Applied System Identification

Author: Jer-Nan Juang
Publisher:
ISBN: 013079211X
Size: 12.55 MB
Format: PDF, Docs
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Effective system identification includes the underlying methodologies, computational procedures, and their implementation. To this end, this volume presents readers with the mathematical background required to participate in the growing field of system identification as applied to engineering systems. Author Jer-Nan Juang provides a common basis for understanding the techniques developed under various disciplines. In addition, he attempts to bring the discipline of system identification up to date. Specifically Applied System Identification: provides an overview of the disciplines of modal testing used in structural engineering and system identification; presents time- and frequency-domain models used in the disciplines of structures and controls; identifies basic concepts and properties of the frequency response function; features a unified mathematical framework based on the theory of system realization to correlate some of the existing time-domain methods commonly used in modal testing; introduces readers to a new way of interpreting the input/output relationship via an observer for identification of a system model and its corresponding observer to characterize system uncertainties; proposes a simple, yet effective way of curve-fitting the frequency response data and of constructing a system model via matrix-fraction description methods; considers the identification problem of a system operating in closed-loop with an existing feedback controller; develops a unified mathematical framework to derive recursive algorithms for the fast transversal filter and the least-squares lattice filter. Whether used as a textbook or as an addition to your personal reference library, Applied System Identification offers an ideal opportunity to build a bridge between the disciplines of system identification as applied to controls and to modal testing.

System Identification Sysid 03

Author: P. M. J. van den Hof
Publisher: Elsevier
ISBN: 0080437095
Size: 11.63 MB
Format: PDF, Docs
View: 61

The scope of the symposium covers all major aspects of system identification, experimental modelling, signal processing and adaptive control, ranging from theoretical, methodological and scientific developments to a large variety of (engineering) application areas. It is the intention of the organizers to promote SYSID 2003 as a meeting place where scientists and engineers from several research communities can meet to discuss issues related to these areas. Relevant topics for the symposium program include: Identification of linear and multivariable systems, identification of nonlinear systems, including neural networks, identification of hybrid and distributed systems, Identification for control, experimental modelling in process control, vibration and modal analysis, model validation, monitoring and fault detection, signal processing and communication, parameter estimation and inverse modelling, statistical analysis and uncertainty bounding, adaptive control and data-based controller tuning, learning, data mining and Bayesian approaches, sequential Monte Carlo methods, including particle filtering, applications in process control systems, motion control systems, robotics, aerospace systems, bioengineering and medical systems, physical measurement systems, automotive systems, econometrics, transportation and communication systems *Provides the latest research on System Identification *Contains contributions written by experts in the field *Part of the IFAC Proceedings Series which provides a comprehensive overview of the major topics in control engineering.

Applied Control Systems Design

Author: Magdi S. Mahmoud
Publisher: Springer Science & Business Media
ISBN: 9781447128793
Size: 10.13 MB
Format: PDF, ePub
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Applied Control System Design examines several methods for building up systems models based on real experimental data from typical industrial processes and incorporating system identification techniques. The text takes a comparative approach to the models derived in this way judging their suitability for use in different systems and under different operational circumstances. A broad spectrum of control methods including various forms of filtering, feedback and feedforward control is applied to the models and the guidelines derived from the closed-loop responses are then composed into a concrete self-tested recipe to serve as a check-list for industrial engineers or control designers. System identification and control design are given equal weight in model derivation and testing to reflect their equality of importance in the proper design and optimization of high-performance control systems. Readers’ assimilation of the material discussed is assisted by the provision of problems and examples. Most of these exercises use MATLAB® to make computation and visualization more straightforward. Applied Control System Design will be of interest to academic researchers for its comparison of different systems models and their response to different control methods and will assist graduate students in learning the practical necessities of advanced control system design. The consistent reference to real systems coupled with self-learning tools will assist control practitioners who wish to keep up to date with the latest control design ideas.

Identification Of Dynamic Systems

Author: Rolf Isermann
Publisher: Springer Science & Business Media
ISBN: 3540788794
Size: 15.58 MB
Format: PDF, ePub
View: 62

Precise dynamic models of processes are required for many applications, ranging from control engineering to the natural sciences and economics. Frequently, such precise models cannot be derived using theoretical considerations alone. Therefore, they must be determined experimentally. This book treats the determination of dynamic models based on measurements taken at the process, which is known as system identification or process identification. Both offline and online methods are presented, i.e. methods that post-process the measured data as well as methods that provide models during the measurement. The book is theory-oriented and application-oriented and most methods covered have been used successfully in practical applications for many different processes. Illustrative examples in this book with real measured data range from hydraulic and electric actuators up to combustion engines. Real experimental data is also provided on the Springer webpage, allowing readers to gather their first experience with the methods presented in this book. Among others, the book covers the following subjects: determination of the non-parametric frequency response, (fast) Fourier transform, correlation analysis, parameter estimation with a focus on the method of Least Squares and modifications, identification of time-variant processes, identification in closed-loop, identification of continuous time processes, and subspace methods. Some methods for nonlinear system identification are also considered, such as the Extended Kalman filter and neural networks. The different methods are compared by using a real three-mass oscillator process, a model of a drive train. For many identification methods, hints for the practical implementation and application are provided. The book is intended to meet the needs of students and practicing engineers working in research and development, design and manufacturing.

Flight Dynamics And System Identification For Modern Feedback Control

Author: Jared A Grauer
Publisher: Elsevier
ISBN: 9780857094674
Size: 13.43 MB
Format: PDF, Mobi
View: 31

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

Subspace Methods For System Identification

Author: Tohru Katayama
Publisher: Springer Science & Business Media
ISBN: 9781846281587
Size: 11.20 MB
Format: PDF, Kindle
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An in-depth introduction to subspace methods for system identification in discrete-time linear systems thoroughly augmented with advanced and novel results, this text is structured into three parts. Part I deals with the mathematical preliminaries: numerical linear algebra; system theory; stochastic processes; and Kalman filtering. Part II explains realization theory as applied to subspace identification. Stochastic realization results based on spectral factorization and Riccati equations, and on canonical correlation analysis for stationary processes are included. Part III demonstrates the closed-loop application of subspace identification methods. Subspace Methods for System Identification is an excellent reference for researchers and a useful text for tutors and graduate students involved in control and signal processing courses. It can be used for self-study and will be of interest to applied scientists or engineers wishing to use advanced methods in modeling and identification of complex systems.