GPS based position control and waypoint navigation of a quad tilt-wing UAV

Unmanned aerial vehicles (UAV) are becoming increasingly capable nowadays and the civilian applications and the military tasks that can be carried out by these vehicles are far more critical than before. There have been remarkable advances in the design and development of UAVs. They are equipped with various sensors which make them capable of accomplishing missions in unconstrained environments which are dangerous or effortful for manned aircrafts. Recently, significant interest in unmanned aerial vehicles has directed researchers towards navigation problem of flying vehicles. This thesis work focuses on GPS based position control and waypoint navigation of a quad tilt-wing unmanned aerial vehicle (SUAVI: Sabanci University Unmanned Aerial Vehicle). The vehicle is capable of vertical take-off and landing (VTOL). It can also fly horizontally due to its tilt-wing structure. Mechanical and aerodynamic designs are first outlined. A nonlinear mathematical model expressed in a hybrid frame is then obtained using Newton-Euler formulation which also includes aerodynamics effects such as wind and gusts. Extended Kalman filtering (EKF) using raw IMU measurements is employed to obtain reliable orientation estimates which is crucial for attitude stabilization of the aerial vehicle. A high-level acceleration controller which utilizes GPS data produces roll and pitch references for the low-level attitude controllers for hovering and trajectory tracking of the aerial vehicle. The nonlinear dynamic equations of the vehicle are linearized around nominal operating points in hovering conditions and gravity compensated PID controllers are designed for position and attitude control. Simulations and several real flight experiments demonstrate success of the developed position control algorithms

Adaptive and Optimal Motion Control of Multi-UAV Systems

This thesis studies trajectory tracking and coordination control problems for single and multi unmanned aerial vehicle (UAV) systems. These control problems are addressed for both quadrotor and fixed-wing UAV cases. Despite the fact that the literature has some approaches for both problems, most of the previous studies have implementation challenges on real-time systems. In this thesis, we use a hierarchical modular approach where the high-level coordination and formation control tasks are separated from low-level individual UAV motion control tasks. This separation helps efficient and systematic optimal control synthesis robust to effects of nonlinearities, uncertainties and external disturbances at both levels, independently. The modular two-level control structure is convenient in extending single-UAV motion control design to coordination control of multi-UAV systems. Therefore, we examine single quadrotor UAV trajectory tracking problems to develop advanced controllers compensating effects of nonlinearities and uncertainties, and improving robustness and optimality for tracking performance. At fi rst, a novel adaptive linear quadratic tracking (ALQT) scheme is developed for stabilization and optimal attitude control of the quadrotor UAV system. In the implementation, the proposed scheme is integrated with Kalman based reliable attitude estimators, which compensate measurement noises. Next, in order to guarantee prescribed transient and steady-state tracking performances, we have designed a novel backstepping based adaptive controller that is robust to effects of underactuated dynamics, nonlinearities and model uncertainties, e.g., inertial and rotational drag uncertainties. The tracking performance is guaranteed to utilize a prescribed performance bound (PPB) based error transformation. In the coordination control of multi-UAV systems, following the two-level control structure, at high-level, we design a distributed hierarchical (leader-follower) 3D formation control scheme. Then, the low-level control design is based on the optimal and adaptive control designs performed for each quadrotor UAV separately. As particular approaches, we design an adaptive mixing controller (AMC) to improve robustness to varying parametric uncertainties and an adaptive linear quadratic controller (ALQC). Lastly, for planar motion, especially for constant altitude flight of fixed-wing UAVs, in 2D, a distributed hierarchical (leader-follower) formation control scheme at the high-level and a linear quadratic tracking (LQT) scheme at the low-level are developed for tracking and formation control problems of the fixed-wing UAV systems to examine the non-holonomic motion case. The proposed control methods are tested via simulations and experiments on a multi-quadrotor UAV system testbed

