Dynamic modeling and control of a Quadrotor using linear and nonlinear approaches

With the huge advancements in miniature sensors, actuators and processors depending mainly on the Micro and Nano-Electro-Mechanical-Systems (MEMS/NEMS), many researches are now focusing on developing miniature flying vehicles to be used in both research and commercial applications. This thesis work presents a detailed mathematical model for a Vertical Takeo ff and Landing (VTOL) type Unmanned Aerial Vehicle(UAV) known as the quadrotor. The nonlinear dynamic model of the quadrotor is formulated using the Newton-Euler method, the formulated model is detailed including aerodynamic effects and rotor dynamics that are omitted in many literature. The motion of the quadrotor can be divided into two subsystems; a rotational subsystem (attitude and heading) and a translational subsystem (altitude and x and y motion). Although the quadrotor is a 6 DOF underactuated system, the derived rotational subsystem is fully actuated, while the translational subsystem is underactuated. The derivation of the mathematical model is followed by the development of four control approaches to control the altitude, attitude, heading and position of the quadrotor in space. The fi rst approach is based on the linear Proportional-Derivative-Integral (PID) controller. The second control approach is based on the nonlinear Sliding Mode Controller (SMC). The third developed controller is a nonlinear Backstepping controller while the fourth is a Gain Scheduling based PID controller. The parameters and gains of the forementioned controllers were tuned using Genetic Algorithm (GA) technique to improve the systems dynamic response. Simulation based experiments were conducted to evaluate and compare the performance of the four developed control techniques in terms of dynamic performance, stability and the effect of possible disturbances

Plug-and-play adaptation in autopilot architectures for unmanned aerial vehicles

An accepted autopilot control architecture for fixed-wing unmanned aerial vehicles (UAVs) is the so-called cascaded loop closure, in which inner velocity loops and outer position loops are successively closed with proportional-integral-derivative (PID) controllers. This architecture has become so standard that popular open-source autopilots (e.g. ArduPilot, PX4) implement it in their codes. Despite its popularity, such architecture cannot adequately cope with the inevitable uncertainty in the UAV dynamics. In this work we present a "plug-and-play" adaptive module integrated in standard cascaded autopilot architectures, so as to can guarantee adaptation in the presence of uncertainty. The proposed module is analyzed and tested in a software-in-the-loop environment for an ArduPilot-based autopilot. The tests show that, in the presence of uncertainties occurring during flight, the proposed adaptation module outperforms the original autopilot as well as non-adaptive autopilots

Robust Nonlinear Tracking Control for Unmanned Aircraft in the Presence of Wake Vortex

The flight trajectory of unmanned aerial vehicles (UAVs) can be significantly affected by external disturbances such as turbulence, upstream wake vortices, or wind gusts. These effects present challenges for UAV flight safety. Hence, addressing these challenges is of critical importance for the integration of unmanned aerial systems (UAS) into the National Airspace System (NAS), especially in terminal zones. This work presents a robust nonlinear control method that has been designed to achieve roll/yaw regulation in the presence of unmodeled external disturbances and system nonlinearities. The data from NASA-conducted airport experimental measurements as well as high-fidelity Large Eddy Simulations of the wake vortex are used in the study. Side-by-side simulation comparisons between the robust nonlinear control law and both linear H∞ role= presentation style= box-sizing: border-box; max-height: none; display: inline; line-height: normal; font-size: 13.2px; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; color: rgb(34, 34, 34); font-family: Arial, Arial, Helvetica, sans-serif; position: relative; \u3eH∞�∞ and PID control laws are provided for completeness. These simulations are focused on applications involving small UAV affected by the wake vortex disturbance in the vicinity of the ground (which models the take-off or landing phase) as well as in the out-of-ground zone. The results demonstrate the capability of the proposed nonlinear controller to asymptotically reject wake vortex disturbance in the presence of the nonlinearities in the system (i.e., parametric variations, unmodeled, time-varying disturbances). Further, the nonlinear controller is designed with a computationally efficient structure without the need for the complex calculations or function approximators in the control loop. Such a structure is motivated by UAV applications where onboard computational resources are limited

Disturbance rejection flight control for small fixed-wing unmanned aerial vehicles

Disturbance rejection flight control for small fixed-wing unmanned aerial vehicle

Concept and Feasibility Evaluation of Distributed Sensor-Based Measurement Systems Using Formation Flying Multicopters

Unmanned aerial vehicles (UAVs) have been used for increasing research applications in atmospheric measurements. However, most current solutions for these applications are based on a single UAV with limited payload capacity. In order to address the limitations of the single UAV-based approach, this paper proposes a new concept of measurements using tandem flying multicopters as a distributed sensor platform. Key challenges of the proposed concept are identified including the relative position estimation and control in wind-perturbed outdoor environment and the precise alignment of payloads. In the proposed concept, sliding mode control is chosen as the relative position controller and a gimbal stabilization system is introduced to achieve fine payload alignment. The characterization of the position estimation sensors (including global navigation satellite system and real-time kinematics) and flight controller is carried out using different UAVs (a DJI Matrice M600 Pro Hexacopter and Tarot X4 frame based Quadcopter) under different wind levels. Based on the experimental data, the performance of the sliding mode controller and the performance of the gimbal stabilization system are evaluated in a hardware-in-the-loop simulation environment (called ELISSA). Preliminary achievable control accuracies of the relative position and attitude of subsystems in the proposed concept are estimated based on experimental result

