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In this paper, the notion of affinelike set-valued maps is introduced and some properties of these maps are presented. Then a new Hahn–Banach extension theorem with a K-convex set-valued map dominated by an affinelike set-valued map is obtained. [Copyright &y& Elsevier]

In this paper, we find the optimal transmission of messages in computer networks. This problem has been formulated as a nondelayed optimal control problem in several recent papers on TCP (transmission control protocol). Since the actual transmission of messages from origins to destinations should consist of both forward transmission delays of the buffers and latency of the links, we remodel the problem as a time-delayed optimal control problem consisting of both control-dependent time-delayed arguments and discrete time-delayed arguments. We then develop a modified control parameterization method for solving this time-delayed optimal control problem. The gradients of the new objective function and constraint functions generated by this modified control parametrization method are derived. A numerical example is solved by using the time-delayed version of the problem that we formulate, as well as the nondelayed version of the problem in the literature. Numerical results clearly illustrate the efficiency of the modified control parameterization method for solving both versions of this optimal transmission problem. Comparison of results of the two versions concerning the optimal transmission rates at the origins, the optimal output flow rates at the destination, and the queue sizes at the buffers are obtained. These comparison results clearly reflect how the optimal transmission of messages in computer networks in real life can be affected by both the forward transmission delays of the buffers and the latency of the links. [ABSTRACT FROM AUTHOR]

This paper presents an angle-based approach for distributed formation shape stabilization of multi-agent systems in the plane. We develop an angle rigidity theory to study whether a planar framework can be determined by angles between segments uniquely up to translations, rotations, scalings and reflections. The proposed angle rigidity theory is applied to the formation stabilization problem, where multiple single-integrator modeled agents cooperatively achieve an angle-constrained formation. During the formation process, the global coordinate system is unknown for each agent and wireless communications between agents are not required. Moreover, by utilizing the advantage of high degrees of freedom, we propose a distributed control law for agents to stabilize a target formation shape with desired orientation and scale. Simulation examples are performed for illustrating the effectiveness of the proposed control strategies. [ABSTRACT FROM AUTHOR]

The purpose of this article is to present an efficient coherent feedback control technique for squeezing enhancement of degenerate parametric amplifiers (DPAs). The feedback controllers to be designed are in the form of linear quantum stochastic systems which can be described by quantum feedback networks theory recently developed. The problem of squeezing enhancement is formulated as a non-convex constrained nonlinear programming problem, whose solution yields the coherent feedback controllers to be designed. Compared with the previous study, the proposed approach reveals clear advantage when DPAs are lossy, as is always the case in practice. Based on the recently developed quantum network synthesis theory, we show how the designed coherent feedback controllers can be implemented by means of quantum optical devices. [ABSTRACT FROM AUTHOR]

Abstract: Small world network models have been effective in capturing the variable behaviour of reported case data of the SARS coronavirus outbreak in Hong Kong during 2003. Simulations of these models have previously been realized using informed “guesses” of the proposed model parameters and tested for consistency with the reported data by surrogate analysis. In this paper we attempt to provide statistically rigorous parameter distributions using Approximate Bayesian Computation sampling methods. We find that such sampling schemes are a useful framework for fitting parameters of stochastic small world network models where simulation of the system is straightforward but expressing a likelihood is cumbersome. [Copyright &y& Elsevier]

The purpose of this paper is to study the mixed linear quadratic Gaussian (LQG) andH∞optimal control problem for linear quantum stochastic systems, where the controller itself is also a quantum system, often referred to as ‘coherent feedback controller’. A lower bound of the LQG control is proved. Then two different methods, rank-constrained linear matrix inequality method and genetic algorithm are for controller design. A passive system (cavity) and a non-passive one (degenerate parametric amplifier) demonstrate the effectiveness of these two proposed algorithms. [ABSTRACT FROM PUBLISHER]