Application of recently developed neural network based adaptive output feedback controllers to a diverse range of problems both in simulations and experiments is investigated in this thesis. The purpose is to evaluate the theory behind the development of these controllers numerically and experimentally, identify the needs for further development in practical applications, and to conduct further research in directions that are identified to ultimately enhance applicability of adaptive controllers to real world problems. We mainly focus our attention on adaptive controllers that augment existing fixed gain controllers. A recently developed approach holds great potential for successful implementations on real world applications due to its applicability to systems with minimal information concerning the plant model and the existing controller. In this thesis the formulation is extended to the multi-input multi-output case for distributed control of interconnected systems and successfully tested on a formation flight wind tunnel experiment. The command hedging method is formulated for the approach to further broaden the class of systems it can address by including systems with input nonlinearities. Also a formulation is adopted that allows the approach to be applied to non-minimum phase systems for which non-minimum phase characteristics are modeled with sufficient accuracy and treated properly in the design of the existing controller. It is shown that the approach can also be applied to augment nonlinear controllers under certain conditions and an example is presented where the nonlinear guidance law of a spinning projectile is augmented. Simulation results on a high fidelity 6 degrees-of-freedom nonlinear simulation code are presented. The thesis also presents a preliminary adaptive controller design for closed loop flight control with active flow actuators. Behavior of such actuators in dynamic flight conditions is not known. To test the adaptive controller design in simulation, a fictitious actuator model is developed that fits experimentally observed characteristics of flow control actuators in static flight conditions as well as possible coupling effects between actuation, the dynamics of flow field, and the rigid body dynamics of the vehicle.

The study of satellite relative motion has been of great historic interest, primarily due to its application to rendezvous, intercept, and docking maneuvers, between spacecraft in orbit about gravitational bodies, such as the Earth. Recent interest in the problem of satellite formation flight has also led to renewed effort in understanding the dynamics of relative motion. Satellite formations have been proposed for various tasks, such as deep-space interferometry, and terrestrial observation, among others. Oftentimes, the rich natural dynamics of the relative motion problem near a gravitational body are exploited to design formations of a specific geometry. Traditional analysis models relative motion under the assumptions of a circular reference orbit, linearized differential gravity field (small relative distance), and without environmental perturbations such as oblateness effects of the attracting body, and atmospheric drag. In this dissertation, the dynamics of the relative motion problem are studied when these assumptions are relaxed collectively. Consequently, the combined effects of nonlinearity, eccentricity, and Earth oblateness effects on relative motion, are studied. To this end, coupling effects between the various environmental perturbations are also accounted for. Five key problems are addressed - the development of a state transition matrix that accounts for eccentricity, nonlinearity, and oblateness effects; oblateness effects on averaged relative motion; eccentricity effects on formation design and planning; new analytical expressions for periodic relative motion that account for nonlinearity and eccentricity effects; and a solution to the optimal rendezvous problem near an eccentric orbit. The most notable feature of this dissertation, is that the solutions to the stated problems are completely analytical, and closed-form in nature. Use has been made of a generalized reversion of vector series, and several integral forms of Kepler’s equations, without any assumptions on the magnitude of the eccentricity of the reference orbit.

