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By imposing some restrictions on the open-loop system, two classes of observer based output feedback controllers, one being finite dimensional and the other infinite dimensional, are constructed.
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Three classes of observer-based controls are proposed and the maximal perturbed bound is given.
They draw attention to a vast range of facts concerning the variety of conditions under which objects appear to have the colors they do, and the variety of classes of observers for whom the colors appear.
Finally, the interest of the authors of this paper to a special class of observers, named polytopic observers is motivated.
A new class of observers is thus obtained involving a set of cascaded high-gain state observers and output predictors.
The main idea of the paper is to build a new class of observers for chemostat model using hidden symmetries.
This paper presents theory for stability analysis and design for a class of observer-based feedback control systems.
Theory for stability analysis and design for a class of observer-based feedback control systems is presented.
A new class of observers is presented to estimate the states of dynamic systems, based on the rapidly growing technology of neural networks.
As an application, we show that the reduced-order variant of the class of observers in [Automatica 37 (2001 9231]] preserves global asymptotic stability in a certainty-equivalence implementation.
Then, a new class of observer-based algorithms are designed to solve the finite-time consensus tracking problem without using relative velocity measurements.
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