Rotorcraft System Identification Research Articles

Advancements in the Theory and Practice of Flight Vehicle System Identification

System identification methods have played an essential role in the research and industry projects at the Institute of Flight System Dynamics of the Technical University of Munich. Besides the application of the established system identification approaches to multiple aircraft, novel methods have been developed at the institute to deal with the challenges associated with fixed- and rotary-wing aircraft system identification in the time and frequency domains. This paper provides an overview of these new developments, as well as practical application examples from the past and ongoing projects at the institute. After a brief introduction to the work at the institute, the paper describes the new advancements in the fields of time domain system identification and optimal input design by introducing optimal control methods. It continues with an alternative problem formulation for applying frequency domain system identification and parameter estimation methods to a novel flight control design and tuning approach. Additional topics from the past and ongoing research at the institute such as novel methods and practical findings in rotorcraft system identification and flight path reconstruction for different applications will be discussed and referenced.

Advances and Modern Applications of Frequency-Domain Aircraft and Rotorcraft System Identification

This paper provides an overview of advances and applications of aircraft and rotorcraft flight dynamics system identification at the U.S. Army Combat Capabilities Development Command Aviation & Missile Center over the past 20 years. An overarching topic is how frequency-domain system identification has evolved to aid modeling work of modern aircraft and rotorcraft configurations. The paper starts with a brief overview of the frequency-response method for system identification. Subsequently, the paper highlights and demonstrates several new advances using flight-test data from a conventional helicopter, fixed-wing aircraft, advanced coaxial compound rotorcraft, and a small multirotor unmanned aerial vehicle. The first advancement is the use of identification results to improve simulation model fidelity. The next advancement is the Joint Input-Output Method for identification of aircraft with highly correlated inputs. Next, the paper discusses the advancement of flexible constraints, which provide the ability to directly determine physical parameters from flight-test data. The paper then discusses a methodology to identify lower-order linearized dynamic inflow models from higher-order free wake aerodynamic models. Finally, the paper discusses model stitching, which is the technique of combining or stitching together individual linear models and trim data for discrete flight conditions to produce a continuous, full flight-envelope real-time stitched simulation model.

Retrospective and Recent Examples of Aircraft and Rotorcraft System Identification at DLR

Aircraft system identification has a five-decades-long tradition at German Aerospace Center (DLR). Over the last two decades, the research covered various topics related to system identification of fixed- and rotary-wing aircraft, nonconventional applications and atmospheric effects, the development of new flight-test procedures for system identification purposes, and specific aircraft model enhancements and corresponding parameter estimation. Comprehensive tools were developed that support this research and can be applied to a variety of different problems and types of vehicles. The paper starts with a short description of the different system identification methods used at DLR and the corresponding tools. The discussion of flight-test procedures and maneuver design as well as sensor fusion and flight-path reconstruction provides information on how to optimize the flight tests for system identification and to arrive at a consistent flight-test database. The examples for fixed-wing aircraft provide information on identification including abnormal conditions such as icing and interaction with atmospheric disturbances as well as modeling of structural mechanics and loads. The identification of high-order rotorcraft models that account for rotor and engine dynamics and even structural modes is discussed, and the identification of rotor mast moments as well as the identification of non-physics-based models and their integration into physics-based models are also covered. A final section shows that system identification can also be used to derive models for gyroplanes and parachutes as well as to derive control equivalent turbulence input models and to estimate complex wind field geometries. Thus, a broad overview of possible applications of system identification is given.

A New Heuristic Approach to Rotorcraft System Identification

High-fidelity rotorcraft flight simulation relies on the availability of a quality flight model that further demands a good level of understanding of the complexities arising from aerodynamic couplings and interference effects. This paper explores rotorcraft flight dynamics in the low-speed regime where such complexities abound and presents a new heuristic approach in the time domain to aid identification of nonlinear dynamics and fidelity assessment. The approach identifies flight model parameters "additively," based on their contribution to the local dynamic response of the system, in contrast with conventional approaches where parameter values are identified to minimize errors over a whole maneuver. In these early investigations, identified low-order, rigid-body, linear models show good comparison with flight-test data. The approach is extended to explore nonlinearities attributed to the so-called maneuver wake distortion and wake skew effects emerging in larger maneuvers. The results show a good correlation for the proposed nonlinear model structure, demonstrated by its capability to capture the time response and variations of the stability and control derivatives with response magnitude.

Initial investigation into the complementary use of black box and physics-based techniques in rotorcraft system identification

Accurate linear helicopter models are needed for control system development and simulation and can be determined by system identification when appropriate test data are available. Standard methods for rotorcraft system identification are the frequency domain maximum likelihood method and the frequency response method that are used to derive physics-based linear state-space models. Also the optimized predictor-based subspace identification method (PBSIDopt), a time domain system identification method that yields linear black box state-space models, has been successfully applied to rotorcraft data. As both methods have their respective strengths and weaknesses, it was tried to combine both techniques. The paper demonstrates the successful complementary use of physics-based frequency domain methods and the black box PBSIDopt method in the areas of database requirements, accuracy metrics, and model structure development using flight test data of DLR’s ACT/FHS research rotorcraft.

