This project is part of research funded by NASA Langley in field of Unmanned Aerial Vehicles (UAVs) and is based on past work conducted at Virginia Commonwealth University. Dr. Mark A. Motter of NASA Langley intends to use the new autopilot system to test aircraft with many control surfaces. The goal of this project is to port an existing UAV autopilot system that has more computing power than the previous generation system to allow for more advanced flight control algorithms.The steps taken to complete this project include choosing a new hardware platform, porting C flight control software from a MicroBlaze platform to a PowerPC platform, and developing FPGA based hardware to interface with external sensors. The Suzaku-V based system was shown to have much better computing performance than the previous system, and several successful test flights have proved the viability of the new autopilot system.

This work outlines a design for a small form-factor flight control system designed to fly in a wide variety of airframes. The system was designed with future expansion in mind while providing a complete, all-in-one solution to meet present needs. This system as presented meets most needs while remaining relatively low cost. It has a completely integrated IMU solution as well as on- board GPS. It is capable of basic waypoint navigation. This solution was testing using software and hardware-in-the-loop simulation which proved its functionality.

The performance of a quadrotor can be significantly disturbed in presence of wind. In this paper, a simple-to-implement attitude controller is proposed to render a robust and accurate trajectory tracking in presence of disturbance and model uncertainties. The attitude controller design is based on Quantitative Feedback Theory (QFT). A fuzzy logic controller is further employed to provide satisfactory position trajectory tracking for the quadrotor. The performances of the controllers, in terms of disturbance rejection and trajectory tracking are experimentally studied. Finally, a flight scenario is performed to compare the performances of the designed QFT-Fuzzy control scheme with the ArduCopter controller. / May 2016

by Chiu, Kit Chau. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (leaves 90-92). / Abstracts in English and Chinese. / ABSTRACT --- p.02 / 摘要 --- p.04 / ACKNOWLEDGEMENTS --- p.06 / TABLE OF CONTENTS --- p.07 / LIST OF FIGURES --- p.10 / LIST OF TABLES --- p.12 / Chapter 1 --- INTRODUCTION --- p.13 / Chapter 1.1 --- Application with formation flying --- p.14 / Chapter 1.2 --- Previous work --- p.16 / Chapter 1.3 --- The present work --- p.18 / Chapter 1.4 --- Thesis outline --- p.19 / Chapter 2 --- OPTIMIZATION IN DESIRED TRAJECTORY --- p.21 / Chapter 2.1 --- Problem formulation --- p.21 / Chapter 2.1.1 --- System model --- p.21 / Chapter 2.1.2 --- System constraints --- p.22 / Chapter 2.1.3 --- Cost function of the system --- p.23 / Chapter 2.2 --- Reformation as optimal control problem --- p.23 / Chapter 2.2.1 --- Polynomial form for input --- p.24 / Chapter 2.2.2 --- Problem simplification --- p.26 / Chapter 2.3 --- Numerical case studies --- p.27 / Chapter 2.3.1 --- Case study 2-1: Equal weightings in all units and directions --- p.27 / Chapter 2.3.2 --- Case study 2-2: Equal weightings in all directions but different weightings in control units --- p.30 / Chapter 2.3.3 --- Case 2-3: Different weightings in x-y-z directions but equal weightings in all control units --- p.33 / Chapter 2.4 --- Chapter summary --- p.35 / Chapter 3 --- OBSTACLE AVOIDANCE --- p.36 / Chapter 3.1 --- Additions of obstacle constraints --- p.36 / Chapter 3.2 --- Simulation case studies --- p.37 / Chapter 3.2.1 --- Case study 3-1: No obstacle --- p.38 / Chapter 3.2.2 --- Case study 3-2: Single obstacles --- p.40 / Chapter 3.2.3 --- Case study 3-3: Two obstacles --- p.42 / Chapter 3.2.4 --- Case study 3-4: Two obstacles and optimal velocity --- p.48 / Chapter 3.3 --- Chapter summary --- p.51 / Chapter 4 --- FUZZY INTERACTIVE FORCE BETWEEN ELEMENTS --- p.52 / Chapter 4.1 --- Region of repulsive force --- p.52 / Chapter 4.2 --- Region of attractive force --- p.53 / Chapter 4.3 --- Beyond the attractive region --- p.53 / Chapter 4.4 --- Interactive force as function of separation --- p.54 / Chapter 4.5 --- Fuzzy mapping --- p.55 / Chapter 4.6 --- Chapter summary --- p.58 / Chapter 5 --- VIRTUAL LEADER --- p.59 / Chapter 5.1 --- Virtual leader --- p.59 / Chapter 5.2 --- Two maneuverable elements and two virtual leaders --- p.60 / Chapter 5.3 --- Rotational Trajectories for the two virtual leaders --- p.61 / Chapter 5.4 --- Chapter summary --- p.65 / Chapter 6 --- OPIMIZATION BY INTERACTIVE FORCE --- p.66 / Chapter 6.1 --- Narrow channel passage --- p.66 / Chapter 6.2 --- Interactive forces --- p.68 / Chapter 6.3 --- Definition of interactive force --- p.69 / Chapter 6.4 --- Formulation as optimization problem --- p.71 / Chapter 6.4.1 --- Parameterization of f1 and f2 --- p.71 / Chapter 6.4.2 --- Reformulated optimization problem --- p.73 / Chapter 6.5 --- Simulation results --- p.74 / Chapter 6.6 --- Chapter summary --- p.77 / Chapter 7 --- MODIFICATION IN OBSTACLE --- p.78 / Chapter 7.1 --- Modification for interactive force --- p.78 / Chapter 7.2 --- Modification in obstacle description --- p.79 / Chapter 7.3 --- """Shortest distance"" between control unit and obstacle" --- p.80 / Chapter 7.4 --- Simulation case studies --- p.81 / Chapter 7.4.1 --- Case study 7-1: Single triangular obstacle --- p.81 / Chapter 7.4.2 --- Case study 7-2: Two triangular obstacles --- p.83 / Chapter 7.5 --- Chapter summary --- p.85 / Chapter 8 --- Conclusions and future works --- p.86 / Chapter 8.1 --- Conclusions --- p.86 / Chapter 8.2 --- Future works --- p.88 / Chapter 8.2.1 --- Fuzzy mapping --- p.88 / Chapter 8.2.2 --- Intrinsic parameters and properties --- p.89 / BIBLIOGRAPHY --- p.90

