THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

A method, called the Eigensystem Realization Algorithm (ERA), is developed for modal parameter identification and model reduction of dynamic systems from test data. A new approach is introduced in conjunction with the singular value decomposition technique to derive the basic formulation of minimum order realization which is an extended version of the Ho-Kalman algorithm. The basic formulation is then transformed into modal space for modal parameter identification. Two accuracy indicators are developed to quantitatively identify the system modes and noise modes. For illustration of the algorithm, examples are shown using simulation data and experimental data for a rectangular grid structure.

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An eigensystem realization algorithm for modal parameter identification and model reduction

Aircraft wings are a compromise that allows the aircraft to fly at a range of flight conditions, but the performance at each condition is sub-optimal. The ability of a wing surface to change its geometry during flight has interested researchers and designers over the years as this reduces the design compromises required. Morphing is the short form for metamorphose; however, there is neither an exact definition nor an agreement between the researchers about the type or the extent of the geometrical changes necessary to qualify an aircraft for the title ‘shape morphing.’ Geometrical parameters that can be affected by morphing solutions can be categorized into: planform alteration (span, sweep, and chord), out-of-plane transformation (twist, dihedral/gull, and span-wise bending), and airfoil adjustment (camber and thickness). Changing the wing shape or geometry is not new. Historically, morphing solutions always led to penalties in terms of cost, complexity, or weight, although in certain circumstances, thes...

A Review of Morphing Aircraft

Originally introduced in the fluid mechanics community, dynamic mode decomposition (DMD) has emerged as a powerful tool for analyzing the dynamics of nonlinear systems. However, existing DMD theory deals primarily with sequential time series for which the measurement dimension is much larger than the number of measurements taken. We present a theoretical framework in which we define DMD as the eigendecomposition of an approximating linear operator. This generalizes DMD to a larger class of datasets, including nonsequential time series. We demonstrate the utility of this approach by presenting novel sampling strategies that increase computational efficiency and mitigate the effects of noise, respectively. We also introduce the concept of linear consistency, which helps explain the potential pitfalls of applying DMD to rank-deficient datasets, illustrating with examples. Such computations are not considered in the existing literature, but can be understood using our more general framework. In addition, we show that our theory strengthens the connections between DMD and Koopman operator theory. It also establishes connections between DMD and other techniques, including the eigensystem realization algorithm (ERA), a system identification method, and linear inverse modeling (LIM), a method from climate science. We show that under certain conditions, DMD is equivalent to LIM.

On Dynamic Mode Decomposition: Theory and Applications

We develop a new method which extends dynamic mode decomposition (DMD) to incorporate the effect of control to extract low-order models from high-dimensional, complex systems. DMD finds spatial-temporal coherent modes, connects local-linear analysis to nonlinear operator theory, and provides an equation-free architecture which is compatible with compressive sensing. In actuated systems, DMD is incapable of producing an input-output model; moreover, the dynamics and the modes will be corrupted by external forcing. Our new method, dynamic mode decomposition with control (DMDc), capitalizes on all of the advantages of DMD and provides the additional innovation of being able to disambiguate between the underlying dynamics and the effects of actuation, resulting in accurate input-output models. The method is data-driven in that it does not require knowledge of the underlying governing equations---only snapshots in time of observables and actuation data from historical, experimental, or black-box simulations. W...

https://epubs.siam.org/doi/pdf/10.1137/15M1013857

Dynamic Mode Decomposition with Control

The paper is concerned with the on-line identification of system Markov parameters using observers. Two types of parameters are sought: the forward system parameters, which provide estimates of the outputs for given inputs, and inverse system parameters, which provide estimates of inputs for given outputs. A procedure is proposed which uses the inverse system to generate commands that produce a desired system response. The feasibility of the procedure is demonstrated using test results from an implementation of a truss structure fitted with piezoelectric actuators and collocated strain gauges.

On-line identification of forward/inverse systems for adaptive control applications

A commercially available linear stepper motor is applied as a reaction mass (RM) actuator. With the actuator operating in the (RM) relative-velocity command mode, open-loop and closed-loop testing is performed to determine operational limits. With the actuator mounted on a simple beam structure, root strain, RM acceleration, or beam acceleration is used in the feedback loop to augment the structural damping. The RM relative position is also used as feedback to ensure that the RM remains centered.

Analysis and application of a velocity command motor as a reaction mass actuator

Air drag forces are introduced into the equations for a slewing control maneuver of a flexible structure to assess the effects of atmosphere on the controller design. Simulated modal parameters and transient responses are compared with experiments in normal atmosphere and vacuum. Analytical techniques for control laws are examined and verified. Physical insight into the air damping is gained so that results in vacuum can be extrapolated from results in air.

Effects of atmosphere on slewing control of a flexible structure

This paper presents a procedure for modeling structures containing piezoelectric actuators using MSCMASTRAN and MATLAB. The paper describes the utility and functionality of one set of validated modeling tools. The tools described herein use MSCMASTRAN to model the structure with piezoelectric actuators and a thermally induced strain to model straining of the actuators due to an applied voltage field. MATLAB scripts are used to assemble the dynamic equations and to generate frequency response functions. The application of these tools is discussed using a cantilever aluminum beam with a surface mounted piezoelectric actuator as a sample problem. Software in the form of MSCINASTRAN DMAP input commands, MATLAB scripts, and a step-by-step procedure to solve the example problem are provided. Analysis results are generated in terms of frequency response functions from deflection and strain data as a function of input voltage to the actuator.

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Piezoelectric Actuator Modeling Using MSC/NASTRAN and MATLAB

The first test flight of NASA’s Ares I crew launch vehicle, called Ares I-X, is scheduled for launch in 2009. Ares I-X will use a 4-segment reusable solid rocket booster from the Space Shuttle heritage with mass simulators for the 5th segment, upper stage, crew module and launch abort system. Flight test data will provide important information on ascent loads, vehicle control, separation, and first stage reentry dynamics. As part of hardware verification, a series of modal tests were designed to verify the dynamic finite element model (FEM) used in loads assessments and flight control evaluations. Based on flight control system studies, the critical modes were the first three free-free bending mode pairs. Since a test of the free-free vehicle is not practical within project constraints, modal tests for several configurations in the nominal integration flow were defined to calibrate the FEM. A traceability study by Aerospace Corporation was used to identify the critical modes for the tested configurations. Test configurations included two partial stacks and the full Ares I-X launch vehicle on the Mobile Launcher Platform. This paper provides an overview for companion papers in the Ares I-X Modal Test Session. The requirements flow down, pre-test analysis, constraints and overall test planning are described.

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Lucas G. Horta

Papers

On-line identification of forward/inverse systems for adaptive control applications

Analysis and application of a velocity command motor as a reaction mass actuator

Effects of atmosphere on slewing control of a flexible structure

Piezoelectric Actuator Modeling Using MSC/NASTRAN and MATLAB

Ares I-X Launch Vehicle Modal Test Overview