Piece-wise Identification and Analysis of the Aerodynamic Coefficients, Trim Conditions, and Safe Sets of the Generic Transport Model

Cunis, Torbjørn; Burlion, Laurent; Condomines, Jean-Philippe

doi:10.2514/6.2018-1114

Cited by 3 publications

(5 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Due to their continuous and differentiable nature, polynomials provide the possibility of defining and evaluating models based on analytical computation [52]. So far polynomials have shown remarkable capabilities in modeling the GTM short period dynamics [53] and more recently in piecewise modeling of the fullenvelope aerodynamic coefficients of the GTM [52,54]. More specifically, the idea of interpolating flight envelopes in the offline database approach mentioned in Sec.…”

Section: A Linear Least-squaresmentioning

confidence: 99%

Investigating Impaired Aircraft's Flight Envelope Variation Predictability Using Least-Squares Regression Analysis

Norouzi

Kosari

Sabour

2020

Journal of Aerospace Information Systems

View full text Add to dashboard Cite

Aircraft failures alter the aircraft dynamics and cause maneuvering flight envelope to change. Such envelope variations are nonlinear and generally unpredictable by the pilot as they are governed by the aircraft complex dynamics. Hence, in order to prevent in-flight Loss of Control it is crucial to practically predict the impaired aircraft's flight envelope variation due to any a-priori unknown failure degree. This paper investigates the predictability of the number of trim points within the maneuvering flight envelope and its centroid using both linear and nonlinear least-squares estimation methods. To do so, various polynomial models and nonlinear models based on hyperbolic tangent function are developed and compared which incorporate the influencing factors on the envelope variations as the inputs and estimate the centroid and the number of trim points of the maneuvering flight envelope at any intended failure degree. Results indicate that both the polynomial and hyperbolic tangent function-based models are capable of predicting the impaired fight envelope variation with good precision. Furthermore, it is shown that the regression equation of the best polynomial fit enables direct assessment of the impaired aircraft's flight envelope contraction and displacement sensitivity to the specific parameters characterizing aircraft failure and flight condition.Nomenclature V = total airspeed, knot ,  = angle of attack, sideslip angle, respectively, deg p, q, r = angular velocity components (roll rate, pitch rate, yaw rate, respectively), deg/s 1 Ph.D. Candidate, Faculty of New Sciences and Technologies; ramin.norouzi@ut.ac.ir. Student Member AIAA. 2 Associate Professor, Faculty of New Sciences and Technologies; kosari_a@ut.ac.ir. 3 Assistant Professor, Faculty of New Sciences and Technologies; sabourmh@ut.ac.ir. , , ,  = Euler angles (roll, pitch, yaw, respectively), flight path angle, deg , = state vector, control vector, respectively , , , ℎ = deflection angles (elevator, aileron, rudder, respectively), deg, throttle setting (%) ∈ [0, 1] , �, = fitted model's residual, outcome, parameters (coefficients) vectors, respectively , = predictor vector, model parameters (coefficients) vector, respectively = total degree of polynomial , ℍ, , = gradient, Hessian, Jacobian of the objective function , identity matrix, respectively = Newton's method search direction = Marquardt parameter = hyperbolic tangent function 1 , 2 = total number of neurons in the first (hidden) layer, second (last) layer, respectively = backpropagation training iteration ℒ , ℒ , ℒ , ℒ, = (net output, net input, bias) of ℒ ℎ neuron in layer , respectively ℒ,= weight's element of ℒ ℎ neuron in layer due to ℎ neuron of the previous layer .̂ = standard backpropagation sensitivity, Marquardt sensitivity, respectively ℰ, = contribution of the ℰ ℎ neuron of the last (second) layer to the error of the ℎ training sample = statistical expected value of the ℎ input factor Subscripts , = total number of training samples, total number of model parameters, res...

show abstract

Section: A Linear Least-squaresmentioning

confidence: 99%

Investigating Impaired Aircraft's Flight Envelope Variation Predictability Using Least-Squares Regression Analysis

Norouzi

Kosari

Sabour

2020

Journal of Aerospace Information Systems

View full text Add to dashboard Cite

show abstract

“…Here, simple polynomial models are unsuitable to represent the full-envelope aerodynamics ( Fig. 3; see also [12]). Instead, we will fit the pre-stall and post-stall dynamics piecewise to…”

Section: B Aerodynamic Coefficientsmentioning

confidence: 99%

“…Polynomial models of the aerodynamic coefficients have provided a constructive method to define and evaluate models based on analytical computation due to their continuous and differentiable nature. Despite the fact that polynomial models have been published recently [10,11], none of the results represent the aerodynamic coefficients well in the entire region of the envelope [12]. Indeed, at the stall angle of attack, the laminar flow around the wings in the pre-stall region changes to turbulent flow and remains so in post-stall.…”

Section: Introductionmentioning

confidence: 95%

“…representations proposed for the full-envelope aerodynamics are still insufficient for non-linear analysis and control design [12]. Therefore, improved methods for accurate modeling are imperative, in particular when developing robust and powerful advanced control strategies for upset recovery.…”

Section: Introductionmentioning

confidence: 99%

“…l , C m , C n ; and the changes of attitude Φ, Θ, Ψ are functions of the angular body rates. Comparison of 3rd-order polynomial[10,11] and piecewise identifications [12]. …”

mentioning

confidence: 99%

See 2 more Smart Citations