A novel recursive singularity free FTSM (Fast Terminal Sliding Mode) strategy for finite time tracking control of nonholonomic systems is proposed. As a result, the singularity problem around the origin resulting from...
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Cooperative behaviors are ubiquitous in nature and human *** is very important to understand the internal mechanism of emergence and maintenance of *** we know now,the offsprings inherit not only the phenotype but als...
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Cooperative behaviors are ubiquitous in nature and human *** is very important to understand the internal mechanism of emergence and maintenance of *** we know now,the offsprings inherit not only the phenotype but also the neighborhood relationship of their *** recent research results show that the interactions among individuals facilitate survival of cooperation through network reciprocity of clustering *** paper aims at introducing an inheritance mechanism of neighborhood relationship to explore the evolution of *** detail,a mathematical model is proposed to characterize the evolutionary process with the above inheritance *** analysis and numerical simulations indicate that high-level cooperation can emerge and be maintained for a wide variety of cost-to-benefit ratios,even if mutation happens during the evolving process.
This paper investigates the nonlinear dynamics of network-based dynamical systems where network communication channels of finite data rates are inserted into the closed loops of the controlsystems. The authors analyz...
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This paper investigates the nonlinear dynamics of network-based dynamical systems where network communication channels of finite data rates are inserted into the closed loops of the controlsystems. The authors analyze the bifurcation and chaotic behavior of the non-smooth dynamical systems. The authors first prove that for almost all system parameters there are no periodic orbits. This result distinguishes this type of non-smooth dynamical systems from many others exhibiting border-collision bifurcations. Next, the authors show analytically that the chaotic sets are separated from the region containing the line segment of all fixed points with a finite distance. Finally, the authors employ a simple model to highlight that both the number of clients sharing a common network channel and fluctuations in the available network bandwidth have significant influence on the performance of such dynamical systems.
Social sampling is a novel randomized message passing protocol inspired by social communication for opinion formation in social networks. In a typical social sampling algorithm, each agent holds a sample from the empi...
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Social sampling is a novel randomized message passing protocol inspired by social communication for opinion formation in social networks. In a typical social sampling algorithm, each agent holds a sample from the empirical distribution of social opinions at initial time, and it collaborates with other agents in a distributed manner to estimate the initial empirical distribution by randomly sampling a message from current distribution estimate. In this paper, we focus on analyzing the theoretical properties of the distributed social sampling algorithm over random networks. First, we provide a framework based on stochastic approximation to study the asymptotic properties of the algorithm. Then, under mild conditions, we prove that the estimates of all agents converge to a common random distribution, which is composed of the initial empirical distribution and the accumulation of quantized error. Besides, by tuning algorithm parameters, we prove the strong consistency, namely, the distribution estimates of agents almost surely converge to the initial empirical distribution. Furthermore, the asymptotic normality of estimation error generated by distributed social sample algorithm is addressed. Finally, we provide a numerical simulation to validate the theoretical results of this paper.
In this paper, we propose a genetic algorithm based design procedure for a radial-basis function neural network. A hierarchical rank density genetic algorithm (HRDGA) is used to evolve both the neural network's to...
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We investigate the fault tolerant control problem and propose an intelligent online sliding mode control strategy using artificial neural networks to handle the desired trajectories tracking problem for systems suffer...
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A complete Fault Tolerant control solution calls for a nonlinear adaptive controller with universal approximation capability and guaranteed stability. To fulfill this requirement we propose the use of Neural Networks ...
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An automatic facial feature extraction method is presented in this paper. The method is based on the edge density distribution of the image. In the preprocessing stage a face is approximated to an ellipse, and a genet...
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Gaussian belief propagation algorithm(GaBP) is one of the most important distributed algorithms in signal processing and statistical learning involving Markov networks. It is well known that the algorithm correctly co...
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Gaussian belief propagation algorithm(GaBP) is one of the most important distributed algorithms in signal processing and statistical learning involving Markov networks. It is well known that the algorithm correctly computes marginal density functions from a high dimensional joint density function over a Markov network in a finite number of iterations when the underlying Gaussian graph is acyclic. It is also known more recently that the algorithm produces correct marginal means asymptotically for cyclic Gaussian graphs under the condition of walk summability(or generalised diagonal dominance). This paper extends this convergence result further by showing that the convergence is exponential under the generalised diagonal dominance condition,and provides a simple bound for the convergence rate. Our results are derived by combining the known walk summability approach for asymptotic convergence analysis with the controlsystems approach for stability analysis.
Precision management of agricultural systems, aiming at optimizing profitability, productivity and sustainability, comprises a set of technologies including sensors, information systems, and informed management, etc. ...
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