The classic minimum induced drag spanload is not necessarily the best choice for an aircraft. For a single aircraft configuration, variations from the elliptic, minimum drag optimum load distribution can produce wing weight savings that result in airplane performance benefits. For a group of aircraft flying in formation, non-elliptic lift distributions can give high induced drag reductions both for the formation and for each airplane. For single aircraft, a discrete vortex method which performs the calculations in the Trefftz plane has been used to calculate optimum spanloads for non-coplanar multi-surface configurations. The method includes constraints for lift coefficient, pitching moment coefficient and wing root bending moment. This wing structural constraint has been introduced such that wing geometry is not changed but the modified load distributions can be related to wing weight. Changes in wing induced drag and weight were converted to aircraft total gross weight and fuel weight benefits, so that optimum spanloads that give maximum take-off gross weight reductions can be found. Results show that a reduction in root bending moment from a lift distribution that gives minimum induced drag leads to more triangular spanloads, where the loads are shifted towards the root, reducing wing weight and increasing induced drag. A slight reduction in root bending moment is always beneficial, since the initial increase in induced drag is very small compared to the wing weight decrease. Total weight benefits were studied for a Boeing 777-200IGW type configuration, obtaining take-off gross weight improvements of about 1% for maximum range missions. When performing economical, reduced-range missions, improvements can almost double. A long range, more aerodynamically driven aircraft like the Boeing 777-200IGW will experience lower benefits as a result of increasing drag. Short to medium range aircraft will profit the most from more triangular lift distributions. Formation flight configurations can also result in large induced drag reductions for load distributions that deviate from the elliptical one. Optimum spanloads for a group of aircraft flying in an arrow formation were studied using the same discrete vortex method, now under constraints in lift, pitching moment and rolling moment coefficients. It has been shown that large general improvements in induced drag can be obtained when the spanwise and vertical distances between aircraft are small. In certain cases, using our potential flow vortex model, this results in negative (thrust) induced drag on some airplanes in the configuration. The optimum load distributions necessary to achieve these benefits may, however, correspond to a geometry that will produce impractical lift distributions if the aircraft are flying alone. Optimum separation among airplanes in this type of formation is determined by such diverse factors as the ability to generate the required optimum load distributions or the need for collision avoidance. / Master of Science

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As Unmanned Aerial Vehicles (UAVs) are integrated into the national airspace to comply with the 2012 Federal Aviation Administration Reauthorization Act, new civilian uses for robotic aircraft will come about in addition to the more obvious military applications. One particular area of interest for UAV development is the autonomous cooperative control of multiple UAVs. In this thesis, a decentralized leader-follower control strategy is designed, implemented, and tested from the follower’s perspective using vision-based localization. The tasks of localization and control were carried out with separate processing hardware dedicated to each task. First, software was written to estimate the relative state of a lead UAV in real-time from video captured by a camera on-board the following UAV. The software, written using OpenCV computer vision libraries and executed on an embedded single-board computer, uses the Efficient Perspective-n-Point algorithm to compute the 3-D pose from a set of 2-D image points. High-intensity, red, light emitting diodes (LEDs) were affixed to specific locations on the lead aircraft’s airframe to simplify the task if extracting the 2-D image points from video. Next, the following vehicle was controlled by modifying a commercially available, open source, waypoint-guided autopilot to navigate using the relative state vector provided by the vision software. A custom Hardware-In-Loop (HIL) simulation station was set up and used to derive the required localization update rate for various flight patterns and levels of atmospheric turbulence. HIL simulation showed that it should be possible to maintain formation, with a vehicle separation of 50 ± 6 feet and localization estimates updated at 10 Hz, for a range of flight conditions. Finally, the system was implemented into low-cost remote controlled aircraft and flight tested to demonstrate formation convergence to 65.5 ± 15 feet of separation.

The control of multiple unmanned aerial vehicles (UAVs) in a swarm or cooperative team scenario has been a topic of great interest for well over a decade, growing steadily with the advancements in UAV technologies. In the academic community, a majority of the studies conducted rely on simulation to test developed control strategies, with only a few institutions known to have nurtured the infrastructure required to propel multiple UAV control studies beyond simulation and into experimental testing. With the Cal Poly UAV FLOC Project, such an infrastructure was created, paving the way for future experimentation with multiple UAV control systems. The control system architecture presented was built on concepts developed in previous work by Cal Poly faculty and graduate students. An outer-loop formation flight controller based on a virtual waypoint implementation of potential function guidance was developed for use on an embedded microcontroller. A commercially-available autopilot system, designed for fully autonomous waypoint navigation utilizing low cost hardware and open source software, was modified to include the formation flight controller and an inter-UAV communication network. A hardware-in-the-loop (HIL) simulation was set up for multiple UAV testing and was utilized to verify the functionality of the modified autopilot system. HIL simulation results demonstrated leader-follower formation convergence to 15 meters as well as formation flight with three UAVs. Several sets of flight tests were conducted, demonstrating a successful leader-follower formation, but with relative distance convergence only reaching a steady state value of approximately 35 +/- 5 meters away from the leader.

