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Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2010. / ENGLISH ABSTRACT: This thesis presents the development and implementation of a position based kinematic guidance system, the derivation and testing of a Dynamic Pursuit Navigation algorithm and a thorough analysis of an aircraft’s runway interactions, which is used to implement automated take-off of a fixed wing UAV. The analysis of the runway is focussed on the aircraft’s lateral modes. Undercarriage and aerodynamic effects are first analysed individually, after which the combined system is analysed. The various types of feedback control are investigated and the best solution suggested. Supporting controllers are designed and combined to successfully implement autonomous take-off, with acceleration based guidance. A computationally efficient position based kinematic guidance architecture is designed and implemented that allows a large percentage of the flight envelope to be utilised. An airspeed controller that allows for aggressive flight is designed and implemented by applying Feedback Linearisation techniques. A Dynamic Pursuit Navigation algorithm is derived that allows following of a moving ground based object at a constant distance (radius). This algorithm is implemented and verified through non-linear simulation. / AFRIKAANSE OPSOMMING: Hierdie tesis handel oor die ontwikkeling en toepassing van posisie-afhanklike, kinematiese leidings-algoritmes, die ontwikkeling van ’n Dinamiese Volgings-navigasie-algoritme en ’n deeglike analise van die interaksie van ’n lugraam met ’n aanloopbaan sodat outonome opstygprosedure van ’n vastevlerk vliegtuig bewerkstellig kan word. Die bogenoemde analise het gefokus op die laterale modus van ’n vastevlerk vliegtuig en is tweeledig behartig. Die eerste gedeelte het gefokus op die analise van die onderstel, terwyl die lugraam en die aerodinamiese effekte in die tweede gedeelte ondersoek is. Verskillende tipes terugvoerbeheer vir die outonome opstygprosedure is ondersoek om die mees geskikte tegniek te bepaal. Addisionele beheerders, wat deur die versnellingsbeheer gebaseerde opstygprosedure benodig word, is ontwerp. ’n Posisie gebaseerde kinematiese leidingsbeheerstruktuur om ’n groot persentasie van die vlugvermoë te benut, is ontwikkel. Terugvoer linearisering is toegepas om ’n lugspoedbeheerder , wat in staat is tot aggressiewe vlug, te ontwerp. ’n Dinamiese Volgingsnavigasie-algoritme wat in staat is om ’n bewegende grondvoorwerp te volg, is ontwikkel. Hierdie algoritme is geïmplementeer en bevestig deur nie-lineêre simulasie.

<p>A dual core Atmel DIOPSIS 940 chip consists of a DSP and an ARM9 functional units in a single silicon die. This thesis presents the process of integration and assessment of using this processor in a flight control system. A complete design of the system is provided including a description of the DIOPSIS 940 from the perspective of requirements of the application. The integration of the processor with a typical set of components of a flight control system is provided. Additionally, a suite of programs required for developing software for the system is included. Capabilities of both cores of the processor are analysed in a series of experiments. Computational performance in typical tasks of a flight control system is analyzed and compared. The application of attitude stabilization for a micro-scale UAS is described.</p>

Commercial Aircraft Corporation of China, Ltd (COMAC)and Chinese Scholarship Council. / The aim of this thesis is to develop a real time PIO detection and mitigation system that consists of a detector based on short time Fourier transform(STFT) and autoregressive model(ARX) with exogenous inputs, together with an adaptive controller based mitigation system. The system not only detects the traditional PIO characteristics but also focuses on the trend of pilot behaviour by calculating the rate of change in the open loop crossover frequency. In the detection system, a sliding windowed STFT method was applied to identify the frequency and phase characteristics of the system via processing the signal of pilot input and aircraft state. An ARX model was also applied to get the rate of change of the crossover frequency. After detection, a PIO cue was shown on the primary flight display. A scheduled gain controller was coupled to provide PIO mitigation by varying stick input gain. Compensatory and tracking tests for the evaluation of this system were performed using a quasi-linear Boeing-747 aircraft model including nonlinear command gearing and actuator rate-limiting. Bandwidth and Gibson criteria were used to design PIO prone control laws for system evaluation experiments. Results from PIO tests conducted on desktop PCs were presented. These were analyzed and compared with those obtained from implementing the Real-time Oscillation Verifier module available in literature.

