The Library
A neural network approach to predicting airspeed in helicopters
Tools
UNSPECIFIED (2000) A neural network approach to predicting airspeed in helicopters. NEURAL COMPUTING & APPLICATIONS, 9 (2). pp. 73-82. ISSN 0941-0643.
Research output not available from this repository.
Request-a-Copy directly from author or use local Library Get it For Me service.
Abstract
A helicopter's airspeed and sideslip angle is difficult to measure at speeds below 50 knots. This paper describes the application of Artificial Neural Network (ANN) techniques to the helicopter low air-speed problem. Three ANN methods were applied to the problem: a linear network, a Radial Basis Function (RBF) network, and a Multi-Layer Perceptron (MLP), trained using an implementation of the Levenberg-Marquardt (L-M) algorithm. Internally available measurements, such as control positions and body attitudes and rates, were generated using a realistic simulation model of a Lynx helicopter. These measurements formed the inputs to the ANN methods. The MLP was found to be the superior method. Further testing, including a Taguchi analysis, indicated the validity of the method. It is concluded that ANN techniques present a promising solution to the helicopter low airspeed problem.
Item Type: | Journal Article | ||||
---|---|---|---|---|---|
Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software | ||||
Journal or Publication Title: | NEURAL COMPUTING & APPLICATIONS | ||||
Publisher: | SPRINGER-VERLAG | ||||
ISSN: | 0941-0643 | ||||
Official Date: | 2000 | ||||
Dates: |
|
||||
Volume: | 9 | ||||
Number: | 2 | ||||
Number of Pages: | 10 | ||||
Page Range: | pp. 73-82 | ||||
Publication Status: | Published |
Data sourced from Thomson Reuters' Web of Knowledge
Request changes or add full text files to a record
Repository staff actions (login required)
View Item |