Sensor Fault Accommodation Strategies in Multi-rate Sampled-Data Control of Particulate Processes

This paper focuses on the problem of handling sensor faults in controlled particulate processes with multi-rate sampled-data measurements. The problem is addressed on the basis of an approximate finite-dimensional system that captures the dominant dynamics of the infinite-dimensional particulate process system. An observer-based output feedback controller with an inter-sample model predictor is initially designed. The inter-sample model predictor provides the observer with estimates of the unavailable outputs, and its predictions are corrected each time that a measurement becomes available. Owing to the different sampling rates of the measurement sensors, the model update is performed using different outputs, or combinations of outputs, at each update time. The combined discrete-continuous closed-loop system is analyzed, and an explicit characterization of the feasible combinations of output sampling rates, model uncertainty, as well as controller and observer design parameters is obtained. This characterization is used as the basis for the development of both passive and active fault-tolerant control strategies that preserve closed-loop stability in the presence of sensor faults. The results are illustrated using a simulated model of a non-isothermal continuous crystallizer.