PdE-based model reference adaptive control of uncertain heterogeneous multiagent networks

Robust globally stable model reference adaptive control (MRAC) laws recently derived for systems described by parabolic and hyperbolic partial differential equations (PDEs) with spatially-varying coefficients under distributed sensing and actuation are extended to heterogeneous multiagent networks characterized by parameter uncertainty. The extension is carried out using partial difference equations (PdEs) on graphs that preserve parabolic- and hyperbolic-like cumulative network behavior. Unlike in the PDE case, only boundary input is specified for the reference model. The algorithms proposed directly incorporate this boundary reference input into the reference PdE to generate the distributed admissible reference evolution profile followed by the agents. The agent evolution thus depends only on the interaction with the adjacent agents, making the system fully decentralized. Numerical examples are presented as well, including the case of the switched topology associated with a sudden loss of an agent. The resulting PdE MRAC laws inherit the robust linear structure of their PDE counterparts.     

Nonlinear stable adaptive control based upon Elman networks

Elman networks‘ dynamical modeling capability is discussed in this paper firstly. According to Elman networks‘ unique structure ,a weight training algorithm is designed and a nonlinear adaptive controller is constructed. Without the PE presumption, neural networks controller‘s closed-loop properties are studied and the whole Elman networks‘ passivity is demonstrated.     

A distributed approach to capacity allocation in logical networks

We consider a dynamic capacity reallocation scheme in a logically fully-connected telecommunications network. We show that the problem of optimal capacity allocation can be solved in a distributed manner, an essential feature of such a scheme. Our continuous-capacity reallocation scheme can be used as a foundation for a discrete system. This is useful from the perspective of practical implementation.     

A compound adaptive approach to degenerate nonlinear quenching problems

Quenching phenomena play important roles in both steady and unsteady combustion processes. This article studies a compound finite difference method for solving a nonlinear degenerate combustion model problem. The approach combines procedures of semidiscretization, adaptive ODE solver, and highly stable rational approximation for handling the spatial degeneracy and quenching singularity involved. A second‐order adaptive scheme is constructed, which provides monotone convergence of the numerical solution and direct computations of critical quenching values. It has a simple, yet accurate and reliable, structure and is easy to use. We further demonstrate advantages of the scheme by comparing it to existing algorithms. Numerical examples are presented to further strengthen our results. © 1999 John Wiley & Sons, Inc. Numer Methods Partial Differential Eq 15: 29–47, 1999     

Stabilization of novel multi-layer networks with noise-based nonlinear superior couplings via aperiodically adaptive intermittent pinning control

In this paper, novel multi-layer networks with superior couplings are proposed firstly which are established on a non-strongly connected digraph. Within the multi-layer networks, a nonlinear coupling based on white noises is introduced, which is the feature of superior couplings. We adopt aperiodically adaptive intermittent pinning control to stabilize the multi-layer networks. An concrete analysis framework about selecting the target vertex of the control is revealed. Aperiodically adaptive intermittent control is employed on the vertex systems of the first layer networks, to achieve the stabilization of the first layer networks, where the couplings of drift terms are treated as negative effects on stabilization. With the help of noise stabilization, the stabilization of the other layers networks is realized based on the stability of the first layer networks and the characteristics of the superior coupling that is based on white noises. By employing graph theory and the Lyapunov method, an almost sure exponential stabilization criterion of the multi-layer networks is acquired. As a subsequent result, the proposed theory is applied to a class of stochastic coupled oscillators with sufficient conditions being given to ensure their stability. Finally, a numerical example is provided to illustrate the feasibility of the stated theoretical results.     

Computational study of a nonhierarchical decomposition algorithm

Optimizing the design of complex ground and flight vehicles involves multiple disciplines and multilayered computer codes stitched together from mostly incompativle disciplinary codes. The application of established, large-scale, optimization algorithms to the complete model is nearly impossible. Hierarchical decompositions are inappropriate for these types of problems and do not parallelize well. Sobieszczanski-Sobieski has proposed a nonhierarchical decomposition strategyfor nonlinear constrained optimization that is naturally parallel. Despite some successes on engineering problems, the algorithm as originally proposed fails on simple two-dimensional quadratic programs. This paper demonstrates the failure of the algorithm for quadratic programs and suggests a number of possible modifications.     

Value iteration and optimization of multiclass queueing networks

This paper considers in parallel the scheduling problem for multiclass queueing networks, and optimization of Markov decision processes. It is shown that the value iteration algorithm may perform poorly when the algorithm is not initialized properly. The most typical case where the initial value function is taken to be zero may be a particularly bad choice. In contrast, if the value iteration algorithm is initialized with a stochastic Lyapunov function, then the following hold: (i) a stochastic Lyapunov function exists for each intermediate policy, and hence each policy is regular (a strong stability condition), (ii) intermediate costs converge to the optimal cost, and (iii) any limiting policy is average cost optimal. It is argued that a natural choice for the initial value function is the value function for the associated deterministic control problem based upon a fluid model, or the approximate solution to Poisson’s equation obtained from the LP of Kumar and Meyn. Numerical studies show that either choice may lead to fast convergence to an optimal policy. This revised version was published online in June 2006 with corrections to the Cover Date.     

OPTIMAL INSTAR PARASITIZATION IN A STAGE STRUCTURED HOST-PARASITOID MODEL

A stage structured host-parasitoid model is derived and the equilibria studied. It is shown under what conditions the parasitoid controls an exponentially growing host in the sense that a coexistence equilibrium exists. Furthermore, for host populations whose inherent growth rate is not too large it is proved that in order to minimize the adult host equilibrium level it is necessary that the parasitoids attack only one of the larval stages. It is also proved in this case that the minimum adult host equilibrium level is attained when the parasitoids attack that larval stage which also maximizes the expected number of emerging adult parasitoid per larva at equilibrium. Numerical simulations tentatively indicate that the first conclusion remains in general valid for the model. However, numerical studies also show that it is not true in general that the optimal strategy will maximize the number of emerging adult parasitoid per larva at equilibrium.     

