Quad-Rotor Flight Simulation in Realistic Atmospheric Conditions

Abstract

In trajectory planning and control design for unmanned air vehicles, highly simplified models are typically used to represent the vehicle dynamics and the operating environment. The goal of this work is to perform real-time, but realistic flight simulations and trajectory planning for quad-copters in low altitude (<500m) atmospheric conditions. The aerodynamic model for rotor performance is adapted from blade element momentum theory and validated against experimental data. Large-eddy simulations of the atmospheric boundary layer are used to accurately represent the operating environment of unmanned air vehicles. A reduced-order version of the atmospheric boundary layer data as well as the popular Dryden model are used to assess the impact of accuracy of the wind field model on the predicted vehicle performance and trajectory. The wind model, aerodynamics and control modules are integrated into a six-degree-of-freedom flight simulation environment with a fully nonlinear flight controller. Simulations are performed for two representative flight paths, namely, straight and circular paths. Results for different wind models are compared and the impact of simplifying assumptions in representing rotor aerodynamics is discussed. The simulation framework and codes are open-sourced for use by the community. Nomenclature Symbols c = Rotor chord, m c d = Lumped drag coefficient

Transition in atmospheric boundary layer turbulence structure from neutral to convective, and large-scale rolls

“…2019) and unmanned aviation (Allison, Bai & Jayaraman 2018, 2019, 2020; Jayaraman, Allison & Bai 2019; Davoudi et al. 2020). There has been a long history in the observation, characterization and definition of horizontal roll structures (see Etling & Brown (1993) and Weckwerth et al.…”

A novel approach for optimal trajectory design with multiple operation modes of propulsion system, part 2

“…In order to clarify this point, Figure 5 depicts the time history of the switching functions defined in Eqs. (23) and (24). In fact, it shows that only those engines that operate at the maximum power are contributing to the thrust and rate of change of mass, whereas the engine(s) at the lowest power setting is (are) always inactive.…”

“…Trajectory optimization problems, in particular, and optimal control problems, in general, are solved by direct methods, indirect methods [19,20] or variants thereof [21,22]. The resulting optimal trajectories play a pivotal role in efficient operation of a number of flight vehicles [23,24]. Here, we focus on indirect optimization methods since satisfaction of the resuling first-order necessary conditions of optimality guarantees at least a local extremal solution [25].…”

Genetic Algorithm-Based Tuning of Backstepping Controller for a Quadrotor-Type Unmanned Aerial Vehicle

“…UAV systems have been studied as a whole or in subsystems (for example, tilt control). The challenge of these vehicles is that they are nonlinear, subacted, and multivariable systems, subject to unpredictable disturbances such as the interaction of the rotor flow with the quadrotor chassis or atmospheric turbulence [26][27][28][29][30][31][32][33][34][35][36][37][38][39], so that classic control (linear and invariant over time) has limited results where instabilities can occur when the system moves away from equilibrium.…”