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

Variable Fidelity Studies in Wake Vortex Evolution, Safety, and Control

The purpose of this research is to develop a variable-fidelity approach for addressing the safety of unmanned aerial system (UAS) operations in the national aerospace system (NAS). This task is implemented on the basis of safety investigation toolkit for analysis and reporting wake vortex safety system (SITAR WVSS) code, which is a dynamic low-fidelity model addressing generation, evolution, and interaction of the leader-aircraft wake vortex with the follower-aircraft lifting surfaces. The first part of the dissertation deals with the generation, evolution, and interaction of the wake vortices produced by an aircraft. In particular, it presents the results of the vortex safety analysis conducted for selected UAS operating alongside commercial aircraft in the terminal zone. The work further investigates and compares decay and transport of the wake vortex in the vicinity of various grounds including a solid surface, a forest canopy, and a water surface, representative of various terminal zone environments. The obtained high-fidelity results form the basis for reduced-order models to be integrated into the fast-analysis code under development for in-situ wake vortex safety predictions. The second part of the dissertation introduces a robust nonlinear control method that is proven to achieve altitude regulation in the presence of unmodeled external disturbances (e.g. wind gust, wake vortex disturbance) and actuator parametric uncertainty. This method is designed as a part of “Interaction” sub-module of the SITAR WVSS model. The results demonstrate the capability of the proposed nonlinear controller to asymptotically reject wind gust/wake-vortex disturbances and the parametric uncertainty. The proposed controller is a great choice for small UAV applications with limited computational resources

System Identification of a Circulation Control Unmanned Aerial Vehicle

The advancement in automation and sensory systems in recent years has led to an increase the demand of UAV missions. Due to this increase in demand, the research community has gained interest in investigating UAV performance enhancing systems. Circulation Control (CC), which is an active control flow method used to enhance UAV lift, is a performance enhancing system currently studied. In prior research, experimental studies have shown that Circulation Control wings (CCW) implemented on class-I UAVs can reduce take-off distance by 54%. Wind tunnel tests reveal that CC improves aircraft payload capabilities through lift enhancement. Increasing aircraft payload capabilities causes an increase in UAV applications. Design and implementation of autopilot algorithms making the CC-based UAV capable af autonomous flight increases the number of applications for which it is suited. In this thesis, mathematical models of a CC-based UAV are derived and validated. The mathematical models are used to determine the effects of CC on the stability properties of the UAV. Capturing the dynamics of a CC-based UAV paves the way for designing autopilot algorithms for autonomous flights. Verification experiments demonstrate a good match between the model and UAV (RMS error \u3c 2.5) and good model predictive ability (Theil inequality coefficient is \u3c 0.19). Flight tests reveal the introduction of a nose down pitching moment effect due to CC which changes the trim flight values. Parameter estimation is performed to derive stability derivatives that capture the stability properties of the CC UAV

Deep Reinforcement Learning Attitude Control of Fixed-Wing UAVs Using Proximal Policy Optimization

Contemporary autopilot systems for unmanned aerial vehicles (UAVs) are far more limited in their flight envelope as compared to experienced human pilots, thereby restricting the conditions UAVs can operate in and the types of missions they can accomplish autonomously. This paper proposes a deep reinforcement learning (DRL) controller to handle the nonlinear attitude control problem, enabling extended flight envelopes for fixed-wing UAVs. A proof-of-concept controller using the proximal policy optimization (PPO) algorithm is developed, and is shown to be capable of stabilizing a fixed-wing UAV from a large set of initial conditions to reference roll, pitch and airspeed values. The training process is outlined and key factors for its progression rate are considered, with the most important factor found to be limiting the number of variables in the observation vector, and including values for several previous time steps for these variables. The trained reinforcement learning (RL) controller is compared to a proportional-integral-derivative (PID) controller, and is found to converge in more cases than the PID controller, with comparable performance. Furthermore, the RL controller is shown to generalize well to unseen disturbances in the form of wind and turbulence, even in severe disturbance conditions.Comment: 11 pages, 3 figures, 2019 International Conference on Unmanned Aircraft Systems (ICUAS

