Output feedback-based event-triggered control of distributed processes with communication constraints

This work presents a methodology for the design and analysis of an output feedback-based event-triggered networked control system for spatially-distributed processes with uncertain low-order dynamics, a finite number of spatially-distributed output measurements and sensor-controller communication constraints. Based on an approximate finite-dimensional system that captures the infinite-dimensional system's dominant dynamics, a model-based controller is initially designed and implemented. A state observer, with well-characterized state estimation error convergence properties, is also designed and embedded in the sensor to estimate the slow states of the infinite-dimensional system based on the available output measurements. The observer state is used to update the model state at times when sensor-controller communication is permitted. The update is triggered whenever a certain stability threshold on the model estimation error is breached. The threshold is explicitly characterized in terms of the controller and observer design parameters, the model uncertainty and the control actuator and measurement sensor locations. The connections between the developed output-feedback-based event-triggered control approach and the full-state feedback-based strategy are identified and discussed. Finally, the proposed methodology is illustrated using a simulation example.