查看更多>>摘要：This paper aims to solve the decentralized finite-time connective tracking control problem for p-normal form stochastic large-scale systems with output interconnections existing in both the drift and diffusion terms. By means of the stochastic system theory and a prescribed finite-time performance function (PFTPF), a novel design scheme is presented for the decentralized finite-time connective tracking controllers with an arbitrarily prescribed settling time. The connective stability problem of stochastic large-scale systems is investigated for the first time. In addition, a new solution for the decentralized tracking control problem of stochastic large-scale systems is presented via a novel mathematical treatment algorithm. The proposed controllers can ensure that the tracking errors converge to a predetermined region within an arbitrarily prescribed settling time and the controlled system is connectively bounded stable in probability. Three simulation examples are presented to exhibit the performance and the superiority of the new control strategy. (C) 2021 Elsevier Inc. All rights reserved.
查看更多>>摘要：This paper concentrates on a containment control issue for multi-agent systems in non-affine form with a given accuracy. In comparison with the existing studies on multi-agent systems, precision-based containment control idea is first formulated. With the aid of the proposed strategy, the main merit of this note is that the synchronization errors converge to arbitrary given positive number. Simultaneously, the particular Layapunov functions are constructed by feat of two auxiliary functions. By employing the backstepping and adaptive control technique, the key variables and the actual controller are designed. Unlike the traditional stability analysis, a novel method is used to analyse the convergence of containment errors. In the end, some simulation results demonstrate the correctness for the proposed protocol. (C) 2021 Elsevier Inc. All rights reserved.
查看更多>>摘要：Public goods game has been widely studied on the formation mechanism of cooperation in social dilemmas. Extensive experimental and theoretical researches have shown that punishment can significantly facilitate cooperation. In nature and society, the individual continuously adjusts the degree of cooperation and severity of punishment. In this paper, the particle swarm optimization (PSO) is used for describing the learning rule of updating the input of cooperation and punishment cost. Cooperators performing both cooperation and punishment make a trade-off between public goods investment and punishment cost. We examine how the PSO learning rule affects the evolution of cooperation and punishment intensity. Our simulation results show that the intermediate values of weighting coefficient omega increase the input of punishment. More cooperators in the interior of clusters input punishment cost, which decreases the cooperation level. For low or high values of omega, cooperators decrease the input of punishment and only cooperators on the edge of clusters incline to punish defectors, which increases the cooperation level of population. Our research provides new insights on the coexistence of cooperation and punishment. (C) 2021 Elsevier Inc. All rights reserved.
查看更多>>摘要：This work presents a study about a special class of infeasible solutions called here as pseudo-feasible solutions in bilevel optimization. This work is focused on determining how such solutions can affect the performance of an evolutionary algorithm. After its formal definition, and based on theoretical results, two conditions to detect and deal with them are proposed. Moreover, a novel and scalable set of test problems with characterized pseudo-feasible solutions is introduced. Furthermore, an algorithm designed to solve bilevel optimization problems (BOP) is adapted with the above mentioned conditions and tested in already known test problems and also in the new testbed so as to analyze its performance when compared with state-of-the-art evolutionary approaches for BOPs. The obtained results suggest that the presence of pseudo-feasible solutions can be considered as a source of difficulty in this type of optimization problems, since their presence may lead to incorrect comparisons among algorithms. (C) 2021 Elsevier Inc. All rights reserved.
Garimella, Sai ManikiranAnand, MohanRajagopal, Kumbakonam R.
8页
查看更多>>摘要：In this paper we study a start-up shear flow of a recently proposed model of a shear-thinning fluid that mimics the response of a class of viscoplastic materials, namely the flow between parallel plates, one of which is fixed and the other is started impulsively. In simple shear flows while the generalized viscosity blows up, the shear stress is yet finite and thus the fluid is able to mimic the response of viscoplastic fluids. The analytical solution of the velocity profile is obtained using the semi-inverse approach for a perturbation approximation. The partial differential equation for the perturbation approximation is solved numerically, and compared with the analytical solution in order to validate the numerical scheme. The full equations are then solved numerically and the effect of the various material moduli are assessed by introducing appropriate dimensionless variables. (C) 2021 Elsevier Inc. All rights reserved.
查看更多>>摘要：Fermi-Dirac integrals appear in problems in nuclear astrophysics, solid state physics or in the fundamental theory of semiconductor modeling, among others areas of application. In this paper, we give new and complete asymptotic expansions for the relativistic Fermi-Dirac integral. These expansions could be useful to obtain a correct qualitative understanding of Fermi systems. The performance of the expansions is illustrated with numerical examples. (C) 2021 Published by Elsevier Inc.
查看更多>>摘要：This paper concerns iterated collocation methods for linear and nonlinear Volterra integral equations (VIEs) of the third kind with noncompact operators. The optimal global and local super-convergence orders are determined under a new mesh. Finally, some numerical examples are provided to verify the convergence results. (C) 2021 Published by Elsevier Inc.
查看更多>>摘要：To improve the performance of the low-order linear triangular element for solving transient wave propagation problems, this paper presents a novel enriched finite element method (EFEM) for wave analysis. The original linear nodal shape functions are enriched by using the additional interpolation cover functions over patches of elements. To effectively solve the wave problems, the used interpolation cover function is constructed by using the Lagrangian functions plus the harmonic trigonometric functions. The present approach can be regarded as a combination of the classical finite elements and the spectral techniques, but individual strengths of the two methods are synergized, so more accurate results can be obtained compared to the standard finite elements. In this work the root of the linear dependence (LD) issue in the present EFEM is investigated detailedly, and then an effective approach is proposed to completely eliminate the LD problem. By performing the dispersion analysis, it is found that the present EFEM possesses the attractive monotonic convergence property for transient wave propagations, that is the obtained numerical solutions will monotonically converge to the exact solutions with the decreasing time steps for time integration as long as the reasonably fine meshes are used. Several typical numerical examples are solved to illustrate the capacities of the present method. (C) 2021 Elsevier Inc. All rights reserved.
查看更多>>摘要：This paper aims to solve the decentralized finite-time connective tracking control problem for p-normal form stochastic large-scale systems with output interconnections existing in both the drift and diffusion terms. By means of the stochastic system theory and a prescribed finite-time performance function (PFTPF), a novel design scheme is presented for the decentralized finite-time connective tracking controllers with an arbitrarily prescribed settling time. The connective stability problem of stochastic large-scale systems is investigated for the first time. In addition, a new solution for the decentralized tracking control problem of stochastic large-scale systems is presented via a novel mathematical treatment algorithm. The proposed controllers can ensure that the tracking errors converge to a predetermined region within an arbitrarily prescribed settling time and the controlled system is connectively bounded stable in probability. Three simulation examples are presented to exhibit the performance and the superiority of the new control strategy. (c) 2021 Elsevier Inc. All rights reserved.
查看更多>>摘要：This paper mainly considers the consensus of general first-order continuous-time agents involving delays in both the input and communication network. Suppose that the agent dynamics is unstable and the directed topology contains a spanning tree, control gain depending on the delays bound is employed to design protocol, and some conditions are established to assure consensus. It is shown that the delays in this paper are admitted to be unknown, and the consensus can be realized if the sum of delays is not bigger than the provided bound. Furthermore, delays in this study could be time-varying in some circumstances and consensus of the vector case with a single unstable pole is also researched. Finally, the validity of the proposed results are certified via a numerical example. (C) 2021 Elsevier Inc. All rights reserved.
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