Constantinos I. Siettos

Georgios C. Georgiou

Yannick De Decker

Journal of Applied Mathematics

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Hindawi Publishing CorporationJournal of Applied MathematicsVolume 2013, Article ID 508176, 2 pageshttp://dx.doi.org/10.1155/2013/508176EditorialComplex Systems Modelling, Analysis, and ControlConstantinos I. Siettos,1 Yannick De Decker,2 and Georgios C. Georgiou31 School of Applied Mathematics and Physical Sciences, National Technical University of Athens, 157 80 Athens, Greece2 Center for Nonlinear Phenomena and Complex Systems (CENOLI), Universite´ Libre de Bruxelles, Campus de la Plaine CP231,Brussels, Belgium3Department of Mathematics and Statistics, University of Cyprus, P.O. Box 20537, 1678 Nicosia, CyprusCorrespondence should be addressed to Constantinos I. Siettos; ksiet@mail.ntua.grReceived 24 October 2013; Accepted 24 October 2013Copyright © 2013 Constantinos I. Siettos et al. This is an open access article distributed under the Creative Commons AttributionLicense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properlycited.Complexity pertains to the structure of many real-worldsystems, shaping their behaviour and dynamics. Over the lastfew years, there has been an increasing interest in studyingthe emergent complex dynamics of processes ranging fromfluid mechanics and materials science to the internet andsocial networks and from biological and neural systems toepidemic and ecological systems. Due to the strongly hetero-geneous character of such systems as well as the stochasticand nonlinear very large scale interactions over complexnetworks, the emergent (macroscopic) behavior ismost of thetimes far from trivial to predict. Self-organization, sustainedoscillations, travelling waves, multiplicity of stationary states,and spatiotemporal chaos are paradigms of the rich nonlinearbehavior at the coarse-grained systems level.Hence, the quest for developing new modelling,computational-assisted, and control methodologies to ana-lyze and design the behaviour of complex systems appearsto be a major and timely challenge of our times. Findingand developing such methodologies would enable a betterunderstanding, prediction, and design of complex systemswith important health, social, and economic impact. In thisspecial issue, we invited authors to contribute with originalresearch and review articles with a strong focus on thesetopics includingmaterials science, fluidmechanics, stochasticmodelling of complex problems, multiscale computationalmethods, topology of complex networks and their dynamics,control and optimization methods for multiscale/complexsystems, bifurcation analysis of microscopic and large scalesystems, computational epidemiology, and computationalneuroscience.We received a total of 59 paper. All papers underwenta very careful peer review process and were revised toaccommodate the comments made by the reviewers.We gavea lot of attention to the selection of the appropriate reviewers.We based our choice on strict academic criteria includingthe expertise in the field of each submitted paper and inter-national reputation. In a very small number of manuscriptsfor which we received conflicting pieces of advice we choseto submit the corresponding manuscript to other refereesand finally we made our decision taking into account all thereports and the strength of the arguments therein on the basisof academic merit and subject appropriateness. Finally, 14manuscripts were accepted, that is, the acceptance rate wasslightly less than 24%. The special issue is freely availableonline to all interested readers.In what follows we briefly describe the published contri-butions.M. Liu et al. develop a deadlock prevention systemwith resources reallocation and supervisor reconfigurationfor designing near-optimal supervising controllers for auto-mated flexible manufacturing systems. Their methodology ismainly focused on manufacturing-oriented Petri nets.L. Chai and S. Fei address the problem of stabilizationof a class of linear time-delayed systems for which thedelay parameter appears in both the control and systemmatrices and is unknown. The authors show how one can2 Journal of Applied Mathematicsdesign a feedback controller based on the “error to error” andseparated “descriptor form” functional technique to stabilizethe underlying systems and provide the relevant sufficientconditions which can be obtained by a solvable linear matrixinequality problem.Xian et al. introduce a control system that can be usedto suppress epileptiform spikes from a regular network ofcoupled neural populations. For their illustrations they useda Jansen’s neural massmodel.They show through simulationsthat the type of the controlled populations, the number ofthe controlled populations and the control gain are importantfactors that affect the performance of the control system.C.