810 research outputs found
Control of singularly perturbed hybrid stochastic systems
In this paper, we study a class of optimal stochastic
control problems involving two different time scales. The fast
mode of the system is represented by deterministic state equations
whereas the slow mode of the system corresponds to a jump disturbance
process. Under a fundamental āergodicityā property for
a class of āinfinitesimal control systemsā associated with the fast
mode, we show that there exists a limit problem which provides
a good approximation to the optimal control of the perturbed
system. Both the finite- and infinite-discounted horizon cases are
considered. We show how an approximate optimal control law
can be constructed from the solution of the limit control problem.
In the particular case where the infinitesimal control systems
possess the so-called turnpike property, i.e., are characterized by
the existence of global attractors, the limit control problem can be
given an interpretation related to a decomposition approach
Control of singularly perturbed hybrid stochastic systems
In this paper we study a class of optimal stochastic control
problems involving two different time scales. The
fast mode of the system is represented by deterministic
state equations whereas the slow mode of the system
corresponds to a jump disturbance process. Under a
fundamental āergodicityā property for a class of āinfinitesimal
control systemsā associated with the fast
mode, we show that there exists a limit problem which
provides a good approximation to the optimal control
of the perturbed system. Both the finite and infinite
discounted horizon cases are considered. We show how
an approximate optimal control law can be constructed
from the solution of the limit control problem. In the
particular case where the infinitesimal control systems
possess the so-called turnpike property, i.e. are characterized
by the existence of global attractors, the limit
control problem can be given an interpretation related
to a decomposition approach
The linear quadratic regulator problem for a class of controlled systems modeled by singularly perturbed Ito differential equations
This paper discusses an infinite-horizon linear quadratic (LQ) optimal control problem involving state- and control-dependent noise in singularly perturbed stochastic systems. First, an asymptotic structure along with a stabilizing solution for the stochastic algebraic Riccati equation (ARE) are newly established. It is shown that the dominant part of this solution can be obtained by solving a parameter-independent system of coupled Riccati-type equations. Moreover, sufficient conditions for the existence of the stabilizing solution to the problem are given. A new sequential numerical algorithm for solving the reduced-order AREs is also described. Based on the asymptotic behavior of the ARE, a class of O(āĪµ) approximate controller that stabilizes the system is obtained. Unlike the existing results in singularly perturbed deterministic systems, it is noteworthy that the resulting controller achieves an O(Īµ) approximation to the optimal cost of the original LQ optimal control problem. As a result, the proposed control methodology can be applied to practical applications even if the value of the small parameter Īµ is not precisely known. Ā© 2012 Society for Industrial and Applied Mathematics.Vasile Dragan, Hiroaki Mukaidani and Peng Sh
An integrated approach to global synchronization and state estimation for nonlinear singularly perturbed complex networks
This paper aims to establish a unified framework to handle both the exponential synchronization and state estimation problems for a class of nonlinear singularly perturbed complex networks (SPCNs). Each node in the SPCN comprises both 'slow' and 'fast' dynamics that reflects the singular perturbation behavior. General sector-like nonlinear function is employed to describe the nonlinearities existing in the network. All nodes in the SPCN have the same structures and properties. By utilizing a novel Lyapunov functional and the Kronecker product, it is shown that the addressed SPCN is synchronized if certain matrix inequalities are feasible. The state estimation problem is then studied for the same complex network, where the purpose is to design a state estimator to estimate the network states through available output measurements such that dynamics (both slow and fast) of the estimation error is guaranteed to be globally asymptotically stable. Again, a matrix inequality approach is developed for the state estimation problem. Two numerical examples are presented to verify the effectiveness and merits of the proposed synchronization scheme and state estimation formulation. It is worth mentioning that our main results are still valid even if the slow subsystems within the network are unstable
Singularly Perturbed Stochastic Hybrid Systems: Stability and Recurrence via Composite Nonsmooth Foster Functions
We introduce new sufficient conditions for verifying stability and recurrence
properties in singularly perturbed stochastic hybrid dynamical systems.
Specifically, we focus on hybrid systems with deterministic continuous-time
dynamics that exhibit multiple time scales and are modeled by constrained
differential inclusions, as well as discrete-time dynamics modeled by
constrained difference inclusions with random inputs. By assuming regularity
and causality of the dynamics and their solutions, respectively, we propose a
suitable class of composite nonsmooth Lagrange-Foster and Lyapunov-Foster
functions that can certify stability and recurrence using simpler functions
related to the slow and fast dynamics of the system. We establish the stability
properties with respect to compact sets, while the recurrence properties are
studied only for open sets
On average control generating families for singularly perturbed optimal control problems with long run average optimality criteria
The paper aims at the development of tools for analysis and construction of
near optimal solutions of singularly perturbed (SP) optimal controls problems
with long run average optimality criteria. The idea that we exploit is to first
asymptotically approximate a given problem of optimal control of the SP system
by a certain averaged optimal control problem, then reformulate this averaged
problem as an infinite-dimensional (ID) linear programming (LP) problem, and
then approximate the latter by semi-infinite LP problems. We show that the
optimal solution of these semi-infinite LP problems and their duals (that can
be found with the help of a modification of an available LP software) allow one
to construct near optimal controls of the SP system. We demonstrate the
construction with a numerical example.Comment: 36 pages, 4 figures. arXiv admin note: substantial text overlap with
arXiv:1309.373
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