Intelligent-based PID fault tolerant tracking control for unknown nonlinear MIMO systems

Shu Mei Guo, Jason S.H. Tsai, Yen C. Lin, Tzong Jiy Tsai, Chia W. Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

In this paper, a novel intelligent-based fault tolerant control (FTC) framework is proposed to solve the fault tolerant tracking control problem for unknown nonlinear multi-input multi-output (MIMO) systems. To eliminate the effect of faults, a neural network model adapted with the extended Kalman filter (EKF) is created to online identify the unknown systems, and then the steepest descent and evolutionary programming (EP) method is utilized to find a self-tuning proportional-integral-derivative (PID) controller for the adapted neural network. The resulted PID FTC controller can not only achieve the tracking objective but also can maintain the stability and the expected performance when faults occur in system. Finally, a numerical example is given to illustrate the effectiveness of the proposed methods.

Original languageEnglish
Title of host publication2009 IEEE International Conference on Control and Automation, ICCA 2009
Pages331-336
Number of pages6
DOIs
Publication statusPublished - 2009 Dec 1
Event2009 IEEE International Conference on Control and Automation, ICCA 2009 - Christchurch, New Zealand
Duration: 2009 Dec 92009 Dec 11

Publication series

Name2009 IEEE International Conference on Control and Automation, ICCA 2009

Other

Other2009 IEEE International Conference on Control and Automation, ICCA 2009
CountryNew Zealand
CityChristchurch
Period09-12-0909-12-11

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Human-Computer Interaction
  • Control and Systems Engineering

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