Benefits of developing missions with multiple formation flying spacecraft as an alternative to a traditional monolithic vehicle are becoming apparent. In some cases, these missions can lower cost and increase flexibility among other situational advantages. However, there are various limitations that are imposed by these missions that are centered on the concept of maintaining the necessary formation. One such limitation is that of the propulsion system required for each spacecraft. To mitigate the complexity and mass of the onboard propulsion, the pairing of electromagnetic actuators and differential drag to replace the functionality of a propulsive system is investigated. By using COTS magnetorquer boards to command satellite orientation, a scenario in which two 3U CubeSats are initially deployed from the ISS NanoRacks at an altitude of 400 km. They are then commanded to achieve a relative separation of 1 km and hold the spacing to demonstrate the capability of formation flight. The scenario was simulated through the MATLAB/Simulink platform and the magnitude of the necessary command torques were determined. By comparison to the ISIS magnetorquer board, the necessary command torques seem relatively high than compared to what the actuator is capable of. The ISIS board may supply ~5e-6 Nm of torque while the mission requires as much as 3e-3 Nm at times. However, by extending the settling time of the control law at the expense of absolute orientation control, the control torques necessary to carry out the simulated mission are well within the bounds of the ISIS magnetorquer boards as well as other COTS boards. With this alteration, mission feasibility is determined. It should be noted that further analysis should be conducted regarding concerns with CubeSat detumble to further confirm feasibility.

This thesis presents a comprehensive framework and a study for trajectory optimization based on the patterned formation flying of the aircraft system as well as the maneuvers for deforming the configured and aligned aerial vehicles with safe mode criteria considerations while subjected to typical environmental requirements of aerial-flying zones. The elementary trajectory problem of a simple dynamical point-mass system of the aircraft is mathematically formulated and converted into a simulation version of mathematical programming as finite horizon planning and fixed arrival time planning strategies as an optimization problem. The methodology of the designed framework is mainly concerned with the safer path planning of the aircraft system with testing on all the probable feasibility and safety constraints to incorporate into a mathematical programming design of a collision-free and optimal trajectory characterization. The imperative notion is to create a configurational pattern of the aircraft system based on their creation of wingtip vortices. Flying the aircraft in formation lessen the fuel consumption as well as increase the time efficiency. The aircraft formation is arranged and optimized for safe trajectories during flight operations and for reduction of the carbon footprint of the whole system. Furthermore, deformation maneuvers are incorporated to complete the aircraft planning system by allowing the possibility of safely disassembling the formation for emergency breakout and exit sequences.

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.

In recent years, the interest in flying multiple Unmanned Aerial Vehicles (UAVs) in formation has increased. One challenging aspect of achieving this is the relative positioning within the swarm. This thesis evaluates two different methods for estimating the relative position and orientation between two fixed wing UAVs by fusing range measurements from Ultra-wideband (UWB) sensors and orientation estimates from Inertial Measurement Units (IMUs). To investigate the problem of estimating the relative position and orientation using range measurements, the performance of the UWB nodes regarding the accuracy of the measurements is evaluated. The resulting information is then used to develop a simulation environment where two fixed wing UAVs fly in formation. In this environment, the two estimation solutions are developed. The first solution to the estimation problem is based on the Extended Kalman Filter (EKF) and the second solution is based on Factor Graph Optimization (FGO). In addition to evaluating these methods, two additional areas of interest are investigated: the impact of varying the placement and number of UWB sensors, and if using additional sensors can lead to an increased accuracy of the estimates. To evaluate the EKF and the FGO solutions, multiple scenarios are simulated at different distances, with different amounts of changes in the relative position, and with different accuracies of the range measurements. The results from the simulations show that both solutions successfully estimate the relative position and orientation. The FGO-based solution performs better at estimating the relative position, while both algorithms perform similarly when estimating the relative orientation. However, both algorithms perform worse when exposed to more realistic range measurements. The thesis concludes that both solutions work well in simulation, where the Root Mean Square Error (RMSE) of the position estimates are 0.428 m and 0.275 m for the EKF and FGO solutions, respectively, and the RMSE of the orientation estimates are 0.016 radians and 0.013 radians respectively. However, to perform well on hardware, the accuracy of the UWB measurements must be increased. It is also concluded that by adding more sensors and by placing multiple UWB sensors on each UAV, the accuracy of the estimates can be improved. In simulation, the lowest RMSE is achieved by fusing barometer data from both UAVs in the FGO algorithm, resulting in an RMSE of 0.229 m for the estimated relative position.