2016
DOI: 10.1016/j.ifacol.2016.10.245
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Observer-Based Sequential Control of a Nonlinear Two-Time-Scale System with Multiple Slow and Fast States

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Cited by 5 publications
(11 citation statements)
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“…In this manuscript, we verify that [1] covers another class of systems and an observer that cannot be covered by [2]. We have also checked that our results apply for plants in which the reduced (slow) system is such that nonlinear observers in [4] - [10] can be used to estimate the slow variables. As far as we are aware, there are no existing results dealing with SPA stability.…”
Section: Introductionmentioning
confidence: 61%
“…In this manuscript, we verify that [1] covers another class of systems and an observer that cannot be covered by [2]. We have also checked that our results apply for plants in which the reduced (slow) system is such that nonlinear observers in [4] - [10] can be used to estimate the slow variables. As far as we are aware, there are no existing results dealing with SPA stability.…”
Section: Introductionmentioning
confidence: 61%
“…Although boundedness of solutions of the full system can be assumed, we state it for two reasons, 1) this result is of interest in its own right and 2) some of the assumptions we state for this result are also needed to prove much stronger conclusion on the stability of the error dynamics. In our analysis, we compute the derivatives of 1 ( , ) and ( , , ), given in Assumptions 2 and 3, along the trajectories of (6). This leads to some terms representing the interconnections between the slow and the fast dynamics.…”
Section: Boundedness Of Solutions Of the Plantmentioning
confidence: 99%
“…Nevertheless, those observers are valid only locally and only work well when the system is evolving close to the equilibrium point considered for the linearisation. To counteract this problem, a wide variety of nonlinear observer design methods have been developed [1][2][3][4][5][6][7][8][9][10] , but these approaches may lead to ill-conditioned gains when used for systems exhibiting multiple time scales.…”
Section: Introductionmentioning
confidence: 99%
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