This thesis describes the development of a series of codes for trim and longitudinal stability analysis of a helicopter in forward flight. In general, particular use of these codes can be made for parametric investigation of the effects of the external and internal systems integrated to UH-60 helicopters. However, in this thesis the trim analysis results are obtained for a clean UH-60 configuration and the results are compared with the flight test data that were acquired by ASELSAN, Inc. The first of the developed trim codes, called TRIM-CF, is based on closedform equations which give the opportunity of having quick results. The second code stems from the trim code of Prouty. That code is modified and improved during the course of this study based on the theories outlined in [3], and the resultant code is named TRIM-BE. These two trim codes are verified by solving the trim conditions of the example helicopter of [3]. Since it is simpler and requires fewer input parameters, it is more often more convenient to use the TRIM-CF code. This code is also verified by analyzing the Bo105 helicopter with the specifications given in [2]. The results are compared with the Helisim results and flight test data given in this reference. The trim analysis results of UH-60 helicopter are obtained by the TRIM-CF code and compared with flight test data. A forward flight longitudinal dynamic stability code, called DYNA-STAB, is also developed in the thesis. This code also uses the methods presented in [3]. It solves the longitudinal part of the whole coupled matrix of equations of motion of a helicopter in forward flight. The coupling is eliminated by linearization. The trim analysis results are used as inputs to the dynamic stability code and the dynamic stability characteristics of a forward flight trim case of the example helicopter [3] are analyzed. The forward flight stability code is applied to UH-60 helicopter. The codes are easily applicable to a helicopter equipped with external stores. The application procedures are also explained in this thesis.

This doctoral study aims to develop a methodology for use in determining aerodynamic models and parameters from actual flight test data for different types of autonomous flight vehicles. The stepwise regression method and equation error method are utilized for the aerodynamic model identification and parameter estimation. A closed loop aerodynamic parameter estimation approach is also applied in this study which can be used to fine tune the model parameters. Genetic algorithm is used as the optimization kernel for this purpose. In the optimization scheme, an input error cost function is used together with a final position penalty as opposed to widely utilized output error cost function. Available methods in the literature are developed for and mostly applied to the aerodynamic system identification problem of piloted aircraft / a very limited number of studies on autonomous vehicles are available in the open literature. This doctoral study shows the applicability of the existing methods to aerodynamic model identification and parameter estimation problem of autonomous vehicles. Also practical considerations for the application of model structure determination methods to autonomous vehicles are not well defined in the literature and this study serves as a guide to these considerations.

Fatigue is a well-recognized issue in lightweight and high-performance aircraft structures. As fatigue failures have led to serious accidents and caused significant economic impact in the past, design against fatigue is crucial. Fatigue testing of full-scale aircraft as well as components is an important tool for the advance identification of potential fatigue issues in both new and operational aircraft. Furthermore, coupon testing is used extensively to obtain allowables for materials and structural details to be used in the design process. To obtain accurate results from fatigue testing, not only the test object but also the used load spectrum must accurately represent reality. If the aircraft is operational, an accurate load spectrum can be obtained by measuring the loads in-flight during a sufficiently long period of normal operation of the aircraft. However, the in-flight measured loads data contains an extraordinarily large number of cycles, resulting in long and uneconomical test durations. This thesis aims to propose a method for the selection of an optimal filtering level for fatigue test spectra developed from in-flight measured loads. The thesis also discusses and recommends methods for in-flight measurement of loads, cycle counting as well as damage evaluation using a crack-growth approach. Furthermore, ways to validate the proposed method and its practical application are discussed. An example filtering study is conducted using four different specimens chosen to represent typical structural details of aircraft. The study uses real in-flight measured loads of a light aircraft and also discusses temperature compensation of the loads data. The effect of filtering on fatigue damage is evaluated using crack-growth simulations conducted at a range of filtering and stress levels.  The results show that a remarkable reduction of testing time is possible and as many as 99 % of all cycles in the studied flight load history can be discarded without significantly reducing fatigue damage. The allowable filtering level is shown to differ between the specimens and the different stages of fatigue crack growth. In addition, the applied stress level is found to have a consistent effect on the allowable filtering level.

No description available.

Um método para avaliação do uso de ganho adequado em ensaios de verificação de PIO (Pilot Induced Oscillations) é apresentado. As tarefas de manobra sintética (Synthetic Tracking Task) são utilizadas para demonstração. A teoria é baseada no conceito de entropia estatística proveniente da teoria da informação e no modelo estrutural do piloto humano. O método é apresentado para manobras executadas no eixo lateral e oferece uma medida do ganho humano utilizado durante a sua execução em malha-fechada. Para a modelagem da planta é utilizado modelo black-box com equacionamento de espaço de estados e identificação de parâmetros. Dados de ensaios em voo provenientes de uma aeronave de transporte certificada FAR-25 são utilizados para medir a razão entre o tempo gasto pelo piloto humano em uma malha fechada em posição versus o tempo em uma malha de derivada da posição (roll vs. roll rate). Esta medida é proposta como validadora da execução correta do ensaio. / A method is proposed to verify losed-loop adequate flight test piloting gain in PIO aircraft certification. The synthetic tracking task PIO flight test is used. The theory is based on the entropy concept from information theory and on the structural pilot model of the human pilot. The method is presented for single axis pilot tracking maneuvers and offers a measure of the human pilot gain employed during its execution. A black-box, state-space, parameter-identified model is used for the plant. Flight test data from a FAR-25 transport aircraft is used to verify the theory of how to determine a measure of the ratio between time spent by the human pilot in the error loop versus in the error rate loop to control the aircraft. This measure is proposed as a test point validation method for PIO flight testing.

