Model-based Design Development and Control of a Wind Resistant Multirotor UAV

Multirotor UAVs have in recent years become a trend among academics, engineers and hobbyists alike due to their mechanical simplicity and availability. Commercial uses range from surveillance to recreational flight with plenty of research being conducted in regards to design and control. With applications towards search and rescue missions in mind, the main objective of this thesis work is the development of a mechanical design and control algorithm aimed at maximizing wind resistance. To these ends, an advanced multirotor simulator, based on helicopter theory, has been developed to give an accurate description of the flight dynamics. Controllers are then designed and tuned to stabilize the attitude and position of the UAV followed by a discussion regarding disturbance attenuation. In order to study the impact of different design setups, the UAV model is constructed so that physical properties can be scaled. Parameter influence is then investigated for a specified wind test using a Design of Experiments methodology. These results are combined with a concept generation process and evaluated with a control engineering approach. It was concluded that the proposed final design should incorporate a compact three-armed airframe with six rotors configured coaxially

Effect of rotor tilt on the gust rejection properties of multirotor aircraft

In order to operate safely in windy and gusty conditions, multirotor VTOL aircraft require gust resilience. This paper shows that their gust rejection properties can be improved by applying a small amount of fixed outward rotor tilt. Standard aerodynamic models of the rotors are incorporated into two dynamic models to assess the gust rejection properties. The first case is a conceptual birotor planar VTOL aircraft. The dependence of the trim and stability on the tilt angle are analyzed. The aircraft is stabilized using a pole-placement approach in order to obtain consistent closed-loop station-keeping performance in still air. The effect of gusts on the resulting response is determined by simulation. The second case study is for a quadrotor with a 10∘" role="presentation" style="max-height: none; display: inline; line-height: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; min-width: 0px; min-height: 0px; border-width: 0px; border-style: initial; position: relative;">10∘ outward rotor tilt. The aerodynamic coefficients are analyzed for trimmed station-keeping over a range of steady wind speeds. An LQR controller is used to apply station-keeping that includes integral action, and the gust responses are again obtained using simulation. The results show that the outward rotor tilt causes the aircraft to pitch down into a lateral gust, providing lateral force that opposes the gust and so significantly improving the gust rejection properties

Outdoor operations of multiple quadrotors in windy environment

Coordinated multiple small unmanned aerial vehicles (sUAVs) offer several advantages over a single sUAV platform. These advantages include improved task efficiency, reduced task completion time, improved fault tolerance, and higher task flexibility. However, their deployment in an outdoor environment is challenging due to the presence of wind gusts. The coordinated motion of a multi-sUAV system in the presence of wind disturbances is a challenging problem when considering collision avoidance (safety), scalability, and communication connectivity. Performing wind-agnostic motion planning for sUAVs may produce a sizeable cross-track error if the wind on the planned route leads to actuator saturation. In a multi-sUAV system, each sUAV has to locally counter the wind disturbance while maintaining the safety of the system. Such continuous manipulation of the control effort for multiple sUAVs under uncertain environmental conditions is computationally taxing and can lead to reduced efficiency and safety concerns. Additionally, modern day sUAV systems are susceptible to cyberattacks due to their use of commercial wireless communication infrastructure. This dissertation aims to address these multi-faceted challenges related to the operation of outdoor rotor-based multi-sUAV systems. A comprehensive review of four representative techniques to measure and estimate wind speed and direction using rotor-based sUAVs is discussed. After developing a clear understanding of the role wind gusts play in quadrotor motion, two decentralized motion planners for a multi-quadrotor system are implemented and experimentally evaluated in the presence of wind disturbances. The first planner is rooted in the reinforcement learning (RL) technique of state-action-reward-state-action (SARSA) to provide generalized path plans in the presence of wind disturbances. While this planner provides feasible trajectories for the quadrotors, it does not provide guarantees of collision avoidance. The second planner implements a receding horizon (RH) mixed-integer nonlinear programming (MINLP) model that is integrated with control barrier functions (CBFs) to guarantee collision-free transit of the multiple quadrotors in the presence of wind disturbances. Finally, a novel communication protocol using Ethereum blockchain-based smart contracts is presented to address the challenge of secure wireless communication. The U.S. sUAV market is expected to be worth $92 Billion by 2030. The Association for Unmanned Vehicle Systems International (AUVSI) noted in its seminal economic report that UAVs would be responsible for creating 100,000 jobs by 2025 in the U.S. The rapid proliferation of drone technology in various applications has led to an increasing need for professionals skilled in sUAV piloting, designing, fabricating, repairing, and programming. Engineering educators have recognized this demand for certified sUAV professionals. This dissertation aims to address this growing sUAV-market need by evaluating two active learning-based instructional approaches designed for undergraduate sUAV education. The two approaches leverages the interactive-constructive-active-passive (ICAP) framework of engagement and explores the use of Competition based Learning (CBL) and Project based Learning (PBL). The CBL approach is implemented through a drone building and piloting competition that featured 97 students from undergraduate and graduate programs at NJIT. The competition focused on 1) drone assembly, testing, and validation using commercial off-the-shelf (COTS) parts, 2) simulation of drone flight missions, and 3) manual and semi-autonomous drone piloting were implemented. The effective student learning experience from this competition served as the basis of a new undergraduate course on drone science fundamentals at NJIT. This undergraduate course focused on the three foundational pillars of drone careers: 1) drone programming using Python, 2) designing and fabricating drones using Computer-Aided Design (CAD) and rapid prototyping, and 3) the US Federal Aviation Administration (FAA) Part 107 Commercial small Unmanned Aerial Vehicles (sUAVs) pilot test. Multiple assessment methods are applied to examine the students’ gains in sUAV skills and knowledge and student attitudes towards an active learning-based approach for sUAV education. The use of active learning techniques to address these challenges lead to meaningful student engagement and positive gains in the learning outcomes as indicated by quantitative and qualitative assessments

