Large-Scale Complex Systems

Abstract

Large-scale complex systems (LSS) have traditionally been characterized by large numbers of variables, structure of interconnected subsystems, and other features that complicate the control models such as nonlinearities, time delays, and uncertainties. The decomposition of LSS into smaller, more manageable subsystems allowed for implementing effective decentralization and coordination mechanisms. The last decade revealed new characteristic features of LSS such as the networked structure, enhanced geographical distribution and increased cooperation of subsystems, evolutionary development, and higher risk sensitivity. This chapter aims to present a balanced review of several traditional well-established methods and new approaches together with typical applications. First the hierarchical systems approach is described and the transition from coordinated control to collaborative schemes is highlighted. Three subclasses of methods that are widely utilized in LSS – decentralized control, simulation-based, and artificial-intelligence-based schemes – are then reviewed. Several basic aspects of decision support systems (DSS) that are meant to enable effective cooperation between man and machine and among the humans in charge with LSS management and control are briefly exposed. The chapter concludes by presenting several technology trends in LSS.