Robust and Optimal Control of Physical Systems with Networked Communication Structures

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There is no doubt that we are in a networked world right now. Many physical, virtual, or hybrid (mixed physical and virtual) systems operate, communicate, or are controlled through different kinds of network structures, wireless or wired. Examples can be given as: internet systems, electric power grids, automotive systems, various sensor networks, etc. The common nature of these networked systems is that they are exhibited as both dynamical systems and networks, i.e., carrying the features of both dynamical systems and networks which brings in both advantages (such as cost reduction for wiring and maintenance, enhanced flexible functions at both system and network levels, etc.) and challenges (such as increased complexities in the interaction among systems or system components, time-sensitive performance compromise due to networked communication, etc. ). For example, on the advantage side, people have seen tremendous reduction of the wiring costs in every automobile nowadays by adopting the Controller Area Network (CAN) bus for critical applications such as engine control and the Local Interconnected Network (LIN) bus for noncritical applications such as power window/seat control; on the challenge aspect, on the other hand, it has already been realized that the networked communication of data among distributed sensors, controllers, and underlying plant systems tends to downgrade the transient dynamical performance of the controlled systems which, if not carefully addressed, could result in the instability of the whole systems. It has been identified that the challenge posed by the communication network is of great interest to many practical time-sensitive industrial systems such as electric power grids, automotive engine control systems, and sensor network, etc. Although this challenge has been attacked in great number of published literature most recently, many important questions remain open, for example, so far one still does not know how to design a controller that could simultaneously address quantizing and noise effects in the network communication channels and regulate the various desired dynamical behaviors of the controlled target systems. Also, some important questions, such as what the networked communication means to the performance of multi-agent systems, how the networked communication would affect the performance of estimation in distributed control systems, and how the networked communication affect the performance of control systems with both time and event-triggered mechanism, etc., still remain untouched, yet these questions are on top of the ‘most-wanted’ list in various industries. In this Discovery Grant proposal, the focus will be on developing systematic design tools to address the time-sensitive performance in physical control systems with networked communication structure. In particular, it is argued that the information theory and control theory should be integrated to generate conceptually new methods to address the said problems and to design robust and optimal control and management mechanisms for the networked dynamical systems. It is also argued that the methods developed would be industrial needs oriented and hence would find their way to be friendly applied in practice.