3,345 research outputs found
Stability Analysis of Continuous-Time Switched Systems with a Random Switching Signal
This paper is concerned with the stability analysis of continuous-time
switched systems with a random switching signal. The switching signal manifests
its characteristics with that the dwell time in each subsystem consists of a
fixed part and a random part. The stochastic stability of such switched systems
is studied using a Lyapunov approach. A necessary and sufficient condition is
established in terms of linear matrix inequalities. The effect of the random
switching signal on system stability is illustrated by a numerical example and
the results coincide with our intuition.Comment: 6 pages, 6 figures, accepted by IEEE-TA
Robust normalization and guaranteed cost control for a class of uncertain singular Markovian jump systems via hybrid impulsive control
This paper investigates the problem of robust normalization and guaranteed cost control for a class of uncertain singular Markovian jump systems. The uncertainties exhibit in both system matrices and transition rate matrix of the Markovian chain. A new impulsive and proportional-derivative control strategy is presented, where the derivative gain is to make the closed-loop system of the singular plant to be a normal one, and the impulsive control part is to make the value of the Lyapunov function does not increase at each time instant of the Markovian switching. A linearization approach via congruence transformations is proposed to solve the controller design problem. The cost function is minimized via solving an optimization problem under the designed control scheme. Finally, three examples (two numerical examples and an RC pulse divider circuit example) are provided to illustrate the effectiveness and applicability of the proposed methods
Quantitative ergodicity for some switched dynamical systems
We provide quantitative bounds for the long time behavior of a class of
Piecewise Deterministic Markov Processes with state space Rd \times E where E
is a finite set. The continuous component evolves according to a smooth vector
field that switches at the jump times of the discrete coordinate. The jump
rates may depend on the whole position of the process. Under regularity
assumptions on the jump rates and stability conditions for the vector fields we
provide explicit exponential upper bounds for the convergence to equilibrium in
terms of Wasserstein distances. As an example, we obtain convergence results
for a stochastic version of the Morris-Lecar model of neurobiology
Controlled diffusion processes
This article gives an overview of the developments in controlled diffusion
processes, emphasizing key results regarding existence of optimal controls and
their characterization via dynamic programming for a variety of cost criteria
and structural assumptions. Stochastic maximum principle and control under
partial observations (equivalently, control of nonlinear filters) are also
discussed. Several other related topics are briefly sketched.Comment: Published at http://dx.doi.org/10.1214/154957805100000131 in the
Probability Surveys (http://www.i-journals.org/ps/) by the Institute of
Mathematical Statistics (http://www.imstat.org
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