Experimental Study and Neural Network Modeling of Aerodynamic Characteristics of Canard Aircraft at High Angles of Attack

Abstract

Flow over an aircraft at high angles of attack is characterized by a combination of separated and vortical flows that interact with each other and with the airframe. As a result, there is a set of phenomena negatively affecting the aircraft's performance, stability and control, namely, degradation of lifting force, nonlinear variation of pitching moment, positive damping, etc. Wind tunnel study of aerodynamic characteristics of a prospective transonic aircraft, which is in a canard configuration, is discussed in the paper. A three-stage experimental campaign was undertaken. In the first stage, a steady aerodynamic experiment was conducted. The influence of a reduced oscillation frequency and angle of attack on unsteady aerodynamic characteristics was studied in the second stage. In the third stage, forced large-amplitude oscillation tests were carried out for the detailed investigation of the unsteady aerodynamics in the extended flight envelope. The experimental results demonstrate the strongly nonlinear behavior of the aerodynamic characteristics because of canard vortex effects on the wing. The obtained data are used to design and test mathematical models of unsteady aerodynamics via different popular approaches, namely the Neural Network (NN) technique and the phenomenological state space modeling technique. Different NN architectures, namely feed-forward and recurrent, are considered and compared. Thorough analysis of the performance of the models revealed that the Recurrent Neural Network (RNN) is a universal approximation tool for modeling of dynamic processes with high generalization abilities.

Gaussian Process Adaptive Incremental Backstepping Flight Control

“…x x u u xu (4) Assuming that the increment in state 𝛥𝒙 = 𝒙 − 𝒙 0 is much smaller than the increment in both state derivative 𝛥𝒙̇= 𝒙̇− 𝒙̇0 and input 𝛥𝒖 = 𝒖 − 𝒖 0 , the dynamics (4) can be further simplified 0 B    xu (5) where 𝐵 0 = 𝜕𝒇 𝒙 ( 𝒙,𝒖 ) 𝜕𝒖 is a control effectiveness matrix. The dynamics equation in the form (5) states that the ID of the system is produced by the control input increment. For the implementation of such a concept, it is assumed that sampling time is small.…”

“…Recently, great efforts have been undertaken to develop aircraft control design t ools and techniques for analysis and improvement of safe flight [2][3][4][5][6][7][8]. The idea that non-conventional control strategies can prevent possible accidents and recover aircraft from dangerous situations stimulates researches toward fault -tolerant and adaptive flight control [9][10][11][12].…”

Yer Etkisi Altındaki Delta Kanat Üzerinde Oluşan Taşıma Katsayısının Yapay Sinir Ağı Kullanılarak Tahmin Edilmesi

“…Ignatyev and Khrabrov [26] developed a neural network model to predict the aerodynamic characteristics of canard aircraft at high angles of attack. The aircraft is equipped with leading-edge extension (LEX) and a canard surface with a high sweep angle.…”

Interplay of unsteady aerodynamics and flight dynamics of transport aircraft in icing conditions

“…Most of the researches are aimed at studying the aerodynamics and flight dynamics of an iced aircraft at trim conditions that makes proper design of control algorithms. Nevertheless, modelling of flight dynamics in the extended flight envelope is crucial for understanding of reasons that might cause aircraft loss of control and, thus, helps to improve flight safety [15]- [17]. To support these activities, the technique for estimation of stability boundary of an aircraft in icing conditions based on the analyzing the region of attraction was proposed in [18].…”