Paper Info
Title
A Survey of the Probability Density Function Control for Stochastic Dynamic Systems
Abstract
Probability density function (PDF) control strategy investigates the controller design approaches in order to to realise a desirable distributions shape control of the random variables for the stochastic processes. Different from the existing stochastic optimisation and control methods, the most important problem of PDF control is to establish the evolution of the PDF expressions of the system variables. Once the relationship between the control input and the output PDF is formulated, the control objective can be described as obtaining the control input signals which would adjust the system output PDFs to follow the pre-specified target PDFs. This paper summarises the recent research results of the PDF control while the controller design approaches can be categorised into three groups: 1) system model-based direct evolution PDF control; 2) model-based distribution-transformation PDF control methods and 3) data-based PDF control. In addition, minimum entropy control, PDF-based filter design, fault diagnosis and probabilistic decoupling design are also introduced briefly as extended applications in theory sense.
Year
DOI
Venue
2018
10.23919/IConAC.2018.8749012
2018 24th International Conference on Automation and Computing (ICAC)
Keywords
DocType
ISBN
stochastic dynamic systems,stochastic processes,PDF control,control input signals,minimum entropy control,PDF-based filter design,controller design,stochastic optimisation,probability density function control,distributions shape control
Conference
978-1-5386-4891-9
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Mifeng Ren1167.85
Qichun Zhang2103.84
Jianhua Zhang37114.22