Aircraft and Rotorcraft System Identification: Engineering Methods with Flight Test Examples, Second Edition [Bookshelf

This book is largely devoted to the practical engineering aspects of aircraft system identification using real-world flight tests, and it indeed includes an impressive array of examples. The text presents examples involving 17 different airframes, including conventional fixed-wing aircraft, helicopters, tilt-rotors, vertical and/or short take-off and landing (V/STOL) aircraft, and small unmanned aerial vehicles (UAVs). The author is most well known in the rotorcraft community due to his affiliation with the U.S. Army AeroFlightDynamics Directorate (AFDD) and their involvement in numerous military and civil rotorcraft programs over the last few decades. The frequency-domain approach is well suited for rotorcraft system identification and is prevalent throughout the rotorcraft industry. Although the examples in the text are weighted more toward rotorcraft, it should be noted that the second edition includes a variety of new fixed-wing examples, making the latest edition more suitable for the general aircraft community. The material in the book is very much linked to the software package Comprehensive Identification from Frequency Responses (CIFER), which was developed by the author's group at AFDD. Several chapters in the book have a direct correlation with specific components of the software, and virtually all of the example results are produced by CIFER. The second edition has been updated to be compatible with the latest version of CIFER, including its updated user interface. The text was never intended to be a software user’s manual, but since the examples in the book are inherently tied to CIFER, reference to the detailed operation of the software is inevitable. In general, the improvements in the software also translate into improved readability and accessibility of the text.

Rotorcraft system identification: a time/frequency domain approach

The availability of accurate models for helicopter aeromechanics is becoming more and more important, as rotorcraft flight control systems have to meet progressively more stringent performance requirements: as the required control bandwidth increases, model accuracy becomes a vital part of the design problem. In this paper, the results of a joint industry-academia research project aimed at developing a novel time/frequency domain approach to rotorcraft model identification will be presented and discussed. The proposed approach will be illustrated by means of a case study based on data collected during piloted simulations of a state-of-the-art flight dynamics code.

Aircraft and Rotorcraft System Identification, Engineering Methods with Flight-Test Examples, 2nd Edition

Aircraft and Rotorcraft System Identification, Engineering Methods with Flight-Test Examples, <i>2nd Edition</i>

Aircraft and Rotorcraft System Identification: Engineering Methods with Flight Test Examples (M.B. Tischler et al.; 2006) [Bookshelf

The world of aircraft system identification is divided into two camps, namely, those who use time-domain methods and those who use frequency-domain methods. Tischler and Remple are firmly in the frequency-domain camp. and their entire book is dedicated to this approach to system identification. The book also features the software package Comprehensive Identification from Frequency Responses (CIFER), which was developed by Tischler's group and is widely used throughout the rotorcraft industry. Topics covered in the text include: an overview of the aircraft system identification process and a review of basic concepts; an overview of the frequency-domain method; an overview of the CIFER software; details of collecting and validating flight test data; the theory and implementation of frequency-domain identification methods incorporated in the CIFER software; state-space models; time-domain verification; and issues relating to the development of high-order dynamic models of rotorcraft, and, in particular, models that involve rotor-body coupling. The book presents numerous examples with real flight test data. It is an essential reference for those working in system identification of rotorcraft and anyone who is using CIFER. The book might also be useful to those engineers considering the use of frequency-domain methods for system identification. It could possibly serve as a textbook for a special topics course.

Rotorcraft Parameter Identification from Real Time Flight Data

Rotorcraft system identification involves the derivation of the model structure and parameters, such as aerodynamic stability and control derivatives, from flight-test results. Accurate rotorcraft system identification often requires higher order mathematical models. However, system identification becomes difficult and complicated as the number of modeling degrees of freedom are increased. In the present work, a new method for rotorcraft parameter estimation based on the application of a radial basis function network is proposed. The radial basis function networkbased technique does not require a mathematical model of the helicopter, and the rotorcraft parameters can be directly computed from the flight data. The radial basis function network is found to give results in the same range as obtained from conventional parameter estimation techniques, such as the maximum likelihood method. Results obtained using the radial basis function network approach are compared to published research on the BO 105 helicopter and found to be in good agreement.

Book Review: Aircraft and Rotorcraft System Identification Engineering Methods with Flight-Test Examples by Dr. Mark B. Tischler and Robert K. Remple

Book Review: Aircraft and Rotorcraft System Identification Engineering Methods with Flight-Test Examples by Dr. Mark B. Tischler and Robert K. Remple

Advances in rotorcraft system identification

System identification can best be described as the extraction of system characteristics from measured flight test data. Therefore it provides an excellent tool for determining and improving mathematical models for a wide range of applications. The increasing need for accurate models for the design of high bandwidth control systems for rotorcraft has initiated a high interest in and a more intensive use of system identification. This development was supported by the AGARD FVP Working Group 18 on ‘Rotorcraft System Identification’, which brought together specialists from research organisations and industry, tasked with exploring the potential of this tool. In the Group, the full range of identification approaches was applied to dedicated helicopter flight-test-data including data quality checking and the determination and verification of flight mechanical models. It was mainly concentrated on the identification of six degrees of freedom rigid body models, which provide a realistic description of the rotorcraft dynamics for the lower and medium frequency range. The accomplishment of the Working Group has increased the demand for applying these techniques more routinely and, in addition, for extending the model order by including explicit rotor degrees of freedom. Such models also accurately characterize the higher frequency range needed for high bandwidth control system designs. In the specific case of the DLR In-Flight Simulator BO 105 ATTHeS, the application of the identified higher order models for the model-following control system was a major prerequisite for the obtained high simulation quality.

Frequency-Response Method for Rotorcraft System Identification: Flight Applications to BO 105 Coupled Rotor/Fuselage Dynamics

Frequency-Response Method for Rotorcraft System Identification: Flight Applications to BO 105 Coupled Rotor/Fuselage Dynamics

Frequency‐Response Method for Rotorcraft System Identification: Flight Applications to BO 105 Coupled Rotor/Fuselage Dynamics

Frequency‐Response Method for Rotorcraft System Identification: Flight Applications to BO 105 Coupled Rotor/Fuselage Dynamics