Disturbance observer enhanced neural network LPV control for a blended-wing-body large aircraft

Simple item page
dc.contributor.authorLiu, Shiqian
dc.contributor.authorWhidborne, James F.
dc.contributor.authorChumalee, Sunan
dc.date.accessioned2021-03-31T14:17:19Z
dc.date.available2021-03-31T14:17:19Z
dc.date.issued2021-03-24
dc.description.abstractThe problem of trajectory tracking control for a Blended-Wing-Body (BWB) large aircraft with model parameter uncertainties and unknown disturbances is considered. A Linear Parameter-Varying (LPV) model is derived from the nonlinear dynamics of the BWB aircraft from which a robust linear parameter-varying controller is designed to track a desired trajectory. Using a Single Quadratic Lyapunov Function (SQLF) and an infinite number of linear matrix inequalities to be evaluated at all vertices, a pair of positive definite symmetric matrix solutions is determined via Lyapunov stability theory and linear matrix inequality technique. Furthermore, a disturbance-observer is designed to process the unknown disturbances. Considering the plant exists some model errors except for disturbances, a Radial Basis Function Neural Network (RBFNN) approximation is embedded into the SQLF LPV controller to improve tracking performances, and a composite disturbance-observer based Neural Network Single Quadratic Lyapunov Function (NNSQLF) controller can realize desired trajectory tracking of the linear parameter-varying system through regulating performance weighting functions. The closed-loop system of trajectory tracking control is proved to be asymptotically stable by using Lyapunov theory. Simulation results of forward flight speed and altitude tracking control of the BWB aircraft show that the proposed disturbance-observer based NNSQLF control can robustly stabilize the LPV system and precisely track the desired trajectory by comparing with conventional SQLF control and Parameter-Dependent Lyapunov Functions (PDLF) control, even in unknown exterior disturbances and model uncertainties.en_UK
dc.identifier.citationLiu S, Whidborne JF, Chumalee S. (2021) Disturbance observer enhanced neural network LPV control for a blended-wing-body large aircraft. IEEE Transactions on Aerospace and Electronic Systems, Volume 57, Number 5, October 2021, pp. 2689-2703en_UK
dc.identifier.issn0018-9251
dc.identifier.urihttps://doi.org/10.1109/TAES.2021.3068429
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/16531
dc.language.isoenen_UK
dc.publisherIEEEen_UK
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectBWB aircraften_UK
dc.subjectlinear parameter-varying systemen_UK
dc.subjectdisturbance observeren_UK
dc.subjecttrajectory trackingen_UK
dc.subjectneural networken_UK
dc.titleDisturbance observer enhanced neural network LPV control for a blended-wing-body large aircraften_UK
dc.typeArticleen_UK

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
enhanced_neural_network_LPV_control-2021.pdf
Size:
3.6 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.63 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Staff publications (SATM)