On the controlled eigenvalue problem for stochastically perturbed multi-channel systems

In this brief paper, we consider the problem of minimizing the asymptotic exit rate of diffusion processes from an open connected bounded set pertaining to a multi-channel system with small random perturbations. Specifically, we establish a connection between: (i) the existence of an invariant set for the unperturbed multi-channel system w.r.t. certain class of state-feedback controllers; and (ii) the asymptotic behavior of the principal eigenvalues and the solutions of the Hamilton-Jacobi-Bellman (HJB) equations corresponding to a family of singularly perturbed elliptic operators. Finally, we provide a sufficient condition for the existence of a Pareto equilibrium (i.e., a set of optimal exit rates w.r.t. each of input channels) for the HJB equations -- where the latter correspond to a family of nonlinear controlled eigenvalue problems.Comment: A short paper with 9 pages (a continuation of our previous paper arXiv:1408.6260

A brief remark on the topological entropy for linear switched systems

In this brief note, we investigate the topological entropy for linear switched systems. Specifically, we use the Levi-Malcev decomposition of Lie-algebra to establish a connection between the basic properties of the topological entropy and the stability of switched linear systems. For such systems, we show that the topological entropy for the evolution operator corresponding to a semi-simple subalgebra is always bounded from above by the negative of the largest real part of the eigenvalue that corresponds to the evolution operator of a maximal solvable ideal part.Comment: 8 Page

Large deviation principle for dynamical systems coupled with diffusion-transmutation processes

In this paper, we introduce a mathematical apparatus that is relevant for understanding a dynamical system with small random perturbations and coupled with the so-called transmutation process -- where the latter jumps from one mode to another, and thus modifying the dynamics of the system. In particular, we study the exit problem, i.e., an asymptotic estimate for the exit probabilities with which the corresponding processes exit from a given bounded open domain, and then formally prove a large deviation principle for the exit position joint with the type occupation times as the random perturbation vanishes. Moreover, under certain conditions, the exit place and the type of distribution at the exit time are determined and, as a consequence of this, such information also give the limit of the Dirichlet problems for the associated partial differential equation systems with a vanishing small parameter.Comment: 16 page

On a connection between the reliability of multi-channel systems and the notion of controlled-invariance entropy

The purpose of this note is to establish a connection between the problem of reliability (when there is an intermittent control-input channel failure that may occur between actuators, controllers and/or sensors in the system) and the notion of controlled-invariance entropy of a multi-channel system (with respect to a subset of control-input channels and/or a class of control functions). We remark that such a connection could be used for assessing the reliability (or the vulnerability) of the system, when some of these control-input channels are compromised with an external "malicious" agent that may try to prevent the system from achieving more of its goal (such as from attaining invariance of a given compact state and/or output subspace).Comment: 11 pages a brief pape

On the stochastic decision problems with backward stochastic viability property

In this paper, we consider a stochastic decision problem for a system governed by a stochastic differential equation, in which an optimal decision is made in such a way to minimize a vector-valued accumulated cost over a finite-time horizon that is associated with the solution of a certain multi-dimensional backward stochastic differential equation (BSDE). Here, we also assume that the solution for such a multi-dimensional BSDE {\it almost surely} satisfies a backward stochastic viability property w.r.t. a given closed convex set. Moreover, under suitable conditions, we establish the existence of an optimal solution, in the sense of viscosity solutions, to the associated system of semilinear parabolic PDEs. Finally, we briefly comment on the implication of our results.Comment: 20 pages (Additional Note: This work is, in some sense, a continuation of our previous papers arXiv:1610.07201, arXiv:1603.03359 and arXiv:1611.03405

Optimal residence time control for stochastically perturbed prescription opioid epidemic models

In this paper, we consider an optimal control problem for a prescription opioid epidemic model that describes the interaction between the regular prescription or addictive use of opioid drugs, and the process of rehabilitation and that of relapsing into opioid drug use. In particular, our interest is in the situation, where the control appearing linearly in the opioid epidemics is interpreted as the rate at which the susceptible individuals are effectively removed from the population due to an opioid-related intervention policy or when the dynamics of the addicted is strategically influenced due to an accessible addiction treatment facility, while a small perturbing noise enters through the dynamics of the susceptible group in the population compartmental model. To this end, we introduce a mathematical apparatus that minimizes the asymptotic exit-rate with which the solution for such stochastically perturbed prescription opioid epidemics exits from a given bounded open domain. Moreover, under certain assumptions, we also provide an admissible optimal Markov control for the corresponding optimal control problem that optimally effected removal of the susceptible or recovered individuals from the population dynamics.Comment: 11 pages - Version 2.0 - December, 2018 (Additional Note: This work is, in some sense, a continuation of our previous papers arXiv:1805.12534 and arXiv:1806.09502

