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  1. A probabilistic framework to achieve robust non-fragile tuning methods: PD control of IPD-modeled processes
A probabilistic framework to achieve robust non-fragile tuning methods: PD control of IPD-modeled processes
275 viewed

A probabilistic framework to achieve robust non-fragile tuning methods: PD control of IPD-modeled processes

Bahavarnia, M

A probabilistic framework to achieve robust non-fragile tuning methods: PD control of IPD-modeled processes

Bahavarnia, M ; Sharif University of Technology | 2022

275 Viewed
  1. Type of Document: Article
  2. DOI: 10.1002/rnc.5644
  3. Publisher: John Wiley and Sons Ltd , 2022
  4. Abstract:
  5. We introduce a novel probabilistic framework to achieve robust non-fragile tuning methods in control of processes with parametric uncertainties. We consider probability distributions to model the process parameters' uncertainties. First, we propose the tuning framework in a general setting. Then, as an illustration, we apply it to PD control of IPD-modeled processes. It is noteworthy that the proposed tuning method is robust against the considered parametric uncertainties. Also, to empower the proposed robust tuning method in the viewpoint of non-fragility, we utilize a centroid approach. Selecting the form of the probabilistic framework, we empirically observe some of the popular tuning methods are special cases of the proposed novel framework. Moreover, we theoretically/empirically make a comparison among the tuning methods in the literature based on non-fragility and robustness via such a probabilistic framework. © 2021 John Wiley & Sons Ltd
  6. Keywords:
  7. PD controller ; Closed loop systems ; Process control ; Centroid approach ; In-control ; IPD model ; Non-fragile ; Parametric uncertainties ; PD control ; PD controllers ; Probabilistic framework ; Robust ; Tuning method ; Probability distributions
  8. Source: International Journal of Robust and Nonlinear Control ; Volume 32, Issue 18 , 2022 , Pages 9593-9609 ; 10498923 (ISSN)
  9. URL: https://onlinelibrary.wiley.com/doi/abs/10.1002/rnc.5644