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Global finite‐time stabilization via time‐varying output‐feedback for uncertain nonlinear systems with unknown growth rate

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Summary This paper considers the global finite-time output-feedback stabilization for a class of uncertain nonlinear systems. Comparing with the existing related literature, two essential obstacles exist: On the one hand,… Click to show full abstract

Summary This paper considers the global finite-time output-feedback stabilization for a class of uncertain nonlinear systems. Comparing with the existing related literature, two essential obstacles exist: On the one hand, the systems in question allow serious parametric unknowns and serious time variations coupling to the unmeasurable states, which is reflected in that the systems have the unmeasurable states dependent growth with the rate being an unknown constant multiplying a known continuous function of time. On the other hand, the systems possess remarkably inherent nonlinearities, whose growth allows to be not only low-order but especially high-order with respect to the unmeasurable states. To effectively cope with these obstacles, we established a time-varying output-feedback strategy to achieve the finite-time stabilization for the systems under investigation. First, a time-varying state-feedback controller is constructed by adding an integrator method, and by homogeneous domination approach, a time-varying reduced-order observer is designed to precisely rebuild the unmeasurable states. Then, by certainty equivalence principle, a desired time-varying output-feedback controller is constructed for the systems. It is shown that, as long as the involved time-varying gain is chosen fast enough to overtake the serious parametric unknowns and the serious time variations, the output-feedback controller renders that the closed-loop system states converge to zero in finite time. Copyright © 2017 John Wiley & Sons, Ltd.

Keywords: finite time; output feedback; time varying; time; varying output

Journal Title: International Journal of Robust and Nonlinear Control
Year Published: 2017

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