Optimal control of diffusion processes pertaining to an opioid epidemic dynamical model with random perturbations

In this paper, we consider the problem of controlling a diffusion process pertaining to an opioid epidemic dynamical model with random perturbation so as to prevent it from leaving a given bounded open domain. Here, we assume that the random perturbation enters only through the dynamics of the susceptible group in the compartmental model of the opioid epidemic dynamics and, as a result of this, the corresponding diffusion is degenerate, for which we further assume that the associated diffusion operator is hypoelliptic. In particular, we minimize the asymptotic exit rate of such a controlled-diffusion process from the given bounded open domain and we derive the Hamilton-Jacobi-Bellman equation for the corresponding optimal control problem, which is closely related to a nonlinear eigenvalue problem. Finally, we also prove a verification theorem that provides a sufficient condition for optimal control.Comment: 13 pages - Version 1.0 - June 25, 2018 (Additional Note: This work is, in some sense, a continuation of our previous paper arXiv:1805.12534

On noncooperative nn-player principal eigenvalue games

We consider a noncooperative $n$-player principal eigenvalue game which is associated with an infinitesimal generator of a stochastically perturbed multi-channel dynamical system -- where, in the course of such a game, each player attempts to minimize the asymptotic rate with which the controlled state trajectory of the system exits from a given bounded open domain. In particular, we show the existence of a Nash-equilibrium point (i.e., an $n$-tuple of equilibrium linear feedback operators) that is distinctly related to a unique maximum closed invariant set of the corresponding deterministic multi-channel dynamical system, when the latter is composed with this $n$-tuple of equilibrium linear feedback operators.Comment: 4 Page

On the asymptotic of exit problems for controlled Markov diffusion processes with random jumps and vanishing diffusion terms

In this paper, we study the asymptotic of exit problem for controlled Markov diffusion processes with random jumps and vanishing diffusion terms, where the random jumps are introduced in order to modify the evolution of the controlled diffusions by switching from one mode of dynamics to another. That is, depending on the state-position and state-transition information, the dynamics of the controlled diffusions randomly switches between the different drift and diffusion terms. Here, we specifically investigate the asymptotic exit problem concerning such controlled Markov diffusion processes in two steps: (i) First, for each controlled diffusion model, we look for an admissible Markov control process that minimizes the principal eigenvalue for the corresponding infinitesimal generator with zero Dirichlet boundary conditions -- where such an admissible control process also forces the controlled diffusion process to remain in a given bounded open domain for a longer duration. (ii) Then, using large deviations theory, we determine the exit place and the type of distribution at the exit time for the controlled Markov diffusion processes coupled with random jumps and vanishing diffusion terms. Moreover, the asymptotic results at the exit time also allow us to determine the limiting behavior of the Dirichlet problem for the corresponding system of elliptic partial differential equations containing a small vanishing parameter.Comment: 16 Pages. (Additional Note: This work is, in some sense, a continuation of our previous papers arXiv:1709.04853

Exit Probabilities for a Chain of Distributed Control Systems with Small Random Perturbations

In this paper, we consider a diffusion process pertaining to a chain of distributed control systems with small random perturbation. The distributed control system is formed by n subsystems that satisfy an appropriate Hormander condition, i.e., the second subsystem assumes the random perturbation entered into the first subsystem, the third subsystem assumes the random perturbation entered into the first subsystem then was transmitted to the second subsystem and so on, such that the random perturbation propagates through the entire distributed control system. Note that the random perturbation enters only in one of the subsystems and, hence, the diffusion process is degenerate, in the sense that the backward operator associated with it is a degenerate parabolic equation. Our interest is to estimate the exit probability with which a diffusion process (corresponding to a particular subsystem) exits from a given bounded open domain during a certain time interval. The method for such an estimate basically relies on the interpretation of the exit probability function as a value function for a family of stochastic control problems that are associated with the underlying chain of distributed control systems.Comment: 18 Page