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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 flight - Derives a new flight dynamics model needed to model avian-inspired vehicles, based on nonlinear multibody dynamics - Extracts aerodynamic models of flapping flight from experimental flight data and system identification techniques
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.
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. - Uses Lagrange equations of motion in terms of a generalized coordinate vector of the rigid and flexible bodies in order to model the flexible multi-body system - Provides flight verification data and flight physics of highly flexible ornithoptic vehicles - Includes an online companion site with files/codes used in application examples
Based on a 15-year successful approach to teaching aircraft flight mechanics at the US Air Force Academy, this text explains the concepts and derivations of equations for aircraft flight mechanics. It covers aircraft performance, static stability, aircraft dynamics stability and feedback control.
An updated and expanded new edition of an authoritative book on flight dynamics and control system design for all types of current and future fixed-wing aircraft Since it was first published, Flight Dynamics has offered a new approach to the science and mathematics of aircraft flight, unifying principles of aeronautics with contemporary systems analysis. Now updated and expanded, this authoritative book by award-winning aeronautics engineer Robert Stengel presents traditional material in the context of modern computational tools and multivariable methods. Special attention is devoted to models and techniques for analysis, simulation, evaluation of flying qualities, and robust control system design. Using common notation and not assuming a strong background in aeronautics, Flight Dynamics will engage a wide variety of readers, including aircraft designers, flight test engineers, researchers, instructors, and students. It introduces principles, derivations, and equations of flight dynamics as well as methods of flight control design with frequent reference to MATLAB functions and examples. Topics include aerodynamics, propulsion, structures, flying qualities, flight control, and the atmospheric and gravitational environment. The second edition of Flight Dynamics features up-to-date examples; a new chapter on control law design for digital fly-by-wire systems; new material on propulsion, aerodynamics of control surfaces, and aeroelastic control; many more illustrations; and text boxes that introduce general mathematical concepts. Features a fluid, progressive presentation that aids informal and self-directed study Provides a clear, consistent notation that supports understanding, from elementary to complicated concepts Offers a comprehensive blend of aerodynamics, dynamics, and control Presents a unified introduction of control system design, from basics to complex methods Includes links to online MATLAB software written by the author that supports the material covered in the book
This edition of this this flight stability and controls guide features an unintimidating math level, full coverage of terminology, and expanded discussions of classical to modern control theory and autopilot designs. Extensive examples, problems, and historical notes, make this concise book a vital addition to the engineer's library.
With the demand for more advanced fighter aircraft, relying on unstable flight mechanical characteristics to gain flight performance, more focus has been put on model-based system engineering to help with the design work. The flight control system design is one important part that relies on this modeling. Therefore, it has become more important to develop flight mechanical models that are highly accurate in the whole flight envelope. For today’s modern fighter aircraft, the basic flight mechanical characteristics change between linear and nonlinear as well as stable and unstable as an effect of the desired capability of advanced maneuvering at subsonic, transonic and supersonic speeds. This thesis combines the subject of system identification, which is the art of building mathematical models of dynamical systems based on measurements, with aeronautical engineering in order to find methods for identifying flight mechanical characteristics. Here, some challenging aeronautical identification problems, estimating model parameters from flight-testing, are treated. Two aspects are considered. The first is online identification during flight-testing with the intent to aid the engineers in the analysis process when looking at the flight mechanical characteristics. This will also ensure that enough information is available in the resulting test data for post-flight analysis. Here, a frequency domain method is used. An existing method has been developed further by including an Instrumental Variable approach to take care of noisy data including atmospheric turbulence and by a sensor-fusion step to handle varying excitation during an experiment. The method treats linear systems that can be both stable and unstable working under feedback control. An experiment has been performed on a radio-controlled demonstrator aircraft. For this, multisine input signals have been designed and the results show that it is possible to perform more time-efficient flight-testing compared with standard input signals. The other aspect is post-flight identification of nonlinear characteristics. Here the properties of a parameterized observer approach, using a prediction-error method, are investigated. This approach is compared with four other methods for some test cases. It is shown that this parameterized observer approach is the most robust one with respect to noise disturbances and initial offsets. Another attractive property is that no user parameters have to be tuned by the engineers in order to get the best performance. All methods in this thesis have been validated on simulated data where the system is known, and have also been tested on real flight test data. Both of the investigated approaches show promising results.
The essential introduction to the principles and applications of feedback systems—now fully revised and expanded This textbook covers the mathematics needed to model, analyze, and design feedback systems. Now more user-friendly than ever, this revised and expanded edition of Feedback Systems is a one-volume resource for students and researchers in mathematics and engineering. It has applications across a range of disciplines that utilize feedback in physical, biological, information, and economic systems. Karl Åström and Richard Murray use techniques from physics, computer science, and operations research to introduce control-oriented modeling. They begin with state space tools for analysis and design, including stability of solutions, Lyapunov functions, reachability, state feedback observability, and estimators. The matrix exponential plays a central role in the analysis of linear control systems, allowing a concise development of many of the key concepts for this class of models. Åström and Murray then develop and explain tools in the frequency domain, including transfer functions, Nyquist analysis, PID control, frequency domain design, and robustness. Features a new chapter on design principles and tools, illustrating the types of problems that can be solved using feedback Includes a new chapter on fundamental limits and new material on the Routh-Hurwitz criterion and root locus plots Provides exercises at the end of every chapter Comes with an electronic solutions manual An ideal textbook for undergraduate and graduate students Indispensable for researchers seeking a self-contained resource on control theory
Presenting current trends in the development and applications of intelligent systems in engineering, this monograph focuses on recent research results in system identification and control. The recurrent neurofuzzy and the fuzzy cognitive network (FCN) models are presented. Both models are suitable for partially-known or unknown complex time-varying systems. Neurofuzzy Adaptive Control contains rigorous proofs of its statements which result in concrete conclusions for the selection of the design parameters of the algorithms presented. The neurofuzzy model combines concepts from fuzzy systems and recurrent high-order neural networks to produce powerful system approximations that are used for adaptive control. The FCN model stems from fuzzy cognitive maps and uses the notion of “concepts” and their causal relationships to capture the behavior of complex systems. The book shows how, with the benefit of proper training algorithms, these models are potent system emulators suitable for use in engineering systems. All chapters are supported by illustrative simulation experiments, while separate chapters are devoted to the potential industrial applications of each model including projects in: • contemporary power generation; • process control and • conventional benchmarking problems. Researchers and graduate students working in adaptive estimation and intelligent control will find Neurofuzzy Adaptive Control of interest both for the currency of its models and because it demonstrates their relevance for real systems. The monograph also shows industrial engineers how to test intelligent adaptive control easily using proven theoretical results.
This text covers the material that every engineer, and most scientists and prospective managers, needs to know about feedback control, including concepts like stability, tracking, and robustness. Each chapter presents the fundamentals along with comprehensive, worked-out examples, all within a real-world context.