Monitoring and diagnosing process control performance: The single-loop case

This paper presents a hierarchical method for monitoring and diagnosing the performance of single-loop control systems which 1) identifies significant deviations from control objectives, 2) determines the best achievable performance with the current control structure, and 3) identifies steps to improve the current performance. Within the last point, the method can isolate whether poor performance is due to the feedforward loop or the feedback loop. If in the feedback loop, it is sometimes possible to determine whether the cause of poor performance is plant/model mismatch or poor tuning. These results are achieved by analyzing statistical properties, autocorrelations and cross correlations, of a sample of normal process operating data. The theoretical basis of the method is reviewed and results of successful application to industrial case studies are presented.