An Input-Constrained Reduced-Order Observer and NARMAX Model-Based Adaptive Tracker with Fault Tolerance for Unknown Systems with an Input-Output Direct Feed-Through Term

論文翻譯標題: 適用於具有輸入-輸出直接傳輸項及輸入飽和限制之未知系統的降階觀測器與NARMAX為基礎之自調式容錯追蹤器
  • 許 文騰

學生論文: Doctoral Thesis

摘要

This dissertation proposes an input-constrained reduced-order observer-based adaptive tracker with fault tolerance for unknown nonlinear stochastic systems with an input-output direct feed-through term to obtain good tracking performance The major contributions of this dissertation are stated as follows: Firstly realization of causal current output-based optimal full/reduced-order observer and tracker for the linear sampled-data system with a direct transmission term from input to output is newly proposed Furthermore the time derivative of the control input existed in the continuous-time reduced-order observer can be avoided in the proposed one for the continuous-time system with an input-output feed-through term Secondly an active full-order fault tolerance tracker using the modified nonlinear autoregressive moving average with exogenous inputs (NARMAX) model for state-space self-tuning control (STC) of unknown nonlinear stochastic hybrid systems with a direct transmission term is proposed For the system identification process the initial parameters of the modified NARMAX model assigned by the off-line OKID and can speed up the convergence speed of the recursive extended least squares (RELS) method to determine a reliable dynamic model Moreover the modified state-space self-tuning control methodology due to the NARMAX model can quickly make an appropriate reaction to the variation of system parameters when the abrupt input fault and/or the gradual input fault occurs Finally an input-constrained reduced-order observer-based self-tuner with fault tolerance for unknown nonlinear stochastic systems with an input-output direct feed-through term has been proposed Some illustrative examples are given to demonstrate the effectiveness of the proposed methodologies
獎項日期2014 七月 28
原文English
監督員Jason Sheng-Hon Tsai (Supervisor)

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