The thesis deals with the design and implementation of an Adaptive Flight Control technique for Unmanned Aerial Vehicles (UAVs). The application of UAVs has been increasing exponentially in the last decade both in Military and Civilian fronts. These UAVs fly at very low speeds and Reynolds numbers, have nonlinear coupling, and tend to exhibit time varying characteristics. In addition, due to the variety of missions, they fly in uncertain environments exposing themselves to unpredictable external disturbances. The successful completion of the UAV missions is largely dependent on the accuracy of the control provided by the flight controllers. Thus there is a necessity for accurate and robust flight controllers. These controllers should be able to adapt to the changes in the dynamics due to internal and external changes. From the available literature, it is known that, one of the better suited adaptive controllers is the model based controller. The design and implementation of model based adaptive controller is discussed in the thesis. A critical issue in the design and application of model based control is the online identification of the UAV dynamics from the available sensors using the onboard processing capability. For this, proper instrumentation in terms of sensors and avionics for two platforms developed at UNSW@ADFA is discussed. Using the flight data from the remotely flown platforms, state space identification and fuzzy identification are developed to mimic the UAV dynamics. Real time validations using Hardware in Loop (HIL) simulations show that both the methods are feasible for control. A finer comparison showed that the accuracy of identification using fuzzy systems is better than the state space technique. The flight tests with real time online identification confirmed the feasibility of fuzzy identification for intelligent control. Hence two adaptive controllers based on the fuzzy identification are developed. The first adaptive controller is a hybrid indirect adaptive controller that utilises the model sensitivity in addition to output error for adaptation. The feedback of the model sensitivity function to adapt the parameters of the controller is shown to have beneficial effects, both in terms of convergence and accuracy. HIL simulations applied to the control of roll stabilised pitch autopilot for a typical UAV demonstrate the improvements compared to the direct adaptive controller. Next a novel fuzzy model based inversion controller is presented. The analytical approximate inversion proposed in this thesis does not increase the computational effort. The comparisons of this controller with other controller for a benchmark problem are presented using numerical simulations. The results bring out the superiority of this technique over other techniques. The extension of the analytical inversion based controller for multiple input multiple output problem is presented for the design of roll stabilised pitch autopilot for a UAV. The results of the HIL simulations are discussed for a typical UAV. Finally, flight test results for angle of attack control of one of the UAV platforms at UNSW@ADFA are presented. The flight test results show that the adaptive controller is capable of controlling the UAV suitably in a real environment, demonstrating its robustness characteristics.

This thesis presents a damage-tolerant flight control system design for propulsion-controlled aircraft (PCA). PCA refers to an emergency piloting strategy that flight crews use throttle modulation only to achieve the attitude control of aircraft in case of conventional flight control system failures. PCA also refers to a conceptual or experimental aircraft that is installed with such automated thrust-only control system. When an aircraft undergoes structural damage to its airframe, lifting or control surfaces which cause conventional control system failures, PCA is adopted as an alternative control approach to stabilize the aircraft. However, the control of the damaged aircraft poses complications in stability recovering as unmodeled uncertainties and perturbed dynamics have significant impact on flight dynamics. Therefore, the PCA flight control system should have a high level of robustness against such model uncertainties, aerodynamics parameter deviations, and model perturbations. This thesis presents the study of robust PCA control system design using H infinity-based robust control method. The developed controllers are tested through both linear and nonlinear simulations. A comprehensive evaluation is performed for several different emergency scenarios. The results demonstrate the advantages of the newly-designed robust flight control architecture over the existing optimal controller in dealing with model deviations due to structural damage.

