Ravindra V. Jategaonkar

Flight vehicle system identification : a time domain methodology

This valuable volume offers a systematic approach to flight vehicle system identification and covers exhaustively the time-domain methodology. It addresses in detail the theoretical and practical aspects of various parameter estimation methods, including those in the stochastic framework and focusing on nonlinear models, cost functions, optimization methods, and residual analysis. A pragmatic and balanced account of pros and cons in each case are provided. The book also presents data gathering and model validation and covers both large-scale systems and high-fidelity modeling. Real world problems dealing with a variety of flight vehicle applications are addressed and solutions are provided. Examples encompass such problems as estimation of aerodynamics, stability, and control derivatives from flight data, flight path reconstruction, nonlinearities in control surface effectiveness, stall hysteresis, unstable aircraft, and other critical considerations. Beginners, as well as practicing researchers, engineers, and working professionals who wish to refresh or broaden their knowledge of flight vehicle system identification, will find this book highly beneficial. Based on years of experience, the book also provides recommendations for overcoming problems likely to be faced in developing complex nonlinear and high-fidelity models and can help the novice negotiate the challenges of developing highly accurate mathematical models and aerodynamic databases from experimental flight data. Software that runs under MATLAB® and sample flight data are provided to assist the reader in reworking the examples presented in the text. The software can also be adapted to the reader’s own interests.

Evolution of flight vehicle system identification

Synopsis: From the nostalgic remembrance of the first dynamic flight test this Survey Paper traces several milestones in the history of flight vehicle system identification. A comprehensive account of modern system identification techniques is provided. Several challenging examples bring out the fact that these techniques have reached a high level of maturity, making them a sophisticated and powerful tool not only for research purposes, but also to support the needs of the aircraft industry. This survey paper includes 183 references and provides a consolidated list of publications on the subject.

Aerodynamic Modeling and System Identification from Flight Data - Recent Applications at DLR

System identification is fundamental to any observed dynamic process. This overview presentation brings out why and what system identification is as applied to flight vehicles. A historical background is briefly provided, tracing the developments to the 18th Century and early flight experiments to 1920s. This is followed by highlighting the unified Quad-M approach to flight vehicle system identification that has evolved over the last three decades. Several examples are presented, covering: 1) generation of complete aerodynamic databases, 2) estimation of nonlinear models for control surface effectiveness and stall hysteresis, 3) aerodynamic effects due to landing gear, and 4) Air drop. Some aspects of model validation are brought out. Finally, diversified applications to other flight vehicles are briefly elaborated to demonstrate the wide domain of applicability. The talk is concluded by indicating the possible future directions of work.

Aerodynamic Parameter Estimation from Flight Data Applying Extended and Unscented Kalman Filter

Article history: Received 28 October 2008 Accepted 13 October 2009 Available online 27 October 2009

Five-Hole Flow Angle Probe Calibration from Dynamic and Tower Flyby Maneuvers

Flight-test and data analysis techniques applied to calibrate the static pressure measured by pitot static systems and the flow angles measured by a five-hole probe mounted on a noseboom are described.13; Dynamic maneuvers with rapid variations in the aircraft motion are analyzed by application of parameter estimation techniques based on he output error method to calibrate the angle of attack and angle of sideslip. A complementary approach based on the Kalman filter technique is applied to a wind-box maneuver to calibrate the flow variables. The tower flyby maneuvers are analyzed using the classical approach of altitude determination through geometrical evaluation of photographs,and accurate information is derived from redundant sources to calibrate the pitot static system. The investigations showed that the static pressure measured by aircraft-installed pitot13; static system is accurate, sufficiently whereas that measured by an additional sensor mounted on the noseboom required speed-dependent correction. The flight estimated sensitivity factors for the flow angles measured by the five-hole probe agreed reasonably well with the manufacturers specifications subject to corrections for biases resulting from misalignment and time delays caused by the recording equipment.

Data Analysis of Phoenix RLV Demonstrator Flight Test

Within the framework of the German ASTRA (Advanced Systems and Technologies for RLV Application) program, the Phoenix project was established to implement experimental steps towards the development of a next generation space transportation system. The Phoenix vehicle was designed to flight demonstrate the automatic and un-powered horizontal landing of a representative, winged reusable launcher vehicle (RLV). The shape of the test vehicle was derived from the suborbital RLV concept Hopper. Three automatic landing tests were completed successfully in May 2004. Methods of system identification were applied to the flight data to evaluate the performance and to improve the design models and databases for future applications. A specific emphasis was placed on the evaluation of the on-board navigation system, air data sensor, aerodynamic model, landing gear effects and ground roll characteristics. This paper gives a brief overview of the Phoenix mission and elaborates on the flight data analysis and of the preceding wind tunnel campaigns, to allow a comparison of results from different approaches.

Data analysis of Phoenix reusable launch vehicle demonstrator flight test

The Phoenix vehicle was designed to flight demonstrate the automatic and unpowered horizontal landing of a representative, winged reusable launch vehicle. The shape of the test vehicle was derived from the suborbital reusable launch vehicle concept Hopper. Three automatic landing tests were completed successfully in May 2004. Methods of system identification were applied to the flight data to evaluate the performance and to improve the design models and databases for future applications. A specific emphasis was placed on the evaluation of the onboard navigation system, air data sensor, aerodynamic model, landing gear effects and ground-roll characteristics. This paper gives a brief overview of the Phoenix mission and elaborates on the flight data analysis and of the preceding wind tunnel campaigns, to allow a comparison of results from different approaches.

CALIBRATION OF FIVE-HOLE PROBE FOR FLOW ANGLES FROM DYNAMIC AND TOWER FLY-BY MANEUVERS

This paper describes the flight test and data analysis techniques applied to calibrate the static pressure measured by the pitot static systems and the flow angles measured by a five-hole probe mounted on a noseboom. Dynamic maneuvers with rapid variations in the aircraft motion are analyzed applying modern parameter estimation techniques based on the output error method to calibrate the angle of attack and angle of sideslip. A complementary approach based on the Kalman Filter technique is applied to wind-box maneuver to calibrate the flow variables. The tower fly- by maneuvers are analyzed using the classical approach of altitude determination through geometrical evaluation of photos; and accurate information is derived from redundant sources to calibrate the pitot static system. The investigations showed that the static pressure measured by aircraft installed pitot static system is accurate enough whereas that measured by an additional sensor mounted on the noseboom required speed dependent correction. The flight estimated sensitivity factors for the flow angles measured by the five-hole probe agreed reasonably well with the manufacturers specifications subject to corrections for biases resulting from misalignment and time delays caused by the recording equipment.