Structured Uncertainty Bound Determination From Data For Control And Performance Validation

Structured Uncertainty Bound Determination From Data for Control and Performance Validation

Responsive Systems for Active Vibration Control

Structural vibrations have become the critical factor limiting the performance of many engineering systems, typical amplitudes ranging from meters to a few nanometers. Many acoustic nuisances in transportation systems and residential and office buildings are also related to structural vibrations. The active control of such vibrations involves nine orders of magnitude of vibration amplitude, which exerts a profound influence on the technology. Active vibration control is highly multidisciplinary, involving structural vibration, acoustics, signal processing, materials science, and actuator and sensor technology. Chapters 1-3 of this book provide a state-of-the-art introduction to active vibration control, active sound control, and active vibroacoustic control, respectively. Chapter 4 discusses actuator/sensor placement, Chapter 5 deals with robust control of vibrating structures, Chapter 6 discusses finite element modelling of piezoelectric continua and Chapter 7 addresses the latest trends in piezoelectric multiple-degree-of-freedom actuators/sensors. Chapters 8-12 deal with example applications, including semi-active joints, active isolation and health monitoring. Chapter 13 addresses MEMS technology, while Chapter 14 discusses the design of power amplifiers for piezoelectric actuators.

Structured Uncertainty Bound Determination from Data for Control and Performance Validation

This report attempts to document the broad scope of issues that must be satisfactorily resolved before one can expect to methodically obtain, with a reasonable confidence, a near-optimal robust closed loop performance in physical applications. These include elements of signal processing, noise identification, system identification, model validation, and uncertainty modeling. Based on a recently developed methodology involving a parameterization of all model validating uncertainty sets for a given linear fractional transformation (LFT) structure and noise allowance, a new software, Uncertainty Bound Identification (UBID) toolbox, which conveniently executes model validation tests and determine uncertainty bounds from data, has been designed and is currently available. This toolbox also serves to benchmark the current state-of-the-art in uncertainty bound determination and in turn facilitate benchmarking of robust control technology. To help clarify the methodology and use of the new software, two tutorial examples are provided. The first involves the uncertainty characterization of a flexible structure dynamics, and the second example involves a closed loop performance validation of a ducted fan based on an uncertainty bound from data. These examples, along with other simulation and experimental results, also help describe the many factors and assumptions that determine the degree of success in applying robust control theory to practical problems. Lim, Kyong B. Langley Research Center 706-21-71-01