Distributed estimation and control for general systems

Networked systems have recently been undergoing a quiet revolution in all aspects of the hardware implementation, software development and theoretical research. Such systems arise as natural models in many areas of engineering and sciences with examples including sensor networks, autonomous unmanned vehicles, biological networks, and animal cooperative aggregation and flocking. In addition to the universal attributes of the complex networks, networked systems do possess their own characteristics due mainly to the large number of simple systems interacting through a communication medium. The past decade has seen successful applications of networked systems in many practical areas ranging from military sensing, physical security, air traffic control, to distributed robotics and industrial and manufacturing automation. Accordingly, theoretical research on large-scale networked systems has gained an increasing attention from multiple disciplines including engineering, computer science and mathematics. Lying in the core part of the area are the distributed estimation and control problems that have recently been attracting growing research interests. For distributed estimation and control problems, the networked system is comprised of a large number of simple systems (i.e. nodes) with computing and wireless communication capabilities, where the nodes are spatially distributed to form an ad hoc network and every node has its own notion of time. Each individual node in the network locally estimates/controls the system state from not only its own measurement but also its neighbouring nodes’ measurements according to the given topology. The possible complexity of such a topology poses many challenges for scientists and engineers, and it is difficult to analyse these networks thoroughly with currently available estimation/control algorithms. Therefore, there is an urgent need to research on modelling, analysis of behaviours, systems theory and estimation/control algorithms in networked systems. Numerous fundamental questions have been addressed about the connections between network topology and dynamic properties including stability, controllability, robustness and other observable aspects. In recent years, the problem of distributed filtering or state estimation has been attracting growing research interests. In particular, the problems of distributed filtering or state estimation over sensor networks have drawn much research attention, see Shen, Wang, and Hung (2010), Dong, Wang, and Gao (2013) and Ding et al. (2012). Sensor networks are composed of small nodes which can sense, compute and communicate with their neighbouring nodes. These nodes, also called as sensor nodes, are usually distributed spatially to form a wireless ad hoc network and are capable of processing a limited amount of data. Comparing with sensing and computation, communication is the most energy-consuming operation in sensor networks. For this purpose, a reasonable requirement for the sensor networks would be the distributed processing capability. Therefore, considerable research attention has been devoted to the theoretical research on the distributed estimation problem over sensor networks. The control problem for distributed control has also received considerable research attention. In a distributed control system, the system consists of numerous subsystems (also called “agents”) which are geographically distributed and provide supplemental feedbacks for the local controllers to achieve the requirements of the system, including the stability and H∞