Data-driven distribution tracking for stochastic non-linear systems via PID design

Zhang, Qichun and Yue, Hong; (2019) Data-driven distribution tracking for stochastic non-linear systems via PID design. In: 2019 25th International Conference on Automation and Computing (ICAC). IEEE, GBR, pp. 16-21. ISBN 9781861376664 (https://doi.org/10.23919/IConAC.2019.8895165)

[thumbnail of Zhang-Yue-ICAC2019-Data-driven-distribution-tracking-for-stochastic-non-linear-systems]
Preview
 Text. Filename: Zhang_Yue_ICAC2019_Data_driven_distribution_tracking_for_stochastic_non_linear_systems.pdf
Accepted Author Manuscript
Download (874kB)| Preview

Abstract

This paper investigates the stochastic distribution tracking problem while the probability density function (PDF) of the stochastic non-linear system output can be controlled to desired distribution. To achieve the control objective, a data-driven approach is proposed in which no information of the system model is required. The output PDF can be estimated by kernel density estimation (KDE) based on the collected system output data. Using the estimated PDF, the probability states can be obtained by sampling operation which can be used to re-characterise the PDF of the system output. Thus, the tracking performance can be achieved by PID control. The parametric selection of the controller has been analysed following the identified PDF dynamic model to assure the convergence of the system output. The effectiveness of the presented algorithm is illustrated by a numerical example.

  • Item type:Book Section
    ID code:68993
    Dates:
    Date
    Event
    11 November 2019
    Published
    21 June 2019
    Accepted
    April 2019
    Submitted
    Notes:© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subjects:Technology > Electrical engineering. Electronics Nuclear engineering
    Department:Faculty of Engineering > Electronic and Electrical Engineering
    Depositing user: Pure Administrator
    Date deposited:24 Jul 2019 10:42
    Last modified:24 Apr 2024 00:07
    URI:https://strathprints.strath.ac.uk/id/eprint/68993
CORE (COnnecting REpositories)