1,861 research outputs found
Quantized Feedback Stabilization of Sampled-Data Switched Linear Systems
We propose a stability analysis method for sampled-data switched linear
systems with quantization. The available information to the controller is
limited: the quantized state and switching signal at each sampling time.
Switching between sampling times can produce the mismatch of the modes between
the plant and the controller. Moreover, the coarseness of quantization makes
the trajectory wander around, not approach, the origin. Hence the trajectory
may leave the desired neighborhood if the mismatch leads to instability of the
closed-loop system. For the stability of the switched systems, we develop a
sufficient condition characterized by the total mismatch time. The relationship
between the mismatch time and the dwell time of the switching signal is also
discussed.Comment: 17 pages, 3 figure
Robust Stabilization of Nonlinear Systems by Quantized and Ternary Control
Results on the problem of stabilizing a nonlinear continuous-time system by a
finite number of control or measurement values are presented. The basic tool is
a discontinuous version of the so-called semi-global backstepping lemma. We
derive robust practical stabilizability results by quantized and ternary
controllers and apply them to some significant control problems.Comment: 14 pages, 4 figure
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H∞ fault estimation with randomly occurring uncertainties, quantization effects and successive packet dropouts: The finite-horizon case
In this paper, the finite-horizon H∞ fault estimation problem is investigated for a class of uncertain nonlinear time-varying systems subject to multiple stochastic delays. The randomly occurring uncertainties (ROUs) enter into the system due to the random fluctuations of network conditions. The measured output is quantized by a logarithmic quantizer before being transmitted to the fault estimator. Also, successive packet dropouts (SPDs) happen when the quantized signals are transmitted through an unreliable network medium. Three mutually independent sets of Bernoulli-distributed white sequences are introduced to govern the multiple stochastic delays, ROUs and SPDs. By employing the stochastic analysis approach, some sufficient conditions are established for the desired finite-horizon fault estimator to achieve the specified H∞ performance. The time-varying parameters of the fault estimator are obtained by solving a set of recursive linear matrix inequalities. Finally, an illustrative numerical example is provided to show the effectiveness of the proposed fault estimation approach
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