2003
DOI: 10.1016/s0005-1098(03)00087-6
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Unknown disturbance inputs estimation based on a state functional observer design

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Cited by 218 publications
(129 citation statements)
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“…That leads to a large number of elegant approaches to develop the disturbance observer as well as improve its performance. Xiong and Saif have proposed a state functional disturbance observer to estimate disturbances with a bounded error (8) . In this method, the disturbance observer state does not precisely track the system states, which is an advantage that simplifies the estimation error dynamics.…”
Section: Introductionmentioning
confidence: 99%
“…That leads to a large number of elegant approaches to develop the disturbance observer as well as improve its performance. Xiong and Saif have proposed a state functional disturbance observer to estimate disturbances with a bounded error (8) . In this method, the disturbance observer state does not precisely track the system states, which is an advantage that simplifies the estimation error dynamics.…”
Section: Introductionmentioning
confidence: 99%
“…모의실험에 사용된 시스템은 논문 [11,16]의 시스템에서 외 란 행렬을 수정한 식 (24)이다. 제안하는 외란 관측기의 전달함수는 식 (5)와 같고, 기존의 상수 외란 관측기의 전달함수는 아래 식과 같다 [11].…”
Section: 모의실험unclassified
“…The input observability problem was addressed by Patton in (Hou & Patton, 1998) who gave some necessary and sufficient conditions to prove input observability for linear time invariant systems with unknown initial conditions. As far as the observer is concerned, Xiong (Xiong & Saif, 2003) proposed an Unknown Input Decoupled Functionnal Observer (UIDFO) which has no boundedness conditions as for time varying inputs and does not require differentiation of the measured outputs. The fact remains that control surfaces offer redundancies that make aileron failures not isolable.…”
Section: Fault Diagnosismentioning
confidence: 99%
“…In this part, results established in (Xiong & Saif, 2003) are recalled. The following dynamic system driven by both known and unknown inputs is considereḋ…”
Section: The Unknown Input Decoupled Functional Observermentioning
confidence: 99%
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