Application of Machine Learning to Performance Assessment for a class of PID-based Control Systems
| Autor: | Tomasz Klopot, Bogdan Gabrys, Thanh Tung Khuat, Pawel Nowak, Patryk Grelewicz, Jacek Czeczot |
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| Rok vydání: | 2021 |
| Předmět: |
Human-Computer Interaction
I.2 I.5 Control and Systems Engineering FOS: Electrical engineering electronic engineering information engineering Systems and Control (eess.SY) Electrical and Electronic Engineering Electrical Engineering and Systems Science - Systems and Control Software Computer Science Applications |
| DOI: | 10.48550/arxiv.2101.02939 |
| Popis: | In this paper, a novel machine learning derived control performance assessment (CPA) classification system is proposed. It is dedicated for a wide class of PID-based control industrial loops with processes exhibiting dynamical properties close to second order plus delay time (SOPDT). The proposed concept is very general and easy to configure to distinguish between acceptable and poor closed loop performance. This approach allows for determining the best (but also robust and practically achievable) closed loop performance based on very popular and intuitive closed loop quality factors. Training set can be automatically derived off-line using a number of different, diverse control performance indices (CPIs) used as discriminative features of the assessed control system. The proposed extended set of CPIs is discussed with comprehensive performance assessment of different machine learning based classification methods and practical application of the suggested solution. As a result, a general-purpose CPA system is derived that can be immediately applied in practice without any preliminary or additional learning stage during normal closed loop operation. It is verified by practical application to assess the control system for a laboratory heat exchange and distribution setup. Comment: This work has been submitted to the IEEE Trans. On Systems, Man and Cybernetics: Systems, for possible publication. Comparing to previous version, this one is extended with new comparative results of the proposed method and clear describtion of motivation and novelty of this work |
| Databáze: | OpenAIRE |
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