case for a three water tank laboratory setup with sensors and actuators redundancies. Fault diagnosis and tolerance are two main characteristics of intelligent setups when closed-loop control is used for large complex systems. Discrete adaptive LQG (linear quadratic) and Fuzzy fault tolerant controllers, for nominal situation, are presented and tested in the laboratory setup. For abrupt fault situation (structural fault), switching from one controller to another based on controller performance evaluation using PCA (principal component analysis) technique is implemented. The main contributions are: (a) proposed approach based on PCA to detect structural faults; (b) performance assessment based on performance index through Mahalanobis distance using T2 statistics and (c) control switching between LQG and Fuzzy controllers based on the performance index. Experimental results applied to a three-tank laboratory setup in the presence of a structural fault are shown to evaluate the performance of the proposed approach.

Original languageEnglish
Title of host publicationIntelligent Systems, Control and Automation
Subtitle of host publicationScience and Engineering
PublisherSpringer Netherlands
Pages143-154
Number of pages12
DOIs
Publication statusPublished - 2013

Publication series

NameIntelligent Systems, Control and Automation: Science and Engineering
Volume61
ISSN (Print)2213-8986
ISSN (Electronic)2213-8994

Keywords

  • Controller performance monitoring
  • Principal component analysis
  • Structural faults
  • Switching control

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  • Cite this

    Viveiros, C., Palma, L. B., & Igreja, J. M. (2013). Fault tolerant control based on adaptive LQG and fuzzy controllers. In Intelligent Systems, Control and Automation: Science and Engineering (pp. 143-154). (Intelligent Systems, Control and Automation: Science and Engineering; Vol. 61). Springer Netherlands. https://doi.org/10.1007/978-94-007-4722-7_14