Introduction to modeling and control of complex systems -- Control of complex systems using neural networks -- Modeling and control problems in building structures and bridges -- Model-free adaptive dynamic programming algorithms for H-infinity control of complex linear systems -- Optimization and distributed comntrol for fair data gathering in wireless sensor networks -- Optimization problems in the deployment of sensor networks -- Congestion control in computer networks -- Persistent autonomous formations and cohesive motion control -- Modeling and control of unmanned aerial vehicles : current status and future directions -- A framework for large-scale multi-robot teams -- Modeling and control in cancer genomics -- Modeling and estimation problems in the visuomotor pathway -- Modeling, simulation, and control of transportation systems -- Backstepping controllers for stabilization of turbulent flow PDEs -- An approach to home automation by means of MAS theory -- Multi-robot social group-based search algorithms
Summary
Comprehension of complex systems comes from an understanding of not only the behavior of constituent elements but how they act together to form the behavior of the whole. However, given the multidisciplinary nature of complex systems, the scattering of information across different areas creates a chaotic situation for those trying to understand possible solutions and applications. Modeling and Control of Complex Systems brings together a number of research experts to present some of their latest approaches and future research directions in a language accessible to system theorists. Con
