2009 American Control Conference 2009
DOI: 10.1109/acc.2009.5160347
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State estimation for linear impulsive systems

Abstract: In this paper, we treat the fundamental problem of state estimation for a class of linear impulsive systems with time-driven impulsive effects. We show that a strong observability property enables an impulsive observer to be constructed that yields uniformly exponentially stable estimation error dynamics. This approach accommodates impulsive systems with arbitrarily-spaced impulse times and singular state transition matrices in a manner reminiscent of well-known results for time-varying discrete-time linear sy… Show more

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Cited by 43 publications
(29 citation statements)
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“…The notion of strong observability shown in [7] to be sufficient for the construction of an impulsive observer for (1) that produces an asymptotically convergent state estimate involves the existence a positive integer ᐉ* such that Qfixed(t0, tf, T) = 0 holds for all time intervals [t0, tf] impulse time sets T for which card{T പ (t0, tf)} Ն ᐉ*. As a special case of Theorem V.3, we have the following condition that is necessary and almost sufficient for strong observability.…”
Section: Observability Analysismentioning
confidence: 99%
“…The notion of strong observability shown in [7] to be sufficient for the construction of an impulsive observer for (1) that produces an asymptotically convergent state estimate involves the existence a positive integer ᐉ* such that Qfixed(t0, tf, T) = 0 holds for all time intervals [t0, tf] impulse time sets T for which card{T പ (t0, tf)} Ն ᐉ*. As a special case of Theorem V.3, we have the following condition that is necessary and almost sufficient for strong observability.…”
Section: Observability Analysismentioning
confidence: 99%
“…Conversely, if there exists an integer l such that the observability Gramian is positive definite for any impulse time set and any finite interval containing at least l impulse times, then the system is observable (Medina & Lawrence, 2009). Note that this criterion meets Definition 2.…”
Section: Observability On Some Time Intervalmentioning
confidence: 97%
“…The input u(τ k ) = 0, ∀k is considered without loss of generality. Proof of (1) ⇒ (2) is obtained from Theorem 2, but considering linear ICS and the proof of (1) ⇔ (3) can be found in Medina and Lawrence (2009), so it will be omitted here.…”
Section: Observability On Some Time Intervalmentioning
confidence: 99%
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