Numerical Data Fitting in Dynamical Systems

Numerical Data Fitting in Dynamical Systems PDF Author: Klaus Schittkowski
Publisher: Springer Science & Business Media
ISBN: 9781402010798
Category : Computers
Languages : en
Pages : 416

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Book Description
Real life phenomena in engineering, natural, or medical sciences are often described by a mathematical model with the goal to analyze numerically the behaviour of the system. Advantages of mathematical models are their cheap availability, the possibility of studying extreme situations that cannot be handled by experiments, or of simulating real systems during the design phase before constructing a first prototype. Moreover, they serve to verify decisions, to avoid expensive and time consuming experimental tests, to analyze, understand, and explain the behaviour of systems, or to optimize design and production. As soon as a mathematical model contains differential dependencies from an additional parameter, typically the time, we call it a dynamical model. There are two key questions always arising in a practical environment: 1 Is the mathematical model correct? 2 How can I quantify model parameters that cannot be measured directly? In principle, both questions are easily answered as soon as some experimental data are available. The idea is to compare measured data with predicted model function values and to minimize the differences over the whole parameter space. We have to reject a model if we are unable to find a reasonably accurate fit. To summarize, parameter estimation or data fitting, respectively, is extremely important in all practical situations, where a mathematical model and corresponding experimental data are available to describe the behaviour of a dynamical system.

Numerical Data Fitting in Dynamical Systems

Numerical Data Fitting in Dynamical Systems PDF Author: Klaus Schittkowski
Publisher: Springer Science & Business Media
ISBN: 9781402010798
Category : Computers
Languages : en
Pages : 416

Get Book Here

Book Description
Real life phenomena in engineering, natural, or medical sciences are often described by a mathematical model with the goal to analyze numerically the behaviour of the system. Advantages of mathematical models are their cheap availability, the possibility of studying extreme situations that cannot be handled by experiments, or of simulating real systems during the design phase before constructing a first prototype. Moreover, they serve to verify decisions, to avoid expensive and time consuming experimental tests, to analyze, understand, and explain the behaviour of systems, or to optimize design and production. As soon as a mathematical model contains differential dependencies from an additional parameter, typically the time, we call it a dynamical model. There are two key questions always arising in a practical environment: 1 Is the mathematical model correct? 2 How can I quantify model parameters that cannot be measured directly? In principle, both questions are easily answered as soon as some experimental data are available. The idea is to compare measured data with predicted model function values and to minimize the differences over the whole parameter space. We have to reject a model if we are unable to find a reasonably accurate fit. To summarize, parameter estimation or data fitting, respectively, is extremely important in all practical situations, where a mathematical model and corresponding experimental data are available to describe the behaviour of a dynamical system.

Identification of Dynamic Systems

Identification of Dynamic Systems PDF Author: Rolf Isermann
Publisher: Springer
ISBN: 9783540871552
Category : Technology & Engineering
Languages : en
Pages : 705

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Book Description
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.

Numerical Methods for Bifurcations of Dynamical Equilibria

Numerical Methods for Bifurcations of Dynamical Equilibria PDF Author: Willy J. F. Govaerts
Publisher: SIAM
ISBN: 9780898719543
Category : Mathematics
Languages : en
Pages : 384

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Book Description
Dynamical systems arise in all fields of applied mathematics. The author focuses on the description of numerical methods for the detection, computation, and continuation of equilibria and bifurcation points of equilibria of dynamical systems. This subfield has the particular attraction of having links with the geometric theory of differential equations, numerical analysis, and linear algebra.

Dynamical Systems: Theoretical and Experimental Analysis

Dynamical Systems: Theoretical and Experimental Analysis PDF Author: Jan Awrejcewicz
Publisher: Springer
ISBN: 3319424084
Category : Mathematics
Languages : en
Pages : 424

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Book Description
The book is the second volume of a collection of contributions devoted to analytical, numerical and experimental techniques of dynamical systems, presented at the international conference "Dynamical Systems: Theory and Applications," held in Łódź, Poland on December 7-10, 2015. The studies give deep insight into new perspectives in analysis, simulation, and optimization of dynamical systems, emphasizing directions for future research. Broadly outlined topics covered include: bifurcation and chaos in dynamical systems, asymptotic methods in nonlinear dynamics, dynamics in life sciences and bioengineering, original numerical methods of vibration analysis, control in dynamical systems, stability of dynamical systems, vibrations of lumped and continuous sytems, non-smooth systems, engineering systems and differential equations, mathematical approaches to dynamical systems, and mechatronics.

