Online Tuning Diagnosis of Proportional Integral Derivative Controller based on IEC 61499 Function Blocks

Abstract

Controller performance is a crucial aspect of industrial processes; hence, it is critical to maintaining optimal controller performance conditions. Bad controller performance can be caused by poor proportional integral derivative (PID) controller tuning those results in aggressive and sluggish controllers behavior. Correct diagnosis of poor controller tuning becomes vital so that it can adequately handle the controller. This study designs several function blocks for online diagnosis of poor PID controller tuning based on the IEC 61499 standard. The design of the function blocks began with design the method used for diagnosing a poor controller tuning. The procedure was based on autocorrelation function (ACF), comparison of signal to noise ratio (SNR) estimation, and idle index. The function blocks were validated with first order plus delay time (FOPDT) processes, which had aggressive, sluggish, or well-tuned behavior. The function blocks were implemented on a Fluid Catalytic Cracking (FCC) plant and industrial data with various process faults to evaluate its capability to diagnose a poor controller tuning. The developed function block can precisely analyze a poor controller tuning on FCC plant and 8 of 10 industrial data. It showed that the function blocks could diagnose a poor controller tuning correctly if the oscillation were regular.