Vision - based self - guided Quadcopter landing on moving platform during fault detection

Fault occurrence in the quadcopter is very common during operation in the air. This paper presents a real-time implementation to detect the fault and then the system is guaranteeing to safely land on the surface, even the moving landing platform. Primarily, PixHawk auto-pilot was used to verify in real-time, with platform detection and various environmental conditions. The method is ensuring the quadcopter operates in the landing area zone with the help of a GPS feature. Then the precise landing on the astable-landing platform is calibrated automatically using the vision-based learning feedback technique. The proposed objective is developed using reconfigurable Raspberry Pi-3 with a Pi camera. The full decision on an efficient landing algorithm is deployed into the quadcopter. The system is self-guided and automatically returns to home-based whenever the fault detects. The study is conducted with the situation of low battery operation and the trigger of auto-pilot helps to land the device safely before any mal-function. The system is featured with predetermined speed and altitude while navigating the home base, thus improves the detection process. Finally, the experiment study provided successful trials to track usable platform, landing on a restricted area, and disarm the motors autonomously

Geometric versus Model Predictive Control based guidance algorithms for fixed-wing UAVs in the presence of very strong wind fields.

The recent years have witnessed increased development of small, autonomous fixed-wing Unmanned Aerial Vehicles (UAVs). In order to unlock widespread applicability of these platforms, they need to be capable of operating under a variety of environmental conditions. Due to their small size, low weight, and low speeds, they require the capability of coping with wind speeds that are approaching or even faster than the nominal airspeed. In this thesis, a nonlinear-geometric guidance strategy is presented, addressing this problem. More broadly, a methodology is proposed for the high-level control of non-holonomic unicycle-like vehicles in the presence of strong flowfields (e.g. winds, underwater currents) which may outreach the maximum vehicle speed. The proposed strategy guarantees convergence to a safe and stable vehicle configuration with respect to the flowfield, while preserving some tracking performance with respect to the target path. As an alternative approach, an algorithm based on Model Predictive Control (MPC) is developed, and a comparison between advantages and disadvantages of both approaches is drawn. Evaluations in simulations and a challenging real-world flight experiment in very windy conditions confirm the feasibility of the proposed guidance approach

Nonlinear Feedback Control of Axisymmetric Aerial Vehicles

We investigate the use of simple aerodynamic models for the feedback control of aerial vehicles with large flight envelopes. Thrust-propelled vehicles with a body shape symmetric with respect to the thrust axis are considered. Upon a condition on the aerodynamic characteristics of the vehicle, we show that the equilibrium orientation can be explicitly determined as a function of the desired flight velocity. This allows for the adaptation of previously proposed control design approaches based on the thrust direction control paradigm. Simulation results conducted by using measured aerodynamic characteristics of quasi-axisymmetric bodies illustrate the soundness of the proposed approach

Enabling technologies for precise aerial manufacturing with unmanned aerial vehicles

The construction industry is currently experiencing a revolution with automation techniques such as additive manufacturing and robot-enabled construction. Additive Manufacturing (AM) is a key technology that can o er productivity improvement in the construction industry by means of o -site prefabrication and on-site construction with automated systems. The key bene t is that building elements can be fabricated with less materials and higher design freedom compared to traditional manual methods. O -site prefabrication with AM has been investigated for some time already, but it has limitations in terms of logistical issues of components transportation and due to its lack of design exibility on-site. On-site construction with automated systems, such as static gantry systems and mobile ground robots performing AM tasks, can o er additional bene ts over o -site prefabrication, but it needs further research before it will become practical and economical. Ground-based automated construction systems also have the limitation that they cannot extend the construction envelope beyond their physical size. The solution of using aerial robots to liberate the process from the constrained construction envelope has been suggested, albeit with technological challenges including precision of operation, uncertainty in environmental interaction and energy e ciency. This thesis investigates methods of precise manufacturing with aerial robots. In particular, this work focuses on stabilisation mechanisms and origami-based structural elements that allow aerial robots to operate in challenging environments. An integrated aerial self-aligning delta manipulator has been utilised to increase the positioning accuracy of the aerial robots, and a Material Extrusion (ME) process has been developed for Aerial Additive Manufacturing (AAM). A 28-layer tower has been additively manufactured by aerial robots to demonstrate the feasibility of AAM. Rotorigami and a bioinspired landing mechanism demonstrate their abilities to overcome uncertainty in environmental interaction with impact protection capabilities and improved robustness for UAV. Design principles using tensile anchoring methods have been explored, enabling low-power operation and explores possibility of low-power aerial stabilisation. The results demonstrate that precise aerial manufacturing needs to consider not only just the robotic aspects, such as ight control algorithms and mechatronics, but also material behaviour and environmental interaction as factors for its success.Open Acces