Event-Triggered Control of a Continuum Model of Highly Re-Entrant Manufacturing System

Abstract: With the unceasing growth of intelligent production lines that integrate sensors, actuators, and controllers in a wireless communication environment via internet of things (IoT), we design an event-triggered boundary controller for a continuum model of highly re-entrant manufacturing systems for which the influx rate of products is the controlled quantity. The designed controller can potentially operate in networked control systems subject to limited information sharing resources. A Lyapunov argument is utilized to derive the boundary controller together with a feasible event generator that avoids the occurrence of Zeno behavior for the closed-loop system. The global stability estimate is established using the logarithmic norm of the state due to the system's nonlinearity and positivity of the density. Furthermore, robustness of the proposed controller with respect to the sampling schedule and sampled-data stabilization results are established. Consistent simulation results that support the proposed theoretical statements are provided.