Asymptotic behavior of solutions of functional difference equations

For linear functional difference equations, we obtain some results on the asymptotic behavior of solutions, which correspond to a Perron-type theorem for linear ordinary difference equations. We also apply our results to Volterra difference equations with infinite delay.     

On the reversibility of queueing networks

This paper relates the reversibility of certain discrete state Markovian queueing networks — the class of quasi-reversible networks — to the reversibility of the underlying switching process. Quasi-reversible networks are characterized by a product form equilibrium state distribution.When the state can be represented by customer totals at each node, the reversibility of the state process is equivalent to the reversibility of the switching process. More complicated quasi-reversible networks require additional conditions, to ensure the reversibility of the network state process.     

Nonlinear Boundary Value Problems on Sequence Spaces

In this paper we study the solvability of nonlinear, discrete-time boundary value problems for functional equations. Conditions are established for the existence of solutions to problems of the form $$x(k + 1) = f(k, x(k)) + lambda g(k, x(k)); quad k = 0, 1, 2, ldots$$     

Periodic solutions to a difference equation with maximum

An open problem posed by G. Ladas is to investigate the difference equation

where are any nonnegative real numbers with 0$">. We prove that there exists a positive integer such that every positive solution of this equation is eventually periodic of period .

     

一类非线性差分方程的振动性

用Riccati变换方法，获得了一类非线性差分方程△[αn△（bn△xn=pnxn-r))] qnf(xn-σ)=0的振动性的一些结果，并对已知结果做了一些有意义的改进。     

Elimination of limit cycles in a class of digital filters using single saturation nonlinearity

Using Lyapunov's direct method, a novel frequency-domain criterion for the elimination of limit cycles in a class of digital filters using single saturation nonlinearity is derived. The criterion turns out to be a generalization and improvement over an earlier criterion due to Kar and Singh. An example showing the effectiveness of the criterion is given. A graphical interpretation of a simplified version (involving one free parameter) of the criterion is discussed.     

Newsvendor equations for production networks

We consider production networks with stochastic activity leadtimes. When activities finish early holding costs are incurred and when end products are delivered late penalty costs are incurred. Objective is to find the activity start and finish times that minimize the total cost. We introduce the concept of a tardy path and derive the optimality equations for each node in the network. We show that under the optimal solution, for a set of nodes the tardiness probability satisfies the Newsvendor equations.     

Robust decentralized adaptive synchronization of general complex networks with coupling delayed and uncertainties

The problem of robust decentralized adaptive synchronization of general complex networks with coupling delayed and uncertainties is investigated in this article. It is only assumed that the upper normal bound of uncertain inner and outer coupling matrices is positive but its concrete structure is not also required to be known. The time‐varying coupling delay is a any nonnegative continuous and bounded function and not require its derivative to be less than one, that is, general time‐varying coupling delays and uncertainties. For such a class of uncertain complex networks, a new synchronization scheme is presented by a class of continuous memoryless robust decentralized adaptive synchronization controllers. It is also shown that the synchronization error dynamics of uncertain complex networks can be guaranteed as uniformly exponentially convergent toward a ball that can be as small as desired. Finally, numerical simulations are provided to demonstrate the effectiveness and robustness of proposed complex networks synchronization schemes. © 2013 Wiley Periodicals, Inc. Complexity 19: 10–26, 2014     

Modeling pathways of differentiation in genetic regulatory networks with Boolean networks

We have carried out the first examination of pathways of cell differentiation in model genetic networks in which cell types are assumed to be attractors of the nonlinear dynamics, and differentiation corresponds to a transition of the cell to a new basin of attraction, which may be induced by a signal or noise perturbation. The associated flow along a transient to a new attractor corresponds to a pathway of differentiation. We have measured a variety of features of such model pathways of differentiation, most of which should be observable using gene array techniques. © 2005 Wiley Periodicals, Inc. Complexity 11: 52–60, 2005     

Almost self-optimizing strategies for the adaptive control of diffusion processes

The ergodic control of a multidimensional diffusion process described by a stochastic differential equation that has some unknown parameters appearing in the drift is investigated. The invariant measure of the diffusion process is shown to be a continuous function of the unknown parameters. For the optimal ergodic cost for the known system, an almost optimal adaptive control is constructed for the unknown system.This research was partially supported by NSF Grants ECS-87-18026, ECS-91-02714, and ECS-91-13029.     

Contagion processes on urban bus networks in Indian cities

Bus transportation is the most convenient and cheapest way of public transportation in Indian cities. Due to cost‐effectiveness and wide reachability, buses bring people to their destinations every day. Although the bus transportation has numerous advantages over other ways of public transportation, this mode of transportation also poses a serious threat of spreading contagious diseases throughout the city. It is extremely difficult to predict the extent and spread of such an epidemic. Earlier studies have focused on the contagion processes on scale‐free network topologies; whereas, real‐world networks such as bus networks exhibit a wide‐spectrum of network topology. Therefore, we aim in this study to understand this complex dynamical process of epidemic outbreak and information diffusion on the bus networks for six different Indian cities using SI and SIR models. We identify epidemic thresholds for these networks which help us in controlling outbreaks by developing node‐based immunization techniques. © 2016 Wiley Periodicals, Inc. Complexity 21: 451–458, 2016