Aircraft System Identification


Book Description

This book provides a comprehensive overview of both the theoretical underpinnings and the practical application of aircraft modeling based on experimental data also known as aircraft system identification. Much of the material presented comes from the authors own extensive research and teaching activities at the NASA Langley Research Center, and is based on real-world applications of system identification to aircraft. The book uses actual flight-test and wind-tunnel data for case studies and examples, and is a valuable resource for researchers and practicing engineers, as well as a textbook for postgraduate and senior-level courses. [...] The methods and algorithms explained in the book are implemented in a NASA software toolbox called SIDPAC (System IDentification Programs for AirCraft). SIDPAC is written in MATLAB®, and is available by request from NASA Langley Research Center. SIDPAC is composed of many different tools that implement a wide variety of approaches explained fully in the book. These tools can be readily applied to solve aircraft system identification problems.




Aircraft and Rotorcraft System Identification


Book Description

Although many books have been written on the theory of system identification, few are available that provide a complete engineering treatment of system identification and how to successfully apply it to flight vehicles. This book presents proven methods, practical guidelines, and real-world flight-test results for a wide range of state-of-the-art flight vehicles, from small uncrewed aerial vehicles (UAVs) to large manned aircraft/rotorcraft.




Flight Vehicle System Identification


Book Description

This valuable volume offers a systematic approach to flight vehicle system identification and exhaustively covers the time domain methodology. It addresses in detail the theoretical and practical aspects of various parameter estimation methods, including those in the stochastic framework and focusing on nonlinear models, cost functions, optimization methods, and residual analysis. A pragmatic and balanced account of pros and cons in each case is provided. The book also presents data gathering and model validation, and covers both large-scale systems and high-fidelity modeling. Real world problems dealing with a variety of flight vehicle applications are addressed and solutions are provided. Examples encompass such problems as estimation of aerodynamics, stability, and control derivatives from flight data, flight path reconstruction, nonlinearities in control surface effectiveness, stall hysteresis, unstable aircraft, and other critical considerations.




Flight Test System Identification


Book Description

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.




Flight Dynamics and System Identification for Modern Feedback Control


Book Description

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.




System Identification


Book Description

Electrical Engineering System Identification A Frequency Domain Approach How does one model a linear dynamic system from noisy data? This book presents a general approach to this problem, with both practical examples and theoretical discussions that give the reader a sound understanding of the subject and of the pitfalls that might occur on the road from raw data to validated model. The emphasis is on robust methods that can be used with a minimum of user interaction. Readers in many fields of engineering will gain knowledge about: * Choice of experimental setup and experiment design * Automatic characterization of disturbing noise * Generation of a good plant model * Detection, qualification, and quantification of nonlinear distortions * Identification of continuous- and discrete-time models * Improved model validation tools and from the theoretical side about: * System identification * Interrelations between time- and frequency-domain approaches * Stochastic properties of the estimators * Stochastic analysis System Identification: A Frequency Domain Approach is written for practicing engineers and scientists who do not want to delve into mathematical details of proofs. Also, it is written for researchers who wish to learn more about the theoretical aspects of the proofs. Several of the introductory chapters are suitable for undergraduates. Each chapter begins with an abstract and ends with exercises, and examples are given throughout.







Principles of System Identification


Book Description

Master Techniques and Successfully Build Models Using a Single Resource Vital to all data-driven or measurement-based process operations, system identification is an interface that is based on observational science, and centers on developing mathematical models from observed data. Principles of System Identification: Theory and Practice is an introductory-level book that presents the basic foundations and underlying methods relevant to system identification. The overall scope of the book focuses on system identification with an emphasis on practice, and concentrates most specifically on discrete-time linear system identification. Useful for Both Theory and Practice The book presents the foundational pillars of identification, namely, the theory of discrete-time LTI systems, the basics of signal processing, the theory of random processes, and estimation theory. It explains the core theoretical concepts of building (linear) dynamic models from experimental data, as well as the experimental and practical aspects of identification. The author offers glimpses of modern developments in this area, and provides numerical and simulation-based examples, case studies, end-of-chapter problems, and other ample references to code for illustration and training. Comprising 26 chapters, and ideal for coursework and self-study, this extensive text: Provides the essential concepts of identification Lays down the foundations of mathematical descriptions of systems, random processes, and estimation in the context of identification Discusses the theory pertaining to non-parametric and parametric models for deterministic-plus-stochastic LTI systems in detail Demonstrates the concepts and methods of identification on different case-studies Presents a gradual development of state-space identification and grey-box modeling Offers an overview of advanced topics of identification namely the linear time-varying (LTV), non-linear, and closed-loop identification Discusses a multivariable approach to identification using the iterative principal component analysis Embeds MATLAB® codes for illustrated examples in the text at the respective points Principles of System Identification: Theory and Practice presents a formal base in LTI deterministic and stochastic systems modeling and estimation theory; it is a one-stop reference for introductory to moderately advanced courses on system identification, as well as introductory courses on stochastic signal processing or time-series analysis.The MATLAB scripts and SIMULINK models used as examples and case studies in the book are also available on the author's website: http://arunkt.wix.com/homepage#!textbook/c397




Flight Dynamics


Book Description

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




On Subscale Flight Testing


Book Description

Downscaled physical models, also referred to as subscale models, have played an essential role in the investigation of the complex physics of flight until the recent disruption of numerical simulation. Despite the fact that improvements in computational methods are slowly pushing experimental techniques towards a secondary role as verification or calibration tools, real-world testing of physical prototypes still provides an unmatched confidence. Physical models are very effective at revealing issues that are sometimes not correctly identified in the virtual domain, and hence can be a valuable complement to other design tools. But traditional wind-tunnel testing cannot always meet all of the requirements of modern aeronautical research and development. It is nowadays too expensive to use these scarce facilities to explore different design iterations during the initial stages of aircraft development, or to experiment with new and immature technologies. Testing of free-flight subscale models, referred to as Subscale Flight Testing (SFT), could offer an affordable and low-risk alternative for complementing conventional techniques with both qualitative and quantitative information. The miniaturisation of mechatronic systems, the advances in rapid-prototyping techniques and power storage, as well as new manufacturing methods, currently enable the development of sophisticated test objects at scales that were impractical some decades ago. Moreover, the recent boom in the commercial drone industry has driven a quick development of specialised electronics and sensors, which offer nowadays surprising capabilities at competitive prices. These recent technological disruptions have significantly altered the cost-benefit function of SFT and it is necessary to re-evaluate its potential in the contemporary aircraft development context. This thesis aims to increase the comprehension and knowledge of the SFT method in order to define a practical framework for its use in aircraft design; focusing on low-cost, short-time solutions that don’t require more than a small organization and few resources. This objective is approached from a theoretical point of view by means of an analysis of the physical and practical limitations of the scaling laws; and from an empirical point of view by means of field experiments aimed at identifying practical needs for equipment, methods, and tools. A low-cost data acquisition system is developed and tested; a novel method for semi-automated flight testing in small airspaces is proposed; a set of tools for analysis and visualisation of flight data is presented; and it is also demonstrated that it is possible to explore and demonstrate new technology using SFT with a very limited amount of economic and human resources. All these, together with a theoretical review and contextualisation, contribute to increasing the comprehension and knowledge of the SFT method in general, and its potential applications in aircraft conceptual design in particular.