Attitude Estimation of Quadcopter through Extended Kalman Filter

The aim of this paper is to estimate the attitude of the quadcopter using the sensors: 3-axesaccelerometer, 3-axes gyroscope, 2-axes compass.At first I introduce some basic conception of quadcopter, such as the three main factor: roll, pitch,yaw, and the coordinate system that are used to implement the next calculations. Then according tothe mathematical model, I simulated the quadcopter in Simulink. The sensors are also modeled usingthe real sensor measurements to correctly estimate the measurement noise.After finished the model, I gave it a step input and get the output from the scope. Then I add theGaussian noise on to it and use this as the input of Extended Kalman Filter. And compare somedifferent type of Kalman Filter to conclude that the EKF is the best strategy.Finally we can conclude that the standard extended Kalman filter is the best estimator. If allof the parameters can be set correctly, The EKF can have a better result. But since it is notimplement on the embedded system, it can be used only as a reference and provide satisfyingresult in most situations.Keywords: Quadcopter, Extended Kalman Filter, Eular angl

Robust hovering and trajectory tracking control of a quadrotor helicopter using acceleration feedback and a novel disturbance observer

Hovering and trajectory tracking control of rotary-wing aircrafts in the presence of uncertainties and external disturbances is a very challenging task. This thesis focuses on the development of the robust hovering and trajectory tracking control algorithms for a quadrotor helicopter subject to both periodic and aperiodic disturbances along with noise and parametric uncertainties. A hierarchical control structure is employed where high-level position controllers produce reference attitude angles for the low-level attitude controllers. Reference attitude angles are usually determined analytically from the position command signals that control the positional dynamics. However, such analytical formulas may produce large and non-smooth reference angles which must be saturated and low-pass filtered. In this thesis, desired attitude angles are determined numerically using constrained nonlinear optimization where certain magnitude and rate constraints are imposed. Furthermore, an acceleration based disturbance observer (AbDOB) is designed to estimate and suppress disturbances acting on the positional dynamics of the quadrotor. For the attitude control, a nested position, velocity, and inner acceleration feedback control structure consisting of PID and PI type controllers are developed to provide high sti ness against external disturbances. Reliable angular acceleration is estimated through an extended Kalman filter (EKF) cascaded with a classical Kalman lter (KF). This thesis also proposes a novel disturbance observer which consists of a bank of band-pass filters connected parallel to the low-pass filter of a classical disturbance observer. Band-pass filters are centered at integer multiples of the fundamental frequency of the periodic disturbance. Number and bandwidth of the band-pass filters are two crucial parameters to be tuned in the implementation of the new structure. Proposed disturbance observer is integrated with a sliding mode controller to tackle the robust hovering and trajectory tracking control problem. The sensitivity of the proposed disturbance observer based control system to the number and bandwidth of the band-pass filters are thoroughly investigated via several simulations. Simulations are carried out on a high delity model where sensor biases and measurement noise are also considered. Results show that the proposed controllers are very effective in providing robust hovering and trajectory tracking performance when the quadrotor helicopter is subject to the wind gusts generated by the Dryden wind model along with plant uncertainties and measurement noise. A comparison with the classical disturbance observer-based control is also provided where better tracking performance with improved robustness is achieved in the presence of noise and external disturbance

Validation and Experimental Testing of Observers for Robust GNSS-Aided Inertial Navigation

This chapter is the study of state estimators for robust navigation. Navigation of vehicles is a vast field with multiple decades of research. The main aim is to estimate position, linear velocity, and attitude (PVA) under all dynamics, motions, and conditions via data fusion. The state estimation problem will be considered from two different perspectives using the same kinematic model. First, the extended Kalman filter (EKF) will be reviewed, as an example of a stochastic approach; second, a recent nonlinear observer will be considered as a deterministic case. A comparative study of strapdown inertial navigation methods for estimating PVA of aerial vehicles fusing inertial sensors with global navigation satellite system (GNSS)-based positioning will be presented. The focus will be on the loosely coupled integration methods and performance analysis to compare these methods in terms of their stability, robustness to vibrations, and disturbances in measurements

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