Verification in Relevant Environment of a Physics-Based Synthetic Sensor for Flow Angle Estimation

被引:3
|
作者
Lerro, Angelo [1 ]
Gili, Piero [1 ]
Pisani, Marco [2 ]
机构
[1] Politecn Torino, Dept Mech & Aerosp Engn, Corso Duca Abruzzi 24, I-10129 Turin, Italy
[2] Ist Nazl Ric Metrol, Str Cacce, Str Cacce,91, I-10135 Turin, Italy
关键词
air data system; flow angle; angle-of-attack; angle-of-sideslip; flight dynamics; flight testing; synthetic sensor; analytical redundancy; model-free; physics-based; AERIAL VEHICLES UAVS; OF-ATTACK; ALGORITHM; AIRSPEED;
D O I
10.3390/electronics11010165
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In the area of synthetic sensors for flow angle estimation, the present work aims to describe the verification in a relevant environment of a physics-based approach using a dedicated technological demonstrator. The flow angle synthetic solution is based on a model-free, or physics-based, scheme and, therefore, it is applicable to any flying body. The demonstrator also encompasses physical sensors that provide all the necessary inputs to the synthetic sensors to estimate the angle-of-attack and the angle-of-sideslip. The uncertainty budgets of the physical sensors are evaluated to corrupt the flight simulator data with the aim of reproducing a realistic scenario to verify the synthetic sensors. The proposed approach for the flow angle estimation is suitable for modern and future aircraft, such as drones and urban mobility air vehicles. The results presented in this work show that the proposed approach can be effective in relevant scenarios even though some limitations can arise.
引用
收藏
页数:22
相关论文
共 50 条
  • [1] Physics-based modelling for a closed form solution for flow angle estimation
    Lerro, Angelo
    ADVANCES IN AIRCRAFT AND SPACECRAFT SCIENCE, 2021, 8 (04): : 273 - 287
  • [2] Physics-based flow estimation of fluids
    Nakajima, Y
    Inomata, H
    Nogawa, H
    Sato, Y
    Tamura, S
    Okazaki, K
    Torii, S
    PATTERN RECOGNITION, 2003, 36 (05) : 1203 - 1212
  • [3] Physics-Based Via Model Development and Verification
    Zhang, Jianmin
    Chen, Qinghua B.
    Yang, Zhiping
    Drewniak, James L.
    Orlandi, Antonio
    2010 ASIA-PACIFIC INTERNATIONAL SYMPOSIUM ON ELECTROMAGNETIC COMPATIBILITY & TECHNICAL EXHIBITION ON EMC RF/MICROWAVE MEASUREMENTS & INSTRUMENTATION, 2010, : 1043 - 1046
  • [4] Physics-Based Simulation in the CASTLE Environment
    Pope, Art
    Long, Chris
    Bramsen, Diane
    BIOLOGICALLY INSPIRED COGNITIVE ARCHITECTURES 2011, 2011, 233 : 295 - 295
  • [5] Physics-based optical flow estimation under varying illumination conditions
    Liao, Xiaoxin
    Cai, Zemin
    Chen, Jun
    Liu, Tianshu
    Lai, Jian-huang
    SIGNAL PROCESSING-IMAGE COMMUNICATION, 2023, 117
  • [6] Adaptive Battery Management and Parameter Estimation Through Physics-Based Modeling and Experimental Verification
    Lashway, Christopher R.
    Mohammed, Osama A.
    IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION, 2016, 2 (04): : 454 - 464
  • [7] An analysis of physics-based optical flow
    Wang, Bo
    Cai, Zemin
    Shen, Lixin
    Liu, Tianshu
    JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, 2015, 276 : 62 - 80
  • [8] Physics-based Differentiable Depth Sensor Simulation
    Planche, Benjamin
    Singh, Rajat Vikram
    2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2021), 2021, : 14367 - 14377
  • [9] Physics-Based Deep Learning for Flow Problems
    Sun, Yubiao
    Sun, Qiankun
    Qin, Kan
    ENERGIES, 2021, 14 (22)
  • [10] The SAIFE Project: Demonstration of a Model-Free Synthetic Sensor for Flow Angle Estimation
    Lerro, Angelo
    Brandl, Alberto
    Gili, Piero
    Pisani, Marco
    2021 IEEE 8TH INTERNATIONAL WORKSHOP ON METROLOGY FOR AEROSPACE (IEEE METROAEROSPACE), 2021, : 98 - 103