A Combined Scheme of Nonlinear Adaptive Flight Control and Neural Network Fault Detection

2012 ◽  
Author(s):  
Thomas Krüger ◽  
Philipp Schnetter ◽  
Falk Sachs ◽  
Peter Vörsmann
Keyword(s):  
Neural Network ◽  
Fault Detection ◽  
Flight Control ◽  
Adaptive Flight Control ◽  
Network Fault

PNN and BP Neural Network Fault Diagnosis Research on Electronic Accelerator Pedal Detection

2020 ◽  
Vol 14 (2) ◽  
pp. 205-220
Author(s):  
Yuxiu Jiang ◽  
Xiaohuan Zhao
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Fault Detection ◽  
Lower Limit ◽  
Bp Neural Network ◽  
Accelerator Pedal ◽  
Electronic Throttle ◽  
Measured Voltage ◽  
Upper Limit ◽  
Network Fault

Background: The working state of electronic accelerator pedal directly affects the safety of vehicles and drivers. Effective fault detection and judgment for the working state of the accelerator pedal can prevent accidents. Methods: Aiming at different working conditions of electronic accelerator pedal, this paper used PNN and BP diagnosis model to detect the state of electronic accelerator pedal according to the principle and characteristics of PNN and BP neural network. The fault diagnosis test experiment of electronic accelerator pedal was carried out to get the data acquisition. Results: After the patents for electronic accelerator pedals are queried and used, the first measured voltage, the upper limit of first voltage, the first voltage lower limit, the second measured voltage, the upper limit of second voltage and the second voltage lower limit are tested to build up the data samples. Then the PNN and BP fault diagnosis models of electronic accelerator pedal are established. Six fault samples are defined through the design of electronic accelerator pedal fault classifier and the fault diagnosis processes are executed to test. Conclusion: The fault diagnosis results were analyzed and the comparisons between the PNN and the BP research results show that BP neural network is an effective method for fault detection of electronic throttle pedal, which is obviously superior to PNN neural network based on the experiment data.

Research of Nonlinear Adaptive Flight Control Using Inversible System of Neural Networks

2014 ◽  
Vol 490-491 ◽  
pp. 960-963
Author(s):  
Shao Song Wan ◽  
Jian Cao ◽  
Cen Rui Ma ◽  
Cong Yan
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Stability Analysis ◽  
Flight Control ◽  
Feedback Linearization ◽  
Adaptive Neural Networks ◽  
Adaptive Flight Control ◽  
The Status ◽  
Training Structure

This paper discusses training structure and procedure about inversible system of neural network. Feedback linearization and adaptive neural networks provide a powerful controller architecture. Finally, this paper surveys the status of nonlinear, and adaptive flight control, and summarizes the research being conducted in this area. A description of the controller architecture and associated stability analysis is given.

Adaptive Flight Control for Unmanned Aircraft Using a Stable Neural Network Observer

2010 ◽  
Author(s):  
Thomas Krüger ◽  
Michael Mössner ◽  
Joachim Axmann ◽  
Peter Vörsmann ◽  
Andreas Kuhn
Keyword(s):  
Neural Network ◽  
Flight Control ◽  
Unmanned Aircraft ◽  
Adaptive Flight Control ◽  
Neural Network Observer

Neural Network Fault Detection for the Reverse Pilot of Cable Television Networks

1998 ◽  
Vol 31 (20) ◽  
pp. 325-329
Author(s):  
Nicolaos P. Kourounakis ◽  
Stephen W. Neville ◽  
Nikitas J. Dimopoulos
Keyword(s):  
Neural Network ◽  
Fault Detection ◽  
Cable Television ◽  
Network Fault
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