This research work provides the development of an Adaptive Flight Control System (AFCS) for autonomous hover of a Rotary-wing Unmanned Aerial Vehicle (RUAV). Due to the complex, nonlinear and time-varying dynamics of the RUAV, indirect adaptive control using the Model Predictive Control (MPC) is utilised. The performance of the MPC mainly depends on the model of the RUAV used for predicting the future behaviour. Due to the complexities associated with the RUAV dynamics, a neural network based black box identification technique is used for modelling the behaviour of the RUAV. Auto-regressive neural network architecture is developed for offline and online modelling purposes. A hybrid modelling technique that exploits the advantages of both the offline and the online models is proposed. In the hybrid modelling technique, the predictions from the offline trained model are corrected by using the error predictions from the online model at every sample time. To reduce the computational time for training the neural networks, a principal component analysis based algorithm that reduces the dimension of the input training data is also proposed. This approach is shown to reduce the computational time significantly. These identification techniques are validated in numerical simulations before flight testing in the Eagle and RMAX helicopter platforms. Using the successfully validated models of the RUAVs, Neural Network based Model Predictive Controller (NN-MPC) is developed taking into account the non-linearity of the RUAVs and constraints into consideration. The parameters of the MPC are chosen to satisfy the performance requirements imposed on the flight controller. The optimisation problem is solved numerically using nonlinear optimisation techniques. The performance of the controller is extensively validated using numerical simulation models before flight testing. The effects of actuator and sensor delays and noises along with the wind gusts are taken into account during these numerical simulations. In addition, the robustness of the controller is validated numerically for possible parameter variations. The numerical simulation results are compared with a base-line PID controller. Finally, the NN-MPCs are flight tested for height control and autonomous hover. For these, SISO as well as multiple SISO controllers are used. The flight tests are conducted in varying weather conditions to validate the utility of the control technique. The NN-MPC in conjunction with the proposed hybrid modelling technique is shown to handle additional disturbances successfully. Extensive flight test results provide justification for the use of the NN-MPC technique as a reliable technique for control of non-linear complex dynamic systems such as RUAVs.

This thesis deals with the design and development of a 75 mm fixed-wing nano-air vehicle (NAV). The NAV is designed to fit inside a cube with each side measuring 75 mm. The range and endurance of the NAV are 300 m and 2-3 minutes, respectively. The high-wing horizontal tailless NAV has a take-off weight of 19.5 g. The battery-powered single propeller NAV has two control surfaces in the form of elevator and rudder. This thesis contains a detailed account of the airfoil selection, selection of the configuration of NAV and the longitudinal, lateral and directional aerodynamic characterization of the NAV. The development of one of the lightweight autopilot hardware which weighs 1.8 g is also given in detail. The development of non-linear equations of motion of NAV including thrust and coupling effects is also discussed. The effects of the gyroscopic coupling and counter torque on the linear dynamics of the NAV are analyzed by conducting a parametric study about the variation of the eigenstructure attributable to the varying degree of coupling in the system matrix of the linear coupled model. A robust simultaneously stabilizing output feedback controller is synthesized for stabilizing the plants of the NAV. The synthesizing of the robust simultaneously stabilizing output feedback controller is based on a frequency-shaped central plant. A new procedure is developed to determine the frequency-shaped central plant utilizing the v-gap metric between the plants, the frequency-shaping of the plants with the pre and post compensators and the robust stabilization theory. An optimization problem is formulated to obtain these compensators. A novel iterative algorithm is developed to acquire the compensators by solving the optimization problem. Thereafter, an iterative algorithm is developed to find an output feedback controller for robust simultaneous stabilization by blending the existing features of robust stability condition of right co-prime uncertainty model of the frequency-shaped central plant, the maximum v-gap metric of the frequency-shaped central plant, H∞ loop-shaping and eigenstructure assignment algorithm for output feedback using the genetic algorithm. The six-degree-of-freedom numerical and hardware-in-loop simulations (HILS) of closed-loop non-linear and linear plants of NAV are performed to assess the performance of the controller and to validate the control algorithm implemented in the autopilot. The airworthiness of the aircraft is tested by conducting flight trials in radio-controlled (RC) mode without including the autopilot. The successful RC flight trial of the NAV indicates airworthiness of the aircraft which aided in freezing the configuration. This is one of the smallest fixed wing aerial vehicle that was successfully flown till date.

