Assessing Control Sustainability Using L-Moment Ratio Diagrams

Author:

Domański Paweł D.1ORCID,Jankowski Robert2,Dziuba Krzysztof3ORCID,Góra Radosław3ORCID

Affiliation:

1. Institute of Control and Computation Engineering, Faculty of Electronics and Information Technology, Warsaw University of Technology, Nowowiejska 15/19, 00-665 Warsaw, Poland

2. Honeywell Sp. z o.o., ul. Domaniewska 39, 02-672 Warsaw, Poland

3. Grupa Azoty, Zakłady Azotowe “PUAWY” S.A., al. Tysia̧clecia Państwa Polskiego 13, 24-110 Puławy, Poland

Abstract

This paper presents an application of L-moment statistics and the respective L-moment ratio diagrams (LMRD) to assess control performance, in particular, in terms of control system sustainability. L-moment diagrams are common in extreme events analysis and are considered a very powerful tool in this field at the regional level. Control system assessment is a well-established research area that investigates approaches and methodologies for measuring the quality of control systems. Statistical moments can be used to assess the effectiveness of control systems. The same principle applies to L-moments, with a possible further application to the assessment of control system robustness. The incorporation of the time impact into the analysis allows us to examine the evolution of control systems. In this context, measuring sustainability is only one step away. In this research, L-moments and L-moment ratio diagrams are used to assess the quality of PID-based control systems. In addition, the evolution of their performance over time is depicted visually. Moreover, a robust discordance measure is proposed to measure the robustness, evolution, and sustainability of control systems. The proposed approach is successfully validated using real industrial data obtained from PID basic regulatory control within the hierarchical advanced process control (APC) structure of a large ammonia production plant.

Funder

Polish National Centre for Research and Development

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

Reference34 articles.

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4. Mixed statistical and data mining analysis of river flow and catchment properties at regional scale;Piniewski;Stoch. Environ. Res. Risk Assess.,2022

5. L-moments of the Birnbaum–Saunders distribution and its extreme value version: Estimation, goodness of fit and application to earthquake data;Lillo;J. Appl. Stat.,2018

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