Účelem této práce je navrhnout zjednodušené modely klasického a fuzzy regulátoru pro automatické udržení výšky letu a porovnat jejich vlastnosti. Cílem je vyšetřit, zda fuzzy regulátor neprojeví lepší chování než klasický. Prostředkem pro návrh a srovnání vlastností obou regulátorů je posouzení odezev modelu systému letadlo-regulátor na požadavek změny výšky a modelu turbulence. Simulace jsou realizovány s pomocí prostředí MATLAB SIMULINK.

The objective of this work is to adopt and further expand the type design of the SONG motor glider. The study will result in the basic aerodynamic calculation and the design of lateral control system including structural strength inspection of selected parts. Subsequently, the proposal will allow for further calculation to be made (of flight mechanics, wings strength or fuselage and empennage firmness) and for more specific constructional design of individual components of the glider.

A modern ghter aircraft has an advanced ight control system which highly augmentsthe control inputs from the pilot. To verify a new iteration of the control system is a timeconsuming and expensive task. It is desired to nd qualities that is not satisfactory to thepilot as early as possible in the verication process to reduce the cost for design changes.The primary objective of this thesis is to develop methods that can be used for automaticalevaluation of aircraft ying qualities from the data provided by a desktop simulator. A desktopsimulator is cheap to use compared to ight tests and tests with a pilot in a simulator.Only ghter aircraft in the precision ight phase are studied however the methods developedcould easily be extended to include other types of aircraft and other phases of ight.To evaluate the ying qualities two sets of criteria are used the MIL-F-8785C standardand the Gibson criteria. The MIL-F-8785C standard uses a second order linear system toevaluate the aircraft's ying qualities. The linear system is estimated from the nonlineardata and evaluated against the MIL-F-8785C standard. The Gibson criteria studies the timeand frequency domain directly and are designed to work with highly augmented aircraft.The set of Gibson criteria used in this thesis primary evaluates data from the time domainhowever one criterion from the frequency domain is studied.The methods developed to evaluate the ying qualities from the MIL-F-8785C standardonly works for a small part of the ight envelope furthermore they show a large dierencefor what is considered acceptable ying qualities. Because of this the methods developed forthe MIL-F-8785C standard are considered not to be suited for evaluating ying qualities forhighly augmented aircraft. The methods developed to evaluate the ying qualities againstthe Gibson criteria works for a large part of the ight and also show a high accuracy. Thismakes the methods suited for evaluation of the ying qualities.

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This work introduces a design and implementation of using multiple unmanned aerial vehicles (UAVs) to achieve cooperative formation flight based on the personal remote sensing platforms developed by the author and the colleagues in the Center for Self-Organizing and Intelligent Systems (CSOIS). The main research objective is to simulate the multiple UAV system, design a multi-agent controller to achieve simulated formation flight with formation reconfiguration and real-time controller tuning functions, implement the control system on actual UAV platforms and demonstrate the control strategy and various formation scenarios in practical flight tests. Research combines analysis on flight control stabilities, develop- ment of a low-cost UAV testbed, mission planning and trajectory tracking, multiple sensor fusion research for UAV attitude estimations, low-cost inertial measurement unit (IMU) evaluation studies, AggieAir remote sensing platform and fail-safe feature development, al- titude controller design for vertical take-off and landing (VTOL) aircraft, and calibration and implementation of an air pressure sensor for wind profiling purposes on the developed multi-UAV platform. Definitions of the research topics and the plans are also addressed.

