Unmanned air vehicles are becoming increasingly popular alternatives for private applications which include, but are not limited to, fire fighting, search and rescue, atmospheric data collection, and crop surveys, to name a few. Among these vehicles are avian-inspired, flapping-wing designs, which are safe to operate near humans and are required to carry payloads while achieving manoeuverability and agility in low speed flight. Conventional methods and tools fall short of achieving the desired performance metrics and requirements of such craft. Flight dynamics and system identification for modern feedback control provides an in-depth study of the difficulties associated with achieving controlled performance in flapping-wing, avian-inspired flight, and a new model paradigm is derived using analytical and experimental methods, with which a controls designer may then apply familiar tools. This title consists of eight chapters and covers flapping-wing aircraft and flight dynamics, before looking at nonlinear, multibody modelling as well as flight testing and instrumentation. Later chapters examine system identification from flight test data, feedback control and linearization.
Presents experimental flight data for validation and verification of modelled dynamics, thus illustrating the deficiencies and difficulties associated with modelling flapping-wing flightDerives a new flight dynamics model needed to model avian-inspired vehicles, based on nonlinear multibody dynamicsExtracts aerodynamic models of flapping flight from experimental flight data and system identification techniques

Modern Flexible Multi-Body Dynamics Modeling Methodology for Flapping Wing Vehicles presents research on the implementation of a flexible multi-body dynamic representation of a flapping wing ornithopter that considers aero-elasticity. This effort brings advances in the understanding of flapping wing flight physics and dynamics that ultimately leads to an improvement in the performance of such flight vehicles, thus reaching their high performance potential. In using this model, it is necessary to reduce body accelerations and forces of an ornithopter vehicle, as well as to improve the aerodynamic performance and enhance flight kinematics and forces which are the design optimization objectives. This book is a useful reference for postgraduates in mechanical engineering and related areas, as well as researchers in the field of multibody dynamics.

Active Spanwise Lift Control presents a novel approach to tackle the gust alleviation problem. Traditional approaches typically attempt to suppress the structural response at discrete points of the wing using only the conventional control surfaces (aileron, elevator, rudder), resulting in limited control authority, high-bandwidth actuator requirements, and necessity of gust field measurements ahead of the aircraft. In this book, the authors directly address the spanwise behavior of aerodynamic loads, as this is what should be primarily controlled. Because the gust loads are mainly caused by disturbances in the spanwise lift, the aim is at controlling the shape of the lift distribution profile along the span. Therefore, this distributed approach allows control of the loads at all points of the wing structure. Moreover, using modal decomposition concepts, the control surfaces can be designed to maximize controllability of the most relevant aerodynamic modes, which naturally results in lower actuator rate requirements. In the work herein, the unsteady aerodynamics of a finite wing featuring multiple trailing edge flaps is modeled using the Unsteady Vortex Lattice Method (UVLM), yielding a linear, time-invariant, high-order state-space model. An Eigensystem Realization Algorithm (ERA) is applied for model-order reduction and modal identification, providing aerodynamic mode shapes and associated eigenvalues. By representing the system output (lift distribution) as a truncated superposition of aerodynamic mode shapes, a low-order MIMO modal representation is obtained, suitable for controller synthesis. This methodology is used to synthesize regulators, to suppress gust disturbances in lift distribution, and trackers, to dynamically follow any desired reference lift profile. A special observer structure decouples the gust input from the state estimation process and provides estimates for the gust amplitude along time, thus rendering the gust measurements ahead of the aircraft unnecessary.