Shahriar Keshmiri

Six -DOF Modeling and Simulation of a Generic Hypersonic Vehicle for Conceptual Design Studies

This paper covers the development of a CFD -based Six Degrees of Freedom simulation of a generic hypersonic vehicle [1]. The model and simulation are being developed to support conceptual design studies of hypersonic vehicles with multiple cycle engines. This includes both air breathing and rocket propulsion models. This work is supporte d by the NASA grant # NCC4 -158, in support of their emphasis on new aerospace vehicle concepts and hypersonic technologies. A description of the aerodynamic and propulsion system models developed is included in this paper.

Development of an Aerodynamic Database for a Generic Hypersonic Air Vehicle

An overview of the aerodynami c characteristics, along with the process for developing an aerodynamic database for the Generic Hypersonic Vehicle (GH V), is presented in this paper. The experimental investigation of the aerodynamic characteristics for the blunt bo dy of the GHV has been used as the core of the simulation model . The gaps in the wind tunnel data have been filled using the best available CFD results. The CFD results are compared with the equivalent win d tunnel data for authenticity. The expressions for the aerodynamic f orces and the aerodynamic coeffic ients acting on the GHV are dev eloped. The aerodynamic database covers the range of flight Mach numbers, angles of attack, sideslip angles, a nd control surface deflections. The aerodynamic mo del is then used within the si mulation of the GHV. Nomenclature alt. = altitude, ft b = lateral -directional reference length, span, ft c = longitudinal reference length, mean aerodynamic chord, ft CD = total drag coefficient, n. d. CDa = drag increment coefficient for basic vehicle, n. d. CD-�a = drag increment coefficient for right elevon, n. d. CD-�e = drag increment coefficient for left elevon, n. d. CD-�r = drag increment coefficient for rudder, n. d. CL = total lift coefficient for basic vehicle, n . d. CLa = lift increment coefficient for basic vehicle, n. d. CL-�a = lift increment coefficient for right elevon, n. d. CL-�e = lift increment coefficient for left elevon, n. d. CL-�r = lift increment coefficient for rudder, n. d. CY = tota l side force, n. d. CY� = side force with sideslip derivative for basic vehicle, n. d. CY-�a = side force increment coefficient for right elevon, n. d. CY-�e = side force, increment coefficient for left elevon, n. d. CY-�r = side force, increment coefficient for rudder, n. d. Cl = total rolling moment coefficient, n. d.

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

A nonlinear wind-tunnel and computational-fluid-dynamics-based model of the longitudinal and lateral-directional dynamics for an airbreathing generic hypersonic vehicle is developed. The equations of motion for the generic hypersonic vehicle are derived using Newtons and Eulers 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.

Six -DOF Modeling and Simulation of a Generic Hypersonic Vehicle for Control and Navigation Purposes

This paper covers the development of a Six Degrees of Freedom simulation of a generic hypersonic vehicle (GHV) [1] based on two different aerodynamic models and the aerodynamic database developed in reference [2] for control and navigation purposes. The results from APAS, which is an engineering level CFD program, from a high fidelity CFD code, STARS, and from wind tunnel experiments are used in this research. For the GHV model a combined cycle engine including a turbojet, ramjet-scramjet, and rocket engines are designed to cover subsonic, supersonic, and hypersonic speeds. Using numerical linearization techniques including the Jacobian method, the LTI state equations were developed. This work is supported partially by an Air Force grant, in support of their emphasis on new aerospace vehicle concepts and hypersonic technologies.

Fuzzy-Logic Modeling of a Rolling Unmanned Vehicle in Antarctica Wind Shear

of wind shear are investigated using the recorded test data during a flight from the Pegasus white ice runway in Antarctica. The main purpose of this paper is to determine the reasons and characteristics of roll oscillations for improvement of autopilot design and ground operator training. The Meridian flight test is conducted with the necessaryrangeconstraint, which precludes steadylevel flight.The measured orestimated data,such as theangle of attack and sideslip angle, are filtered through a nonlinear compatibility analysis. The estimated aerodynamic coefficients are modeled as implicit functions of filtered flight variables in a concept of aerodynamic model identification, instead of parameter identification. A model identification method called fuzzy-logic modeling is used to set up the aerodynamic models without assuming the functional relations. The aircraft’s oscillatory stability and control derivatives are found to be significantly impacted by the environmental disturbances. The exhibited highly oscillatory motion in the manual-control mode is analyzed and identified as the pilot-induced oscillation with a new energy method. It is shown that the pilot-induced oscillation is identified as the motion when the motion energy is increasedbythecontrolinput.Intheautopilot flight,themotionisdeterminedtobewingrock,whichisexcitedbythe pilot-induced oscillation in the manual mode and sustained by the interaction between the wing wake and the V tail.