This thesis presents a damage-tolerant flight control system design for propulsion-controlled aircraft (PCA). PCA refers to an emergency piloting strategy that flight crews use throttle modulation only to achieve the attitude control of aircraft in case of conventional flight control system failures. PCA also refers to a conceptual or experimental aircraft that is installed with such automated thrust-only control system. When an aircraft undergoes structural damage to its airframe, lifting or control surfaces which cause conventional control system failures, PCA is adopted as an alternative control approach to stabilize the aircraft. However, the control of the damaged aircraft poses complications in stability recovering as unmodeled uncertainties and perturbed dynamics have significant impact on flight dynamics. Therefore, the PCA flight control system should have a high level of robustness against such model uncertainties, aerodynamics parameter deviations, and model perturbations. This thesis presents the study of robust PCA control system design using H infinity-based robust control method. The developed controllers are tested through both linear and nonlinear simulations. A comprehensive evaluation is performed for several different emergency scenarios. The results demonstrate the advantages of the newly-designed robust flight control architecture over the existing optimal controller in dealing with model deviations due to structural damage.

Research has presented several approaches to achieve varying degrees of fault-tolerance in unmanned aircraft. Approaches in reconfigurable flight control are generally divided into two categories: those which incorporate multiple non-adaptive controllers and switch between them based on the output of a fault detection and identification element and those that employ a single adaptive controller capable of compensating for a variety of fault modes. Regardless of the approach for reconfigurable flight control, certain fault modes dictate system restructuring in order to prevent a catastrophic failure. System restructuring enables active control of actuation not employed by the nominal system to recover controllability of the aircraft. After system restructuring, continued operation requires the generation of flight paths that adhere to an altered flight envelope. The control architecture developed in this research employs a multi-tiered hierarchy to allow unmanned aircraft to generate and track safe flight paths despite the occurrence of potentially catastrophic faults. The hierarchical architecture increases the level of autonomy of the system by integrating five functionalities with the baseline system: fault detection and identification, active system restructuring, reconfigurable flight control, reconfigurable path planning, and mission adaptation. Fault detection and identification algorithms continually monitor aircraft performance and issue fault declarations. When the severity of a fault exceeds the capability of the baseline flight controller, active system restructuring expands the controllability of the aircraft using unconventional control strategies not exploited by the baseline controller. Each of the reconfigurable flight controllers and the baseline controller employ a proven adaptive neural network control strategy. A reconfigurable path planner employs an adaptive model of the vehicle to re-shape the desired flight path. Generation of the revised flight path is posed as a linear program constrained by the response of the degraded system. Finally, a mission adaptation component estimates limitations on the closed-loop performance of the aircraft and adjusts the aircraft mission accordingly. A combination of simulation and flight test results using two unmanned helicopters validates the utility of the hierarchical architecture.

Thesis (Ph. D.)--West Virginia University, 2009. / Title from document title page. Document formatted into pages; contains xiv, 118 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 109-118).

Aircraft control mechanisms, such as those that operate the flaps, ailerons, rudders, etc., are almost exclusively driven by hydraulic-based systems. Their popularity in flight control systems is not unfounded; hydraulic actuators are quite torque-dense and benefit from decades of development bringing operating performance to a high level. On the other hand the infrastructure to support this system increases weight, adds system development complexity, and reduces aircraft maintainability [Jensen et al, 2000]. Based on recent Electro-Mechanical Actuator (EMA) development and design efforts at the Robotics Research Group (RRG), a new opportunity exists to replace current hydraulic flight control systems with those powered by electricity through a national program [Tesar, 2005]. A literature review of the topic found a 30 year old effort by AiResearch to develop a similarly powered hingeline actuator with given traditional performance goals (torque capacity, redundancy, output speed, reliability). In this report,a thorough analysis is performed on each major component group to quantitatively evaluate this baseline device. Using component technologies developed at RRG, this report proposes a dual torque-summing electromechanical actuator, each with a star compound / hypocyclic combined gear train, designed to exceed the performance of the original (1976) AiResearch project. This preliminary design exercise includes a layout of the entire actuator along with an appropriate analysis of major components including bearings, gear train, motor, housing, and release mechanism. The performance of this gear train is critical to overall actuator success and fundamental analytics have already been developed in this area [Park and Tesar, 2005]. Finite Element Analysis on the gear train and housing provide early design feedback and verification of actuator performance characteristics. In particular, simulation results show the gear stiffness, load sharing, and torque capacities exceed analytical estimates. Finally, four different comparisons are presented that evaluate configuration variations of the two designs based on applicable performance criteria. Results show the RRG fault-tolerant actuator has a marked improvement over the baseline in average stiffness (14.2x), reflected inertia (3.2x) and nominal torque density (3.4x). The chapter next lists actuator test methods and aircraft qualification standards. Finally, a summary of future work is detailed in a ten step outline to bring this EMA technology to a level of early deployment in a large range of aircraft systems.