Robust and Asymmetric Assessment of the Benefits from Improved Control – Industrial Validation

Abstract Quality of the control system significantly contributes to the overall process technological and financial results. Plant throughput, environmental footprint and energy consumption push plants towards their technological limitations requiring better operation closer to constraints. Any improvement initiative should be predated with the estimation of the potential benefits associated with the rehabilitation project. The same applies to the control improvements. The assessment is always based on the performance indicators. Classical the same limit method is based on the Gaussian approach. However, investigation of industrial data frequently is not compliant with normal assumption about the properties of the variables. This paper extends the Gaussian approach with the use of robust (Huber) statistics and asymmetric Pearson type IV probability density function.