Development of an Aerodynamic Database for a Generic Hypersonic Air Vehicle

A modeling approach for a Common Aero Vehicle (CAV) with parameterized configuration is presented in this paper. A 6 degrees of freedom (DOF) rigid-body model based on winged-cone configuration is proposed. The aerodynamic coefficients are calculated using both the engineering experimental method and computational fluid dynamics (CFD) method. Two kinds of aerodynamic modals for simulation, engineering aerodynamic model (EAM) and merged aerodynamic model (MAM), are developed, and the advantages of MAM are revealed. The nominal CAV model based on MAM is obtained, which is in a general form of CAV aerodynamic model for hypersonic vehicle control design. The impact of configuration parameters on design objectives (including lift-drag ratio, volume-area ratio and longitudinal static stability) are examined. Vehicle optimization is also examined to get the optimized parameters. The Self-Adaptive Evolution (SAE) algorithm and the Sequential Quadratic Programming (SQP) algorithm are used to produce diverse sets of optimal solutions, which enable the designer to quantify tradeoffs among conflicting objectives. NomenclatureL = rolling moment 1 Associate Professor, 2 M = pitching moment Ma = Mach number MAM = Merged Aerodynamic Model N = yawing moment p = roll rate P = atmospheric pressure q = pitch rate r = yaw rate r ij = correlation coefficient between the i-th input x i and the j-th output y j R = distance between Earth center and vehicle centroid R E = mean radius of Earth RE = relative error S = reference area T = atmospheric temperature V = velocity Y = side force α = angle of attack β = angle of sideslip γ = roll angle of track γ 0 = specific heat ratio δ le = deflection angle of left elevator δ r = deflection angle of rudder δ re = deflection angle of right elevator η = volume-area ratio θ = pitch angle θ Impc = angle of impact μ = angle of track ρ = atmospheric density φ = yaw angle of track φ = roll angle φ lat = latitude φ long = longitude ψ = yaw angle

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“…According to the aerodynamic characteristics of plane-symmetry aircraft, the aerodynamic coefficients are written as follow 14,15 : …”

Section: Aerodynamic Model For Designmentioning

confidence: 99%

Modeling and Design Optimization of a Common Aero Vehicle with Parameterized Configuration

Lin

Zeshan

2012

AIAA Modeling and Simulation Technologies Conference

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“…17. Applying the Jacobian technique to the merged aerodynamic database, the linear steady-state model of the GHV is simulated throughout a realistic flight trajectory, as is also done in [10][11][12][13]. This trajectory is shown in Fig.…”

Section: Nonlinear Modeling and Simulationmentioning

confidence: 99%

“…A trial step (increment) s as in Eq. (11) is computed by completing the minimization given in Eq. (12) over the trust region N:…”

Section: Curve Fitting With Multiple Variablesmentioning

confidence: 99%

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Nonlinear Ten-Degree-of-Freedom Dynamics Model of a Generic Hypersonic Vehicle

Colgren

Keshmiri

Mirmirani

2009

Journal of Aircraft

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A nonlinear wind-tunnel and computational-fluid-dynamics-based model of the longitudinal and lateraldirectional dynamics for an airbreathing generic hypersonic vehicle is developed. The equations of motion for the generic hypersonic vehicle are derived using Newton's and Euler's equations. Results from wind-tunnel investigations, computational fluid dynamics code simulations, and analytical techniques are used to develop a merged aerodynamic database. Nonlinear analytical optimization techniques are employed to generate analytical expressions for the aerodynamic coefficients. The coupling between the aerodynamics and the propulsion systems is included. As an example, the generic hypersonic vehicle dynamic model is linearized and its behavior is studied at 5 times the speed of sound. Nomenclature= zero-lift drag increment coefficient C L = total lift coefficient for the basic vehicle C L clean = lift coefficient for the clean or basic aircraft configuration C La = lift increment coefficient for the right elevon C Le = lift increment coefficient for the left elevon C l = total rolling moment coefficient C l = rolling moment with sideslip derivative for the basic vehicle C n = total yawning moment coefficient C np = yawing moment roll-rate dynamic derivative C Y = total side force c = longitudinal reference length, mean aerodynamic chord, ft I = identity matrix I XX , I YY , I ZZ = roll, pitch, and yaw moments of inertia, slug ft 2 M = Mach number P = roll rate Q = pitch rate fQ BE g = body-frame rotational tensor with respect to the Earth frame q = dynamic pressure fqg = body-axis frame rotational quaternion tensor with respect to the Earth frame R = yaw rate R 2 = coefficient of determination S = stream thrust function S ref = reference theoretical wing area, ft 2 T = engine net thrust, lbf V T = vehicle freestream velocity, ft/s W con = weight of fuel consumed W T = weight of the vehicle, lb X, Y, Z = total aerodynamic forces (in body x, y, and z coordinates) X c:g: = longitudinal distance from momentum reference to vehicle center of gravity = angle of attack, deg = sideslip angle, rad = ratio of specific heats = fuselage cone half-angle = Euler pitch attitude angle, deg = pressure drag = Euler bank angle, deg = Euler heading angle, deg

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“…All aerodynamic data can be found in [22] in the form of figures. Based on these figures, [23] developed their analytical expressions as up to fifth-order polynomials. These highorder expressions represent a high-fidelity model of GHV which covers the whole flight envelope and contains complex coupling effects.…”

Section: Simulation Modelmentioning

confidence: 99%

An Integrated Approach to Hypersonic Entry Attitude Control

Yuan

Tan

et al. 2014

Int. J. Autom. Comput.

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Abstract:This paper presents an integrated approach based on dynamic inversion (DI) and active disturbance rejection control (ADRC) to the entry attitude control of a generic hypersonic vehicle (GHV). DI is firstly used to cancel the nonlinearities of the GHV entry model to construct a basic attitude controller. To enhance the control performance and system robustness to inevitable disturbances, ADRC techniques, including the arranged transient process (ATP), nonlinear feedback (NF), and most importantly the extended state observer (ESO), are integrated with the basic DI controller. As one primary task, the stability and estimation error of the second-order nonlinear ESO are analyzed from a brand new perspective: the nonlinear ESO is treated as a specific form of forced Liénard system. Abundant qualitative properties of the Liénard system are utilized to yield comprehensive theorems on nonlinear ESO solution behaviors, such as the boundedness, convergence, and existence of periodic solutions. Phase portraits of ESO estimation error dynamics are given to validate our analysis. At last, three groups of simulations, including comparative simulations with modeling errors, Monte Carlo runs with parametric uncertainties, and a six degrees-of-freedom reference entry trajectory tracking are executed, which demonstrate the superiority of the proposed integrated controller over the basic DI controller.

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Development of an Aerodynamic Database for a Generic Hypersonic Air Vehicle

Cited by 78 publications

References 1 publication

Modeling and Design Optimization of a Common Aero Vehicle with Parameterized Configuration

Modeling and Design Optimization of a Common Aero Vehicle with Parameterized Configuration

Nonlinear Ten-Degree-of-Freedom Dynamics Model of a Generic Hypersonic Vehicle

An Integrated Approach to Hypersonic Entry Attitude Control

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