Le travail de recherche effectué dans cette thèse a été réalisé dans le cadre d'une convention CIFRE entre le laboratoire IMS de l'université Bordeaux 1 et la société Airbus Operations S.A.S. Cette thèse traite de la détection robuste et précoce des pannes oscillatoires de faible amplitude dans les systèmes de commandes de vol électriques. Une panne oscillatoire est une oscillation anormale d'une surface de contrôle due à un dysfonctionnement dans la chaîne d'asservissement de la servocommande d'une gouverne. Les pannes oscillatoires ont une influence sur la structure, l'aéroélasticité et la pilotabilité de l'avion, lorsqu'ils sont situés dans la bande passante de l'actionneur. La capacité à détecter ces pannes est très importante car elles ont un impact sur la conception structurale de l'avion. Au plan méthodologique, nous nous sommes focalisés sur l'estimation adaptative des paramètres et de l'état à base d'une technique de filtrage non linéaire local. Le mécanisme de filtrage opère sur un modèle non linaire de la chaine de contrôle-commande de l’actionneur hydraulique en amont des surfaces de contrôle. L'algorithme d'estimation est basé sur une interpolation polynomiale d'opérateurs linéaire, et offre l'avantage d'une implémentation relativement aisée. Un problème crucial et sous-jacent est la détermination des hyper-paramètres de réglage de cet algorithme. Nous avons proposé une démarche hors-ligne dédiée, en intégrant un critère de sensibilité vis-à-vis des pannes que nous devons détecter. La technique proposée a été implémentée et testée: les résultats expérimentaux obtenus sur banc essai et sur un simulateur A380 ont clairement mis en évidence l'apport de la nouvelle approche en termes de performances, tout en gardant le même niveau de robustesse. / The research work done in this PhD has been caried out in the frame of an industrial convention (CIFRE) between the IMS laboratory and Airbus Operations S.A.S. The thesis deals with robust and early detection of oscillatory failures (OFC: Oscillatory Failure Case) in the Electrical Flight Control System. An oscillatory failure is an abnormal oscillation of a control surface due to component malfunction in control surface servoloops. OFCs have an influence on structural loads, aeroelasticity and controllability when located within the actuator bandwidth. The ability to detect these failures is very important because they have an impact on the structural design of the aircraft. Usual monitoring techniques cannot always guarantee to remain within an envelope with acceptable robustness. In this work, we develop a model based strategy to detect such failures with small amplitude at a very early stage. The monitoring strategy is based on dedicated non linear local filtering for on-line joint parameter/state estimation, allowing for model parameter variations during A/C flight. This strategy is associated with the same decision making rules as currently used for in-service Airbus A380. We propose a method for adjusting the tuning parameters so that various design goals and trades-off can be easily formulated and managed. The performance of the proposed fault detection scheme is measured by its detection delay, its propensity to issue false alarms and whether it permits a failure to go undetected. The proposed technique has been implemented and tested with success on Airbus test facilities including an A380 flight simulator.

This master thesis is focused on design of control stick grip and rudder pedals extension. These components are equipped with active elements, which provide pilot with haptic feedback. The purpose of the introduced design is to allow prototype to be built into the aeroplane so that the proposed concept of haptic feedback can be tested onboard. It shall verify used technical solutions as well to allow for their application on following development stages that aim at certification of the proposed haptic feedback system to be used in general aviation aeroplanes. The designed components are the successors of prototypes used for experiments carried on flight simulator. The design process follows the requirements of legislation and outcomes of the previous experiments. This thesis follows the design process from setting of the design requirements to mechanical test of 3D printed prototypes.

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A dual core Atmel DIOPSIS 940 chip consists of a DSP and an ARM9 functional units in a single silicon die. This thesis presents the process of integration and assessment of using this processor in a flight control system. A complete design of the system is provided including a description of the DIOPSIS 940 from the perspective of requirements of the application. The integration of the processor with a typical set of components of a flight control system is provided. Additionally, a suite of programs required for developing software for the system is included. Capabilities of both cores of the processor are analysed in a series of experiments. Computational performance in typical tasks of a flight control system is analyzed and compared. The application of attitude stabilization for a micro-scale UAS is described.