Abstract

This paper presents a methodology for supervisory event-based control of networked process systems subject to uncertain dynamics and communication constraints. The proposed methodology aims to balance the overall plant stability with the local performance needs of the component subsystems, while simultaneously optimizing the extent of information transfer between the distributed control systems. Initially, a quasi-decentralized networked control structure is developed consisting of a set of local model-based controllers that communicate with each other over a shared network at discrete times. Using Lyapunov techniques, appropriate thresholds on both the local model estimation errors and the local control Lyapunov functions are then derived and used as triggers for communication with a higher-level supervisor. In the event that either threshold is breached, an alarm signal is sent by the local controller to the supervisor which keeps track of all the alarm signals reported by the various units and then decides which subsystems should communicate with one another. The supervisory logic is designed to take the behavior of both the local and composite control Lyapunov functions into account, in order to meet both the stability and local performance requirements. Finally, the proposed methodology is illustrated using a networked chemical process example.

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