Carefree handling refers to the ability of a pilot to operate an aircraft without the need to continuously monitor aircraft operating limits. At the heart of all carefree handling or maneuvering systems, also referred to as envelope protection systems, are algorithms and methods for predicting future limit violations. Recently, envelope protection methods that have gained more acceptance, translate limit proximity information to its equivalent in the control channel. Envelope protection algorithms either use very small prediction horizon or are static methods with no capability to adapt to changes in system configurations. Adaptive approaches maximizing prediction horizon such as dynamic trim, are only applicable to steady-state-response critical limit parameters. In this thesis, a new adaptive envelope protection method is developed that is applicable to steady-state and transient response critical limit parameters. The approach is based upon devising the most aggressive optimal control profile to the limit boundary and using it to compute control limits. Pilot-in-the-loop evaluations of the proposed approach are conducted at the Georgia Tech Carefree Maneuver lab for transient longitudinal hub moment limit protection. Carefree maneuvering is the dual of carefree handling in the realm of autonomous Uninhabited Aerial Vehicles (UAVs). Designing a flight control system to fully and effectively utilize the operational flight envelope is very difficult. With the increasing role and demands for extreme maneuverability there is a need for developing envelope protection methods for autonomous UAVs. In this thesis, a full-authority automatic envelope protection method is proposed for limit protection in UAVs. The approach uses adaptive estimate of limit parameter dynamics and finite-time horizon predictions to detect impending limit boundary violations. Limit violations are prevented by treating the limit boundary as an obstacle and by correcting nominal control/command inputs to track a limit parameter safe-response profile near the limit boundary. The method is evaluated using software-in-the-loop and flight evaluations on the Georgia Tech unmanned rotorcraft platform- GTMax. The thesis also develops and evaluates an extension for calculating control margins based on restricting limit parameter response aggressiveness near the limit boundary.

Traditionally, the task of determining aircraft position and attitude for automatic control has been handled by the combination of an inertial measurement unit (IMU) with a Global Positioning System (GPS) receiver. In this configuration, accelerations and angular rates from the IMU can be integrated forward in time, and position updates from the GPS can be used to bound the errors that result from this integration. However, reliance on the reception of GPS signals places artificial constraints on aircraft such as small unmanned aerial vehicles (UAVs) that are otherwise physically capable of operation in indoor, cluttered, or adversarial environments. Therefore, this work investigates methods for incorporating a monocular vision sensor into a standard avionics suite. Vision sensors possess the potential to extract information about the surrounding environment and determine the locations of features or points of interest. Having mapped out landmarks in an unknown environment, subsequent observations by the vision sensor can in turn be used to resolve aircraft position and orientation while continuing to map out new features. An extended Kalman filter framework for performing the tasks of vision-based mapping and navigation is presented. Feature points are detected in each image using a Harris corner detector, and these feature measurements are corresponded from frame to frame using a statistical Z-test. When GPS is available, sequential observations of a single landmark point allow the point's location in inertial space to be estimated. When GPS is not available, landmarks that have been sufficiently triangulated can be used for estimating vehicle position and attitude. Simulation and real-time flight test results for vision-based mapping and navigation are presented to demonstrate feasibility in real-time applications. These methods are then integrated into a practical framework for flight in GPS-denied environments and verified through the autonomous flight of a UAV during a loss-of-GPS scenario. The methodology is also extended to the application of vehicles equipped with stereo vision systems. This framework enables aircraft capable of hovering in place to maintain a bounded pose estimate indefinitely without drift during a GPS outage.

Um método para avaliação do uso de ganho adequado em ensaios de verificação de PIO (Pilot Induced Oscillations) é apresentado. As tarefas de manobra sintética (Synthetic Tracking Task) são utilizadas para demonstração. A teoria é baseada no conceito de entropia estatística proveniente da teoria da informação e no modelo estrutural do piloto humano. O método é apresentado para manobras executadas no eixo lateral e oferece uma medida do ganho humano utilizado durante a sua execução em malha-fechada. Para a modelagem da planta é utilizado modelo black-box com equacionamento de espaço de estados e identificação de parâmetros. Dados de ensaios em voo provenientes de uma aeronave de transporte certificada FAR-25 são utilizados para medir a razão entre o tempo gasto pelo piloto humano em uma malha fechada em posição versus o tempo em uma malha de derivada da posição (roll vs. roll rate). Esta medida é proposta como validadora da execução correta do ensaio. / A method is proposed to verify losed-loop adequate flight test piloting gain in PIO aircraft certification. The synthetic tracking task PIO flight test is used. The theory is based on the entropy concept from information theory and on the structural pilot model of the human pilot. The method is presented for single axis pilot tracking maneuvers and offers a measure of the human pilot gain employed during its execution. A black-box, state-space, parameter-identified model is used for the plant. Flight test data from a FAR-25 transport aircraft is used to verify the theory of how to determine a measure of the ratio between time spent by the human pilot in the error loop versus in the error rate loop to control the aircraft. This measure is proposed as a test point validation method for PIO flight testing.