Add to ORKGThis paper presents an adaptive threshold neural-network scheme for Rotorcraft Unmanned Aerial Vehicle (RUAV) sensor failure diagnosis. The approach based on adaptive threshold has the advantages of better detection and identification ability compared with traditional neural-network-based scheme. In this paper, the proposed scheme is demonstrated using the model of a RUAV and the results show that the adaptive threshold neural-network method is an effective tool for sensor fault detection of a RUAV
Drones have been developed for more than two decades. They have become central to the functions of v...
This project assesses the possibility of a new hybrid method based on Kalman Filter and Adaptive Neu...
With the ever-increasing use of Rotary Unmanned Aerial Vehicles (RUAVs) for various purposes, a fast...
This paper presents an adaptive threshold neural-network scheme for Rotorcraft Unmanned Aerial Vehic...
This paper describes recent research on system design of a small-scaled rotorcraft UAV (RUAV) system...
Nowadays model-based fault detection and isolation (FDI) systems have become a crucial step towards ...
With a growing demand for cost reduction in unmanned air vehicles (UAVs), there has been considerabl...
This paper presents a neural-network-based approach for the problem of sensor failure detection, ide...
fault detection and accommodation using neural networks with application to a non-linear unmanned ai...
Unmanned Aerial Vehicle (UAV) is being used in a wide range of human life. Researcher preferred quad...
The paper describes an original technique for the real-time monitoring of parameters and technical d...
A novel adaptive neural network-based fault-tolerant control scheme is proposed for six degree-of-fr...
The aero-engine system is complex, and the working environment is harsh. As the fundamental componen...
71 p.This dissertation presents an Artificial Neural Network (ANN) based scheme for the modeling, si...
Unmanned Airborne Vehicles (UAV) are assuming prominent roles in both the commercial and military ae...
Drones have been developed for more than two decades. They have become central to the functions of v...
This project assesses the possibility of a new hybrid method based on Kalman Filter and Adaptive Neu...
With the ever-increasing use of Rotary Unmanned Aerial Vehicles (RUAVs) for various purposes, a fast...
This paper presents an adaptive threshold neural-network scheme for Rotorcraft Unmanned Aerial Vehic...
This paper describes recent research on system design of a small-scaled rotorcraft UAV (RUAV) system...
Nowadays model-based fault detection and isolation (FDI) systems have become a crucial step towards ...
With a growing demand for cost reduction in unmanned air vehicles (UAVs), there has been considerabl...
This paper presents a neural-network-based approach for the problem of sensor failure detection, ide...
fault detection and accommodation using neural networks with application to a non-linear unmanned ai...
Unmanned Aerial Vehicle (UAV) is being used in a wide range of human life. Researcher preferred quad...
The paper describes an original technique for the real-time monitoring of parameters and technical d...
A novel adaptive neural network-based fault-tolerant control scheme is proposed for six degree-of-fr...
The aero-engine system is complex, and the working environment is harsh. As the fundamental componen...
71 p.This dissertation presents an Artificial Neural Network (ANN) based scheme for the modeling, si...
Unmanned Airborne Vehicles (UAV) are assuming prominent roles in both the commercial and military ae...
Drones have been developed for more than two decades. They have become central to the functions of v...
This project assesses the possibility of a new hybrid method based on Kalman Filter and Adaptive Neu...
With the ever-increasing use of Rotary Unmanned Aerial Vehicles (RUAVs) for various purposes, a fast...