UAS-Based Radar Sounding of the Polar Ice Sheets

Both the Greenland and Antarctic ice sheets are currently losing mass and contributing to global sea level rise. To predict the response of these ice sheets to a warming climate, ice-sheet models must be improved by incorporating information on the bed topography and basal conditions of fast-flowing glaciers near their grounding lines. High-sensitivity, low-frequency radars with 2-D aperture synthesis capability are needed to sound and image fast-flowing glaciers with very rough surfaces and ice that contains inclusions. In response to this need, CReSIS developed an Unmanned Aircraft System (UAS) equipped with a dual-frequency radar that operates at approximately 14 and 35 MHz. The radar transmits 100-W peak power at a pulse repetition frequency of 10 kHz, operates from 20 W of DC power, and weighs approximately 2 kg. The UAS has a take-off weight of about 38.5 kg and a range of approximately 100 km per gallon of fuel. We recently completed several successful test flights of the UAS equipped with the dual-frequency radar at a field camp in Antarctica. The radar measurements performed as a part of these test flights represent the first-ever successful sounding of glacial ice with a UAS-based radar. We also collected data for synthesizing a 2-D aperture, which is required to prevent off-vertical scatter, caused by the rough surfaces of fast-flowing glaciers, from masking bed echoes. In this article, we provide a brief overview of the need for radar soundings of fast-flowing glaciers at low-frequencies and a brief description of the UAS and radar. We also discuss our field operations and provide sample results from data collected in Antarctica. Finally, we present our future plans, which include miniaturizing the radar and collecting measurements in Greenland.

Development of a Pilot Training Platform for UAVs Using a 6DOF Nonlinear Model with Flight Test Validation

This paper describes the evaluation of three different modeling and simulation techniques to support unmanned aerial vehicle development for glacial ice research. A Cloud Cap Technologies Piccolo II autopilot is integrated within a 1/3 scale Yak-54. Two hardware-in-the-loop (HIL) simulation models of the Yak-54 are developed using tools provided with the Piccolo II. Conventional parametric modeling is utilized separate from the Piccolo system and two state space linear models are developed for both longitudinal and lateral dynamics. Open loop flight tests are conducted and the results are used to evaluate the accuracy of each modeling method. The best modeling data set is selected and used to develop a six-degree of freedom (6DOF) nonlinear model. A comparison of the nonlinear and linear model’s responses to the flight test data for each dynamic mode was performed. The study reveals that the 6DOF nonlinear model provides more accurate estimates of the dynamics of the vehicle than the linear model in every aspect. A pilot training platform is developed using the 6DOF nonlinear model in conjunction with a pilot joystick device and 3D visualization software for real-time simulation.

Nonlinear Model Predictive Controller for Navigation, Guidance and Control of a Fixed-Wing UAV

A Nonlinear Model Predictive Controller (NMPC) is designed to perform guidance, navigation, and control of a fixed-wing UAV in waypoint trajectory tracking. The inherent nonlinear nature of the aircraft together with the limited desired operation ranges of both controls and states variables make the use of an on-line control law computation more appropriate. The MPC theory allows an optimal on-line solution, when enough onboard computational power is available. Using nonlinear guidance laws for both lateral and longitudinal planes, extended Kalman filter estimations if required, and a complete nonlinear model of the UAV, the NMPC generates on-line optimal or suboptimal control signals to keep the UAV in trajectory following.

Advanced H-Infinity Trainer Autopilot

This paper presents an autopilot algorithm and simulation that includes a nonlinear guidance logic and an H-infinity MIMO controller for the lateral-directional and longitudinal dynamics of the YAK-54 UAV. Based on waypoints and UAV position and velocity the nonlinear guidance module generates the necessary commands to keep the aircraft within the desired trajectory. These commands were then used by the H-infinity controller for robust control purposes. Simulations have shown that both the guidance module and the robust controller performed well with small trajectory tracking errors. This analysis was compared with flight test results from a COTS Autopilot system and the results demonstrated a superb performance.

Modeling and Simulation of the Yak-54 Scaled Unmanned Aerial Vehicle Using Parameter and System Identification

I. Abstract Modeling and experimental system identification results for the Yak-54 scaled unmanned aerial vehicle (UAV) are presented. The numerical values of the aerodynamic derivatives are computed using Advanced Aircraft Analysis (AAA) software and the geometric parameters of the airplane. A 6-DOF linear time-invariant (LTI) dynamic model of the Yak-54 scaled UAV is developed and used for stability and controls analyses. Results are used to identify the stability and control derivatives of the aircraft. For comparison a series of flight tests are conducted. The flight test results are utilized for system identification using the MATLAB System I.D. toolbox. The comparison results are used in the development of a new autopilot system for small UAVs.