Nonlinear Controller Design for UAVs with Time-Varying Aerodynamic Uncertainties

Unmanned Aerial Vehicles (UAVs) are here and they are here to stay. Unmanned Aviation has expanded significantly in recent years and research and development in the field of navigation and control have advanced beyond expectations. UAVs are currently being used for defense programs around the world but the range of applications is expected to grow in the near future, with civilian applications such as environmental and aerial monitoring, aerial surveillance and homeland security being some representative examples. Conventional and commercially available small-scale UAVs have limited utilization and applicability to executing specific short-duration missions because of limitations in size, payload, power supply and endurance. This fact has already marked the dawn of a new era of more powerful and versatile UAVs (e.g. morphing aircraft), able to perform a variety of missions. This dissertation presents a novel, comprehensive, step-by-step, nonlinear controller design framework for new generation, non-conventional UAVs with time-varying aerodynamic characteristics during flight. Controller design for such UAVs is a challenging task mainly due to uncertain aerodynamic parameters in the UAV mathematical model. This challenge is tackled by using and implementing μ-analysis and additive uncertainty weighting functions. The technique described herein can be generalized and applied to the class of non-conventional UAVs, seeking to address uncertainty challenges regarding the aircraft\u27s aerodynamic coefficients

A survey of free software for the design, analysis, modelling, and simulation of an unmanned aerial vehicle

The objective of this paper is to analyze free software for the design, analysis, modelling, and simulation of an unmanned aerial vehicle (UAV). Free software is the best choice when the reduction of production costs is necessary; nevertheless, the quality of free software may vary. This paper probably does not include all of the free software, but tries to describe or mention at least the most interesting programs. The first part of this paper summarizes the essential knowledge about UAVs, including the fundamentals of flight mechanics and aerodynamics, and the structure of a UAV system. The second section generally explains the modelling and simulation of a UAV. In the main section, more than 50 free programs for the design, analysis, modelling, and simulation of a UAV are described. Although the selection of the free software has been focused on small subsonic UAVs, the software can also be used for other categories of aircraft in some cases; e.g. for MAVs and large gliders. The applications with an historical importance are also included. Finally, the results of the analysis are evaluated and discussed—a block diagram of the free software is presented, possible connections between the programs are outlined, and future improvements of the free software are suggested. © 2015, CIMNE, Barcelona, Spain.Internal Grant Agency of Tomas Bata University in Zlin [IGA/FAI/2015/001, IGA/FAI/2014/006

Mathematical modelling, flight control system design and air flow control investigation for low speed UAVs

The demand for unmanned aerial vehicles (UAVs) has increased dramatically in the last decade from reconnaissance missions to attack roles. As their missions become more complex, advances in endurance and manoeuvrability become crucial. Due to the advances in material fabrication, wing morphing can be seen as an ideal solution for UAVs to provide improvements by overcoming the weight drawback. This thesis investigates the area of aircraft design and simulation for low speed UAVs looking at performance enhancements techniques for low speed UAVs, and their effects on the aerodynamic capabilities of the wing. The focus is on both suitable control design and wing morphing techniques based on current research findings. The low speed UAV X-RAE1 is used as the test bed for this investigation and is initially analytically presented as three dimensional body where the equations relate to the forces and moments acting on the UAV. A linearised model for straight flight at different velocities is implemented and validated against a non-linear model. Simulations showed the X-RAE1 to have acceptable stability properties over the design operating range. Control design techniques, linear quadratic regulators (LQR) and H-infinity optimisation with Loop Shaping Design Procedure (LSDP), are used to design simple control schemes for linearised longitudinal model of the X-RAE1 UAV at different velocities. The effectiveness and limitations of the two design methods show that both designs are very fast, with settling times 2-3 seconds in the height response and remarkably low variation of the results at different velocities. Computational fluid dynamics is then used to investigate and simulate the impact of introducing smart effector arrays on a UAV. The smart effector array produces a form of active flow control by providing localised flow field changes. These induced changes have direct impact on the aerodynamic forces and showed a substantial increase of lift at low angles of attack. There was also a significant increase to the lift to drag ratio at high angles of attack which resulted to a delay in stall

Aerial Vehicles

This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space

Single-Rotor Helicopter Dynamics and Maneuvering Simulation

This paper presents the development and validation of a robust flight dynamics model for simulation of a full-scale single-rotor helicopter dynamics and maneuvering. A minimum-complexity dynamic model is used to compute the aerodynamic forces and moments using trajectory-planning strategy. A high-order sliding mode (HOSM) observer is used as a numerical differentiator for computing time rate changes of longitudinal and lateral control inputs to the main rotor dynamics during maneuvering. The HOSM differentiator suppresses numerical instability and increases computation accuracy of both dynamic and kinematic characteristics. Using available data and flight test results for UH-60 helicopter, the control input characteristics are interpolated versus flight speeds. A pull-up maneuver is simulated to demonstrate the effectiveness of the proposed model