Fully Probabilistic Design for Stochastic Discrete System with Multiplicative Noise

Abstract

In this paper, a novel algorithm based on fully probabilistic design (FPD) is proposed for a class of linear stochastic dynamic processes with multiplicative noise. Compared with the traditional FPD, the new procedure is presented to deal with multiplicative noise and the system parameters are estimated online using linear optimisation methods. The performance index is characterised by the Kullback-Leibler divergence (KLD) distance. The generalised probabilistic control law is obtained by solving a generalised Riccatti equation that takes the multiplicative noise into consideration. To demonstrate the effectiveness of the proposed method, a numerical example is given and the results are compared with the traditional FPD.

Publication DOI: https://doi.org/10.1109/ICCA.2019.8899607
Divisions: Engineering & Applied Sciences > Mathematics
Engineering & Applied Sciences
Engineering & Applied Sciences > Systems analytics research institute (SARI)
Engineering & Applied Sciences > Computer Science
Additional Information: © 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.
Event Title: The 15th IEEE International Conference on Control and Automation (IEEE ICCA 2019)
Event Type: Other
Event Dates: 2019-07-16
Uncontrolled Keywords: Artificial Intelligence,Computer Science Applications,Control and Systems Engineering,Electrical and Electronic Engineering,Industrial and Manufacturing Engineering
ISBN: 9781728111643
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Conference contribution
Published Date: 2019-07-19
Accepted Date: 2019-02-22
Authors: Zhou, Yuyang ( 0000-0002-2188-2781)
Herzallah, Randa ( 0000-0001-9128-6814)
Zafar, Ana

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