Proceedings of the International Micro Air Vehicles Conference and Flight Competition 2017 (IMAV 2017)

The IMAV 2017 conference has been held at ISAE-SUPAERO, Toulouse, France from Sept. 18 to Sept. 21, 2017. More than 250 participants coming from 30 different countries worldwide have presented their latest research activities in the field of drones. 38 papers have been presented during the conference including various topics such as Aerodynamics, Aeroacoustics, Propulsion, Autopilots, Sensors, Communication systems, Mission planning techniques, Artificial Intelligence, Human-machine cooperation as applied to drones

Force-Canceling Mixer Algorithm for Vehicles with Fully-Articulated Radially Symmetric Thruster Arrays

A new type of fully-holonomic aerial vehicle is identified and developed that can optionally utilize automatic cancellation of excessive thruster forces to maintain precise control despite little or no throttle authority. After defining the physical attributes of the new vehicle, a flight control mixer algorithm is defined and presented. This mixer is an input/output abstraction that grants a flight control system (or pilot) full authority of the vehicle\u27s position and orientation by means of an input translation vector and input torque vector. The mixer is shown to be general with respect to the number of thrusters in the system provided that they are distributed in a radially symmetric array. As the mixer is designed to operate independently of the chosen flight control system, it is completely agnostic to the type of control methodology implemented. Validation of both the vehicle\u27s holonomic capabilities and efficacy of the flight control mixing algorithm are provided by a custom MATLAB-based rigid body simulation environment

A hierarchical neuro-evolutionary approach to small quadrotor control

Quadrotors are unique among Micro Aerial Vehicles in providing excellent maneuverability (as opposed to winged flight),while maintaing a simple mechanical construction (as opposed to helicopters). This mechanical simplicity comes at a cost of increased controller complexity. Quadrotors are inherently unstable, in the sense that they are essentially unflyable by a human without stability assistance. Prior work has developed model-based controllers that successfully control quadrotors operating near hover conditions, but small quadrotor dynamics make such control more difficult. In this thesis,we present a hierarchical neuro-controller for small (0.5 kg) quadrotor control. The first stage of control aims to stabilize the craft and outputs rotor speeds based on a requested attitude (pitch, roll, yaw, and vertical velocity). This controller is developed in four parts around each of the variables, initially training them to achieve results similar to a PID controller. The four parts are then combined and the controller is trained further to increase robustness. The second stage of control aims to achieve a requested(x,y,z) position by providing the first stage with the appropriate attitude. The simulation results show that stable quadrotor control is achieved through this control architecture. In addition, the results show that the hierarchical control approach recovers from discrete angle disturbances over an order of magnitude faster than a basic PID controller, and can even recover from a disturbance that knocks the craft upside down. Finally, using the average volume used to maintain a stable hover, we show that the hierarchical controller provides stable flight in the presence of 5 times more sensor noise and 8 times more actuator noise as compared to the PID controller

Physics-Based Modeling for Control and Autonomous Operation of Unmanned Aerial Vehicles