Numerical Data Fitting in Dynamical Systems

Numerical Data Fitting in Dynamical Systems PDF Author: Klaus Schittkowski
Publisher: Springer Science & Business Media
ISBN: 1441957626
Category : Computers
Languages : en
Pages : 406

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Book Description
Real life phenomena in engineering, natural, or medical sciences are often described by a mathematical model with the goal to analyze numerically the behaviour of the system. Advantages of mathematical models are their cheap availability, the possibility of studying extreme situations that cannot be handled by experiments, or of simulating real systems during the design phase before constructing a first prototype. Moreover, they serve to verify decisions, to avoid expensive and time consuming experimental tests, to analyze, understand, and explain the behaviour of systems, or to optimize design and production. As soon as a mathematical model contains differential dependencies from an additional parameter, typically the time, we call it a dynamical model. There are two key questions always arising in a practical environment: 1 Is the mathematical model correct? 2 How can I quantify model parameters that cannot be measured directly? In principle, both questions are easily answered as soon as some experimental data are available. The idea is to compare measured data with predicted model function values and to minimize the differences over the whole parameter space. We have to reject a model if we are unable to find a reasonably accurate fit. To summarize, parameter estimation or data fitting, respectively, is extremely important in all practical situations, where a mathematical model and corresponding experimental data are available to describe the behaviour of a dynamical system.

Scientific and Technical Aerospace Reports

Scientific and Technical Aerospace Reports PDF Author:
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 818

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Book Description


Neural Network Modeling and Identification of Dynamical Systems

Neural Network Modeling and Identification of Dynamical Systems PDF Author: Yury Tiumentsev
Publisher: Academic Press
ISBN: 0128154306
Category : Science
Languages : en
Pages : 334

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Book Description
Neural Network Modeling and Identification of Dynamical Systems presents a new approach on how to obtain the adaptive neural network models for complex systems that are typically found in real-world applications. The book introduces the theoretical knowledge available for the modeled system into the purely empirical black box model, thereby converting the model to the gray box category. This approach significantly reduces the dimension of the resulting model and the required size of the training set. This book offers solutions for identifying controlled dynamical systems, as well as identifying characteristics of such systems, in particular, the aerodynamic characteristics of aircraft. - Covers both types of dynamic neural networks (black box and gray box) including their structure, synthesis and training - Offers application examples of dynamic neural network technologies, primarily related to aircraft - Provides an overview of recent achievements and future needs in this area

Scientific Information Bulletin

Scientific Information Bulletin PDF Author:
Publisher:
ISBN:
Category : Research
Languages : en
Pages : 708

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Book Description


EngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization

EngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization PDF Author: H.C. Rodrigues
Publisher: Springer
ISBN: 3319977733
Category : Technology & Engineering
Languages : en
Pages : 1486

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Book Description
The papers in this volume focus on the following topics: design optimization and inverse problems, numerical optimization techniques,efficient analysis and reanalysis techniques, sensitivity analysis and industrial applications. The conference EngOpt brings together engineers, applied mathematicians and computer scientists working on research, development and practical application of optimization methods in all engineering disciplines and applied sciences.

Topics in Nonlinear Dynamics, Volume 3

Topics in Nonlinear Dynamics, Volume 3 PDF Author: D. Adams
Publisher: Springer Science & Business Media
ISBN: 1461424151
Category : Technology & Engineering
Languages : en
Pages : 330

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Book Description
Topics in Nonlinear Dynamics, Volume 3, Proceedings of the 30th IMAC, A Conference and Exposition on Structural Dynamics, 2012, the third volume of six from the Conference, brings together 26 contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Structural Dynamics, including papers on: Application of Nonlinearities: Aerospace Structures Nonlinear Dynamics Effects Under Shock Loading Application of Nonlinearities: Vibration Reduction Nonlinear Dynamics: Testing Nonlinear Dynamics: Simulation Nonlinear Dynamics: Identification Nonlinear Dynamics: Localization