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Applied and Computational Control, Signals, and Circuits: Recent Developments

Posted By: AvaxGenius
Date: 1 Feb 2024 10:51:42
Applied and Computational Control, Signals, and Circuits: Recent Developments

Applied and Computational Control, Signals, and Circuits: Recent Developments by Biswa Nath Datta
English | PDF | 2001 | 298 Pages | ISBN : 0792374029 | 26 MB

Applied and Computational Control, Signals, and Circuits: Recent Developments is an interdisciplinary book blending mathematics, computational mathematics, scientific computing and software engineering with control and systems theory, signal processing, and circuit simulations. The material consists of seven state-of-the-art review chapters, each written by a leading expert in that field. Each of the technical chapters deals exclusively with some of the recent developments involving applications and computations of control, signals and circuits. Also included is a Chapter focusing on the newly developed Fortran-based software library, called SLICOT, for control systems design and analysis.
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Stable Adaptive Neural Network Control

Posted By: AvaxGenius
Date: 6 Aug 2023 16:35:26
Stable Adaptive Neural Network Control

Stable Adaptive Neural Network Control by Shuzhi S. Ge , Chang C. Hang , Tong H. Lee , Tao Zhang
English | PDF | 2002 | 296 Pages | ISBN : 0792375971 | 23.5 MB

Recent years have seen a rapid development of neural network control tech­ niques and their successful applications. Numerous simulation studies and actual industrial implementations show that artificial neural network is a good candidate for function approximation and control system design in solving the control problems of complex nonlinear systems in the presence of different kinds of uncertainties. Many control approaches/methods, reporting inventions and control applications within the fields of adaptive control, neural control and fuzzy systems, have been published in various books, journals and conference proceedings. In spite of these remarkable advances in neural control field, due to the complexity of nonlinear systems, the present research on adaptive neural control is still focused on the development of fundamental methodologies. From a theoretical viewpoint, there is, in general, lack of a firmly mathematical basis in stability, robustness, and performance analysis of neural network adaptive control systems.
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Nonlinear Dynamical Control Systems

Posted By: AvaxGenius
Date: 20 Nov 2022 05:17:26
Nonlinear Dynamical Control Systems

Nonlinear Dynamical Control Systems by Henk Nijmeijer, Arjan Schaft
English | PDF | 1990 | 480 Pages | ISBN : 038797234X | 26.3 MB

This book has recently been retypeset in LaTeX for clearer presentation.
This textbook on the differential geometric approach to nonlinear control grew out of a set of lecture notes, which were prepared for a course on nonlinear system theory, given by us for the first time during the fall semester of 1988. The audience consisted mostly of graduate students , taking part in the Dutch national Graduate Program on Systems and Control.
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Practical Numerical Algorithms for Chaotic Systems (Repost)

Posted By: AvaxGenius
Date: 7 Jun 2022 14:21:07
Practical Numerical Algorithms for Chaotic Systems (Repost)

Practical Numerical Algorithms for Chaotic Systems by Thomas S. Parker
English | PDF | 1989 | 353 Pages | ISBN : 1461281210 | 24.5 MB

One of the basic tenets of science is that deterministic systems are completely predictable-given the initial condition and the equations describing a system, the behavior of the system can be predicted 1 for all time. The discovery of chaotic systems has eliminated this viewpoint. Simply put, a chaotic system is a deterministic system that exhibits random behavior.
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Linear Systems and Optimal Control

Posted By: AvaxGenius
Date: 23 Mar 2022 01:29:39
Linear Systems and Optimal Control

Linear Systems and Optimal Control by Charles K. Chui
English | PDF | 1989 | 162 Pages | ISBN : 3540187375 | 10.9 MB

A knowledge of linear systems provides a firm foundation for the study of optimal control theory and many areas of system theory and signal processing. State-space techniques developed since the early sixties have been proved to be very effective. The main objective of this book is to present a brief and somewhat complete investigation on the theory of linear systems, with emphasis on these techniques, in both continuous-time and discrete-time settings, and to demonstrate an application to the study of elementary (linear and nonlinear) optimal control theory.
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