DATA BASED QUANTIFICATION OF SYSTEM NONLINEARITY

The presence of nonlinearities in a process can affect its control performance adversely. Changes in operating conditions due to nonlinearities may render the current controller tuning as ‘non-optimal'. Nonlinearities in valves, e.g., stiction may cause oscillations in process variables. Such oscillations from one control loop can easily propagate to different units of the plant, thus resulting in a plant-wide oscillations. The detection and quantification of process nonlinearity can help decide whether to implement a nonlinear controller or not. It is also useful in diagnosing the root-cause of plant-wide oscillations. A new Total Nonlinearity Index (TNLI) has been developed to quantify process nonlinearity. The previously published Non-Gaussianity Index (NGI) and Nonlinearity Index (NLI) are modified to overcome their limitations. The efficacy of the proposed indices is demonstrated using an illustrative example and an industrial case study.