-Y. Huang et al. describe a (four-layer universal epi-demic dynamics) FLUed platform incorporating complexdaily commuting network data into multiple age-structuredcompartmental models for the simulation and the analysisof the dynamics of epidemics. The proposed model wasvalidated and tested through real-world data concerningthe seasonal influenza A and 2009 swine-origin influenzaA (H1N1). The potential impact of intervention policies aswell as variation in initial outbreak areas for novel/seasonalinfluenza A in Taiwan is also investigated and discussed.Xiangjie Liu et al. design a fuzzy state feedback controlsystem based on the delay partitioning approach in order toexamine the passivity of Tagaki-Sugeno fuzzy systems withtime delay.The resulting sufficient conditions are given in theform of linear matrix inequalities.In the paper of P. Liu et al., a proportional-integral-derivative (PID) controller is designed with a feedforwardcompensation for the trajectory tracking problem of a giantmagnetostrictive actuator (GMA). The effectiveness of theirproposed approach is illustrated through both model-basedsimulations and experiments.T. Chen andY.-C.Wang present a fuzzy slack-diversifyingfluctuation-smoothing rule to enhance the performance ofa multiobjective job dispatching wafer fabrication factory.The performance of the proposed methodology which aimsat optimizing cycle time, cycle time standard deviation, themaximum lateness, and number of tardy jobs is demonstratedthrough a model simulating a real wafer fabrication factorylocated in Taichung Scientific Park of Taiwan having amonthly capacity of about 25,000 wafers.S. Cang et al. introduce an adaptive control systemthat can be employed to achieve projective synchronizationof coupled chaotic systems which are not identical, withfully unknown parameters, uncertain terms, and externalbounded disturbances. The design is based on the Lyapunovstability theory and the effectiveness of the proposed schemeis illustrated through two examples, namely, the Lorenz andLu¨ systems.L. Tan and D. Lei provide analytic solutions for the steadystate distribution of the vertex degree, the vertex strength,and the edge weight for a class of generalized weighted scale-free networks, where the new vertex connects to m pairsof vertices selected preferentially. Numerical simulations arealso provided and compared to the analytical derivations.Y. Yao et al. formulate a delayed Internet worm prop-agation model with birth and death rates. It is shownthrough analysis that when the time delay passes a threshold,corresponding to a Hopf bifurcation, the worm propagationbecomes unstable and gets out of control. The delay shouldthus be kept to values less than the threshold to ensure thestability of the system and a better predictability of the scaleand rate of the worm spreading. Numerical experiments arepresented, which fully support their analysis.T. Wang et al. employ the immersed boundary-fictitiousdomain method to simulate numerically the adhesion anddissociation kinetics of erythrocytes in horizontal micro-channels with stenosis. Their simulations demonstrate theimportance of the geometrical characteristics on the dis-sociation of the erythrocyte aggregates and that the latterdissociate easier when they are horizontally and not verticallyoriented.Y. Zhao et al. investigate the cluster synchronization ofimpulsive complex networks with stochastic perturbationand time-varying delays. The nodes in the complex networksare nonidentical. Using the Lyapunov stability theory andstochastic analysis theory as well as linearmatrix inequalities,sufficient conditions are derived to guarantee the cluster syn-chronization. Numerical simulations are provided to showthe effectiveness of the theoretical results.L.Wang et al. investigate the exponential synchronizationproblem for a class of moving agent networks in a two-dimensional space, which exhibits time-varying topologystructure. Based on the Lyapunov stability theory, adaptivefeedback controllers are developed to guarantee the exponen-tial synchronization between agents. A numerical examplebased on the Ro¨ssler system is provided to demonstratethe effectiveness and applicability of the proposed designapproach.B. Liu et al. studied the adaptive synchronization ofcomplex dynamical networks satisfying local Lipschitz condi-tion with switching topology. Based on differential inclusionand nonsmooth analysis, it is proved that all nodes canconverge to a synchronous state even though only one node isinformed,when introducing decentralized adaptive strategiesto the coupling strengths and feedback gains. Numericalsimulations are performed to illustrate the analytical results.Constantinos I. SiettosYannick De DeckerGeorgios C. 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