Show simple item record

dc.contributor.authorRen, Mifengen
dc.contributor.authorZhang, Qichunen
dc.contributor.authorZhang, Jianhuaen
dc.date.accessioned2018-11-20T16:01:09Z
dc.date.available2018-11-20T16:01:09Z
dc.date.issued2018-09-07
dc.identifier.citationRen, M., Zhang, Q. and Zhang, J. (2018) A Survey of the Probability Density Function Control for Stochastic Dynamic Systems. 24rd International Conference on Automation and Computing (ICAC)en
dc.identifier.urihttp://hdl.handle.net/2086/17235
dc.description.abstractProbability 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) databased 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.en
dc.titleA Survey of the Probability Density Function Control for Stochastic Dynamic Systemsen
dc.typeConferenceen
dc.peerreviewedYesen
dc.funderN/Aen
dc.projectidN/Aen
dc.cclicenceCC-BY-NCen
dc.researchinstituteInstitute of Engineering Sciences (IES)en


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record