1,347 research outputs found
Passivity Degradation In Discrete Control Implementations: An Approximate Bisimulation Approach
In this paper, we present some preliminary results for compositional analysis
of heterogeneous systems containing both discrete state models and continuous
systems using consistent notions of dissipativity and passivity. We study the
following problem: given a physical plant model and a continuous feedback
controller designed using traditional control techniques, how is the
closed-loop passivity affected when the continuous controller is replaced by a
discrete (i.e., symbolic) implementation within this framework? Specifically,
we give quantitative results on performance degradation when the discrete
control implementation is approximately bisimilar to the continuous controller,
and based on them, we provide conditions that guarantee the boundedness
property of the closed-loop system.Comment: This is an extended version of our IEEE CDC 2015 paper to appear in
Japa
Event-Enhanced Quantum Theory And Piecewise Deterministic Dynamics
The standard formalism of quantum theory is enhanced and definite meaning is
given to the concepts of experiment, measurement and event. Within this
approach one obtains a uniquely defined piecewise deterministic algorithm
generating quantum jumps, classical events and histories of single quantum
objects. The wave-function Monte Carlo method of Quantum Optics is generalized
and promoted to the level of a fundamental process generating all the real
events in Nature. The already worked out applications include SQUID-tank model
and generalized cloud chamber model with GRW spontaneous localization as a
particular case. Differences between the present approach and quantum
measurement theories based on environment induced master equations are
stressed. Questions: what is classical, what is time, and what are observers
are addressed. Possible applications of the new approach are suggested, among
them connection between the stochastic commutative geometry and
Connes'noncommutative formulation of the Standard Model, as well as potential
applications to the theory and practice of quantum computers.Comment: 10 pages, twocolumn, REVTE
Dissipative Stabilization of Linear Systems with Time-Varying General Distributed Delays (Complete Version)
New methods are developed for the stabilization of a linear system with
general time-varying distributed delays existing at the system's states, inputs
and outputs. In contrast to most existing literature where the function of
time-varying delay is continuous and bounded, we assume it to be bounded and
measurable. Furthermore, the distributed delay kernels can be any
square-integrable function over a bounded interval, where the kernels are
handled directly by using a decomposition scenario without using
approximations. By constructing a Krasovski\u{i} functional via the application
of a novel integral inequality, sufficient conditions for the existence of a
dissipative state feedback controller are derived in terms of matrix
inequalities without utilizing the existing reciprocally convex combination
lemmas. The proposed synthesis (stability) conditions, which take dissipativity
into account, can be either solved directly by a standard numerical solver of
semidefinite programming if they are convex, or reshaped into linear matrix
inequalities, or solved via a proposed iterative algorithm. To the best of our
knowledge, no existing methods can handle the synthesis problem investigated in
this paper. Finally, numerical examples are presented to demonstrate the
effectiveness of the proposed methodologies.Comment: Accepted by Automatic
Finite-time stochastic input-to-state stability and observer-based controller design for singular nonlinear systems
This paper investigated observer-based controller for a class of singular nonlinear systems with state and exogenous disturbance-dependent noise. A new sufficient condition for finite-time stochastic input-to-state stability (FTSISS) of stochastic nonlinear systems is developed. Based on the sufficient condition, a sufficient condition on impulse-free and FTSISS for corresponding closed-loop error systems is provided. A linear matrix inequality condition, which can calculate the gains of the observer and state-feedback controller, is developed. Finally, two simulation examples are employed to demonstrate the effectiveness of the proposed approaches
Quantized passive filtering for switched delayed neural networks
The issue of quantized passive filtering for switched delayed neural networks with noise interference is studied in this paper. Both arbitrary and semi-Markov switching rules are taken into account. By choosing Lyapunov functionals and applying several inequality techniques, sufficient conditions are proposed to ensure the filter error system to be not only exponentially stable, but also exponentially passive from the noise interference to the output error. The gain matrix for the proposed quantized passive filter is able to be determined through the feasible solution of linear matrix inequalities, which are computationally tractable with the help of some popular convex optimization tools. Finally, two numerical examples are given to illustrate the usefulness of the quantized passive filter design methods
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