Networked controller design and analysis for uncertain distributed processes with measurement and actuation error

This work presents a methodology for the design and analysis of networked controllers for a class of spatially distributed process systems with uncertain low-order dynamics, discrete sensor-controller communication, and sensor and actuator errors. Initially, a model-based networked controller that enforces exponential closed-loop stability in the absence of sensor and actuator errors is synthesized using an approximate finite-dimensional model of the infinite-dimensional system. Lyapunov techniques are then used to analyze the implementation of the model-based controller in the presence of bounded measurement and actuation errors. Precise conditions for stability and ultimate boundedness of the closed-loop trajectories are derived and used to obtain an explicit characterization of the interdependence between the achievable ultimate bound on the one hand, and the sensor/actuator error bounds, the sensor data transmission rate, the size of process-model mismatch and the choice of sensor/actuator spatial configurations, on the other. It is shown that by judicious selection of these parameters, closed-loop stability with minimal performance degradation can be attained. Finally, the results are illustrated using a diffusion-reaction process example.