Igital redesign of the decentralized adaptive control for linear large-scale systems with actuator faults

Jason Sheng-Hon Tsai, M. H. Lin, Shu-Mei Guo, P. Y. Sun, L. S. Shieh, C. R. Liu

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

Abstract

A novel digital redesign of the analog model-reference-based decentralized adaptive controller is proposed for the sampled-data large scale system consisting of N interconnected linear subsystems with actuator faults. The adaptation of the analog controller gain is derived by using the model-reference adaptive control theory based on Lyapunov method. In this paper, it is shown that the sampled-data decentralized adaptive control system is theoretically possible to asymptotically track the desired output with a specified performance even when actuator faults occur. Then, a method of actuator fault recovery is proposed. With the estimated faults, one can use the proposed input compensation method to solve actuator faults. In this paper, we also introduce a prediction-based digital redesign method to develop the corresponding sampled-data controller for the sampled-data decentralized adaptive control systems.

Original languageEnglish
Title of host publicationProceedings of the 10th IASTED International Conference on Control and Applications, CA 2008
Pages107-112
Number of pages6
Publication statusPublished - 2008 Dec 1
Event10th IASTED International Conference on Control and Applications, CA 2008 - Quebec City, QC, United States
Duration: 2008 May 262008 May 28

Publication series

NameProceedings of the 10th IASTED International Conference on Control and Applications, CA 2008

Other

Other10th IASTED International Conference on Control and Applications, CA 2008
CountryUnited States
CityQuebec City, QC
Period08-05-2608-05-28

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Control and Systems Engineering

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