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A dissertation submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Master of Science in Engineering. Johannesburg, April 2016 / A Rotary Wing Unmanned Aerial Vehicle (RW UAV) as a platform and its payload consisting of sophisticated sensors would be costly items. Hence, a RW UAV in the 500 kg class designed to fulfil a number of missions would represent a considerable capital outlay for any customer. Therefore, in the event of an engine failure, a means should be provided to get the craft safely back on the ground without incurring damage or causing danger to the surrounding area. The aim of the study was to design a controller for autorotative landing of a RW UAV in the event of engine failure. In order to design a controller for autorotative landing, an acceleration model was used obtained from a study by Stanford University. FLTSIM helicopter flight simulation package yielded necessary RW UAV response data for the autorotation regimes. The response data was utilized in identifying the unknown parameters in the acceleration model. A Differential Dynamic Programming (DDP) control algorithm was designed to compute the main and tail rotor collective pitch and the longitudinal and lateral cyclic pitch control inputs to safely land the craft. The results obtained were compared to the FLTSIM flight simulation response data. It was noted that the mathematical model could not accurately model the pitch dynamics. The main rotor dynamics were modelled satisfactorily and which are important in autorotation because without power from the engine, the energy in main rotor is critical in a successful execution of an autorotative landing. Stanford University designed a controller for RC helicopter, XCell Tempest, which was deemed successful. However, the DDP controller was designed for autonomous autorotative landing of RW UAV weighing 560 kg, following engine failure. The DDP controller has the ability to control the RW UAV in an autorotation landing but the study should be taken further to improve certain aspects such as the pitch dynamics and which can possibly be achieved through online parameter estimation. / MT 2017

<p>The dissertation research was conducted to examine articles, research, and studies that have been collected in recent years to understand energy management for general aviation airplane pilots. The experiment was broken down into four phases with control and treatment groups which have evaluated the real-world problem of energy management in aviation. The four phases were to fly a flight profile, evaluate the energy state of the airplane within the flight by video, fly the same flight profile again, and a post-flight interview with the pilots. The idea of this experiment was to recognize the lack of understanding in energy management in pilots, build a conceptual model, and lastly verify and validate Phase II of the model by utilizing previous studies and research. Additionally, the three main goals were to assess the ability to interpret energy management, assess the ability to control the aircraft, and lastly, to interview for perception of energy management. The data was collected on the flight training device’s G1000, and the researcher analyzed the data using R, Minitab, Excel, and NVivo. The research provided ideas for creating a future model to evaluate energy management, validated by testing Phase II of the model to understand assessing energy management in real time, and interviewed pilots on their experiences with energy management, identified gaps in general aviation research, and suggested methods of how to facilitate understanding of energy management.</p>

<p>Current indirect optimal control problem (IOCP) solvers, like beluga or PINs, use symbolic math to derive the necessary conditions to solve the IOCP. This limits the capability of IOCP solvers by only admitting symbolically representable functions. The purpose of this thesis is to present a framework that extends those solvers to derive the necessary conditions of an IOCP with fully numeric methods. With fully numeric methods, additional types of functions, including conditional logic functions and look-up tables can now be easily used in the IOCP solver.</p> <p><br></p> <p>This aim was achieved by implementing algorithmic differentiation (AD) as a method to derive the IOCP necessary conditions into a new solver called Giuseppe. The Brachistochrone problem was derived analytically and compared Giuseppe to validate the automatic derivation of necessary conditions. Two additional problems are compared and extended using this new solver. The first problem, the maximum cross-range problem, demonstrates a trajectory can be optimized indirectly while utilizing a conditional density function that switches as a function of height according to the 1976 U.S. atmosphere model. The second problem, the minimum time to climb problem, demonstrates a trajectory can be optimized indirectly while utilizing 6 interpolated look up tables for lift, drag, thrust, and atmospheric conditions. The AD method yields the exact same precision as the symbolic methods, rather than introducing numeric error as finite difference derivatives would with the benefit of admitting conditional switching functions and look-up tables. </p>

<p dir="ltr">The electrification of pneumatic or hydraulic system on aircraft has been shown effective in reducing the fuel burn. Recently, electrifying propulsive loads has attracted a lot of atten- tion to further improve fuel economy. This work focuses on tools to facilitate more electric aircraft at conceptual design stage, particularly assuming a turbo-generator architecture. Specifically, we develop a simulation tool, mimicking SUAVE [1], which allows mission and fuel burn analysis. Major differences from SUAVE include more detailed models of compo- nents in the electric propulsive branch and degrees of freedom to adjust the velocity profile along the entire mission. Based on the simulator, this work further proposes to leverage a gradient-free optimization technique, which optimizes the optimal velocity profile along the entire mission to minimize fuel burn. Simulation results on two aircraft designs, a con- ventional Boeing 737-800 and NASA-STARC-ABL, verify the effectiveness of the proposed tools.</p>