UAS are widely employed in commercial and military applications, and their utilization is growing at a rapid pace. Effective predictive models for aeromechanics, body dynamics and control are critical in trajectory planning and optimization, autonomous operations, and decision-making. Aeromechanical and wind models that are currently used in the control and guidance of UAS are typically simplistic and often do not represent the essential physics to an adequate degree. Therefore, the performance and versatility of such vehicles may be limited in extreme flight conditions. At the other end of the spectrum, there exist high fidelity models that are computationally expensive, and thus not applicable in path planning, optimization, and onboard flight controllers. The major goal of this dissertation is to bridge the gap between physics-based models and onboard decision-making. Multi-disciplinary models of appropriate fidelity are developed and integrated into a comprehensive flight simulation software suite. These models are experimentally validated and utilized in trajectory planning, optimization, onboard control and autonomous flight. Studying the impact of models of different fidelity for the environment and the aerodynamics determines the impact of modeling uncertainty on system-level goals. A vortex-based model for lifting surfaces is developed, using which control surfaces and couplings therein can be efficiently represented. Using this model, the interaction of the propeller wake with a downstream wing is studied, and it is demonstrated these models are effective tools in predicting the propeller-induced span-wise loading. Such a model is beneficial for trajectory planning and optimization applications to improve flight stability and trajectory tracking. Next, a novel HBEM model is developed to predict rotor forces over a wide range of flight conditions. The HBEM model is self-contained and combines blade element theory, momentum theory and a linear inflow model to determine the {em unique} inflow that is {em consistent with all theories}. The model utilizes the blade geometry and the flight condition as inputs to determine the relationship between the forces/moments and the rotor RPM. A detailed set of wind tunnel experiments is conducted to validate the model across a very wide range of flight regimes. Further, a semi-empirical model for the RIPF is developed using experimental data. It is noted that these models can be executed in real-time which makes them useful for implementation in flight software. A custom quadrotor is built and equipped with an ultrasonic wind sensor and RPM sensors. The HBEM and RIPF models are embedded in quadrotor flight software, and it is illustrated these models are fully integrable and efficient enough to run on a typical onboard compute module. To evaluate the ability of these models to function in harsh environmental conditions, motion capture aided autonomous flight is realized in the presence of strong wind gusts generated by a large industrial fan. A feedforward controller is designed to incorporate physical insight into flight mechanics and to provide estimates of the state. Flight tests are conducted in and out of strong crosswind conditions to further show the impact of computationally efficient models that are capable of being executed onboard in real-time. It is shown that the wind sensing and physics-based models along with the feedforward controller improve trajectory tracking in extreme environmental conditions.PHDAerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169719/1/davoudi_1.pd

Design, construction and flight control of a quad tilt-wing unmanned aerial vehicle

Unmanned Aerial Vehicles (UAVs) are flying robots that are employed both in civilian and military applications with a steeply increasing trend. They are already used extensively in civilian applications such as law enforcement, earth surface mapping and surveillance in disasters, and in military missions such as surveillance, reconnaissance and target acquisition. As the demand on their utilization increases, novel designs with far more advances in autonomy, flight capabilities and payloads for carrying more complex and intelligent sensors are emerging. With these technological advances, people will find even newer operational fields for UAVs. This thesis work focuses on the design, construction and flight control of a novel UAV (SUAVI: Sabanci University Unmanned Aerial VehIcle). SUAVI is an electric powered compact size quad tilt-wing UAV, which is capable of vertical takeoff and landing (VTOL) like a helicopter, and flying horizontally like an airplane by tilting its wings. It carries onboard cameras for capturing images and broadcasting them via RF communication with the ground station. In the aerodynamic and mechanical design of SUAVI, flight duration, flight speed, size, power source and missions to be carried out are taken into account. The aerodynamic design is carried out by considering the maximization of the aerodynamic efficiency and the safe fiight characteristics. The components in the propulsion system are selected to optimize propulsion efficiency and fulfill the requirements of the control for a stable flight in the entire speed range. Simulation results obtained by ANSYS and NASA FoilSimII are evaluated and motor thrust tests are conducted during this optimization process. The power source is determined by taking the weight and flight duration into account. The wings and the fuselage are shaped iteratively in fluid flow simulations. Additionally, the verification of aerodynamic design and maneuverability are assessed in the wind tunnel tests on the half-body prototype. The mechanical structure is designed to be lightweight, strong and protective, and to allow easy assembly and disassembly of SUAVI for practical use. The safety factors in the mechanical system are determined using FEM analysis in ANSYS environment. Specimens of candidate composite skin materials are prepared and tested for lightness, strength and integrity in mechanical tests. The ready for flight prototype SUAVI is produced from the selected composite material. Dynamical model of SUAVI is obtained using Newton-Euler formulation. Aerodynamic disturbances such as wind gusts are modeled using the wellknown Dryden wind turbulence model. As the flight control system, a supervisory control architecture is implemented where a Gumstix microcomputer and several Atmega16 microcontrollers are used as the high-level and low- level controllers, respectively. Gumstix computer acts as a supervisor which orchestrates switching of low-level controllers into the system and is responsible for decision making, monitoring states of the vehicle and safety checks during the entire flight. It also generates attitude references for the low-level controllers using data from GPS or camera. Various analog and digital filters are implemented to smooth out noisy sensor measurements. Extended Kalman filter is utilized to obtain reliable orientation information by fusing data from low-cost MEMS inertial sensors such as gyros, accelerometers and the compass. PID controllers are implemented for both the high-level GPS based acceleration controller and the low-level altitude and attitude controllers. External disturbances are estimated and compensated by a disturbance observer. Real-time control software is developed for the whole fiight control system. SUAVI can operate in semi-autonomous mode by communicating with the ground station. A quadrotor test platform (SUQUAD: Sabanci University QUADrotor) is also produced and used for the initial performance tests of the fiight control system. After successful fiight tests on this platform, the control system is transferred to SUAVI. Performance of the flight control system is verified by numerous simulations and real flight experiments. VTOL and horizontal flights are successfully realized