Dong et al., 2013 - Google Patents
Research on inflight parameter identification and icing location detection of the aircraftDong et al., 2013
- Document ID
- 5532245345941350615
- Author
- Dong Y
- Ai J
- Publication year
- Publication venue
- Aerospace Science and Technology
External Links
Snippet
This paper introduces a research on inflight parameter identification and icing location detection of the aircraft. A quasi-state nonlinear iced aircraft model is constructed. A command input of the aircraft control surfaces is designed in both longitudinal and …
- 238000001514 detection method 0 title abstract description 41
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B64—AIRCRAFT; AVIATION; COSMONAUTICS
- B64C—AEROPLANES; HELICOPTERS
- B64C13/00—Control systems or transmitting systems for actuating flying-control surfaces, lift-increasing flaps, air brakes, or spoilers
- B64C13/02—Initiating means
- B64C13/16—Initiating means actuated automatically, e.g. responsive to gust detectors
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Dong et al. | Research on inflight parameter identification and icing location detection of the aircraft | |
| Cao et al. | Aircraft flight characteristics in icing conditions | |
| Bragg et al. | Effect of ice accretion on aircraft flight dynamics | |
| Melody et al. | Parameter identification for inflight detection and characterization of aircraft icing | |
| US9650152B2 (en) | Flight envelope protection system for unmanned aerial vehicles | |
| Ackerman et al. | L1 stability augmentation system for Calspan's variable-stability Learjet | |
| Deiler et al. | Performance-based ice detection methodology | |
| Lombaerts et al. | Design and simulation of fault tolerant flight control based on a physical approach | |
| Lombaerts et al. | On-line safe flight envelope determination for impaired aircraft | |
| Armanini et al. | Decision-making for unmanned aerial vehicle operation in icing conditions | |
| Chang | Examination of excessive fuel consumption for transport jet aircraft based on fuzzy-logic models of flight data | |
| Aykan et al. | Kalman filter and neural network‐based icing identification applied to A340 aircraft dynamics | |
| Dong et al. | Inflight Parameter Identification and Icing Location Detection of the Aircraft: The Time‐Varying Case | |
| Sheu et al. | Estimation of turbulent vertical velocity from nonlinear simulations of aircraft response | |
| Preisighe Viana | Time-domain system identification of rigid-body multipoint loads model | |
| Dutta et al. | Machine-learning based rotor fault diagnosis in a multicopter with strain data | |
| Aykan et al. | Aircraft icing detection, identification and reconfigurable control based on Kalman filtering and neural networks | |
| Vicroy et al. | Characterizing the hazard of a wake vortex encounter | |
| Pei et al. | In-flight icing risk prediction and management in consideration of wing stall | |
| Lombaerts et al. | Real time damaged aircraft model identification for reconfiguring flight control | |
| Chen et al. | Flight data validation of an icing accretion estimation scheme using super-twisting observers | |
| Capone et al. | Review and Recommended Experimental Procedures For Evaluation Of Abrupt Wing Stall Characteristics | |
| Vogel et al. | Aircraft control augmentation and health monitoring using flush air data system feedback | |
| Dogan et al. | Wake-vortex induced wind with turbulence in aerial refueling-part b: Model and simulation validation | |
| Reed | Indirect aircraft structural monitoring using artificial neural networks |