7,089 research outputs found

    A State-Space Approach to Parametrization of Stabilizing Controllers for Nonlinear Systems

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    A state-space approach to Youla-parametrization of stabilizing controllers for linear and nonlinear systems is suggested. The stabilizing controllers (or a class of stabilizing controllers for nonlinear systems) are characterized as (linear/nonlinear) fractional transformations of stable parameters. The main idea behind this approach is to decompose the output feedback stabilization problem into state feedback and state estimation problems. The parametrized output feedback controllers have separation structures. A separation principle follows from the construction. This machinery allows the parametrization of stabilizing controllers to be conducted directly in state space without using coprime-factorization

    Attenuation of Persistent L∞-Bounded Disturbances for Nonlinear Systems

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    A version of nonlinear generalization of the L1-control problem, which deals with the attenuation of persistent bounded disturbances in L∞-sense, is investigated in this paper. The methods used in this paper are motivated by [23]. The main idea in the L1-performance analysis and synthesis is to construct a certain invariant subset of the state-space such that achieving disturbance rejection is equivalent to restricting the state-dynamics to this set. The concepts from viability theory, nonsmooth analysis, and set-valued analysis play important roles. In addition, the relation between the L1-control of a continuous-time system and the l1-control of its Euler approximated discrete-time systems is established

    H∞ Control of Nonlinear Systems: A Class of Controllers

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    The standard state space solutions to the H∞ control problem for linear time invariant systems are generalized to nonlinear time-invariant systems. A class of nonlinear H∞-controllers are parameterized as nonlinear fractional transformations on contractive, stable free nonlinear parameters. As in the linear case, the H∞ control problem is solved by its reduction to four simpler special state space problems, together with a separation argument. Another byproduct of this approach is that the sufficient conditions for H∞ control problem to be solved are also derived with this machinery. The solvability for nonlinear H∞-control problem requires positive definite solutions to two parallel decoupled Hamilton-Jacobi inequalities and these two solutions satisfy an additional coupling condition. An illustrative example, which deals with a passive plant, is given at the end

    ℋ∞ control of nonlinear systems via output feedback: controller parameterization

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    The standard state space solutions to the ℋ∞ control problem for linear time invariant systems are generalized to nonlinear time-invariant systems. A class of local nonlinear (output feedback) ℋ∞ controllers are parameterized as nonlinear fractional transformations on contractive, stable nonlinear parameters. As in the linear case, the ℋ∞ control problem is solved by its reduction to state feedback and output estimation problems, together with a separation argument. Sufficient conditions for ℋ∞-control problem to be locally solved are also derived with this machinery

    H∞ control of nonlinear systems: a convex characterization

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    The nonlinear H∞-control problem is considered with an emphasis on developing machinery with promising computational properties. The solutions to H∞-control problems for a class of nonlinear systems are characterized in terms of nonlinear matrix inequalities which result in convex problems. The computational implications for the characterization are discussed

    Electronic Preresonance Stimulated Raman Scattering Microscopy

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    Optical microscopy has generated great impact for modern research. While fluorescence microscopy provides the ultimate sensitivity, it generally lacks chemical information. Complementarily, vibrational imaging methods provide rich chemical-bond-specific contrasts. Nonetheless, they usually suffer from unsatisfying sensitivity or compromised biocompatibility. Recently, electronic preresonance stimulated Raman scattering (EPR-SRS) microscopy was reported, achieving simultaneous high detection sensitivity and superb vibrational specificity of chromophores. With newly synthesized Raman-active dyes, this method readily breaks the optical color barrier of fluorescence microscopy and is well-suited for supermultiplex imaging in biological samples. In this Perspective, we first review previous utilizations of electronic resonance in various Raman spectroscopy and microscopy. We then discuss the physical origin and uniqueness of the electronic preresonance region, followed by quantitative analysis of the enhancement factors involved in EPR-SRS microscopy. On this basis, we provide an outlook for future development as well as the broad applications in biophotonics

    Stimulated emission reduced fluorescence microscopy: a concept for extending the fundamental depth limit of two-photon fluorescence imaging

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    Two-photon fluorescence microscopy has become an indispensable tool for imaging scattering biological samples by detecting scattered fluorescence photons generated from a spatially confined excitation volume. However, this optical sectioning capability breaks down eventually when imaging much deeper, as the out-of-focus fluorescence gradually overwhelms the in-focal signal in the scattering samples. The resulting loss of image contrast defines a fundamental imaging-depth limit, which cannot be overcome by increasing excitation efficiency. Herein we propose to extend this depth limit by performing stimulated emission reduced fluorescence (SERF) microscopy in which the two-photon excited fluorescence at the focus is preferentially switched on and off by a modulated and focused laser beam that is capable of inducing stimulated emission of the fluorophores from the excited states. The resulting image, constructed from the reduced fluorescence signal, is found to exhibit a significantly improved signal-to-background contrast owing to its overall higher-order nonlinear dependence on the incident laser intensity. We demonstrate this new concept by both analytical theory and numerical simulations. For brain tissues, SERF is expected to extend the imaging depth limit of two-photon fluorescence microscopy by a factor of more than 1.8
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