2000
DOI: 10.1049/ip-cta:20000134
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Observer-based neuro identifier

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Cited by 21 publications
(13 citation statements)
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“…So it is still a challenge to suggest a workable technique to analyze the stability of the identification error generated by sliding-mode-type (discontinuous nonlinearity) observers [19,20,25].…”
Section: Introductionmentioning
confidence: 99%
“…So it is still a challenge to suggest a workable technique to analyze the stability of the identification error generated by sliding-mode-type (discontinuous nonlinearity) observers [19,20,25].…”
Section: Introductionmentioning
confidence: 99%
“…Remark 6: Assumption 4 is weaker than that in Yu, Moreno and Li (2000) where jh k 0 ðx, tÞj was required to have a constant bound. Because " A, " P and h k 0 ðx, tÞ are selected by the user, Equation (43) is not hard to be satisfied if F k 0 ðx, tÞ is bounded.…”
Section: Observer-based Identifiermentioning
confidence: 99%
“…Optimal selection method of " L, " Q and j to improve the transient performance of the model free observer can be seen in Yu et al (2000) and Xu and Zhang (2004) and references therein, which is not addressed in this article.…”
Section: Proof: Consider a Lyapunov Function Candidatementioning
confidence: 99%
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“…This expression provides stability condition of error terms in the presence of uncertainty and disturbance. Therefore the tracking error and its derivative are defined as below: It is necessary to be noted that ( ) P e T is not a square matrix and therefore pseudo inverse matrix is used to calculate u s vector [11]. The block diagram of the overall UPFC control system is depicted in fig.…”
Section: Y Bumentioning
confidence: 99%