Performance-based Fault Mitigation in Sampled-Data Process Systems with Sensor Faults and Measurement Delays

摘要

The objective of this work is to provide systematic tools for the analysis and mitigation of sensor faults in sampled-data processes with discretely-sampled and delayed state measurements. The emphasis is on determining the effects of varying process and controller parameters, including faults, sampling period, delay, plant-model mismatch and controller gain, on the stability and performance characteristics of the closed-loop system, and providing insight into how these effects can be counteracted through the use of active fault accommodation measures. The developed insights and methods are applied to a representative chemical process system with sampled and delayed state measurements. The stability of the closed-loop system is first characterized as a function of the sampling rate, the measurement delay, the fault magnitude, the fault accommodation measures, and the plant-model mismatch. The faults assessed have the form of diminished or hyperactive measurements of the system states. As a primary accommodation measure for these faults, the location of the closed-loop poles are adjusted to achieve stability during faulty operation. A performance metric that captures the closed-loop system’s disturbance recovery behavior is chosen and parameterized in the same manner as the stability of the system, and is used to inform the fault accommodation decision-making process further. The explicit characterization of the stability and performance regions offer insight into the operational robustness and ranges of tolerable sensor faults that can be accommodated; and these are discussed with some simulation results for context.