Non Linear Feedback Neural Networks PDF Download
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| Author | : Jagannathan Sarangapani |
| Publisher | : CRC Press |
| Total Pages | : 624 |
| Release | : 2018-10-03 |
| Genre | : Technology & Engineering |
| ISBN | : 1420015451 |
Download Neural Network Control of Nonlinear Discrete-Time Systems Book in PDF, ePub and Kindle
Intelligent systems are a hallmark of modern feedback control systems. But as these systems mature, we have come to expect higher levels of performance in speed and accuracy in the face of severe nonlinearities, disturbances, unforeseen dynamics, and unstructured uncertainties. Artificial neural networks offer a combination of adaptability, parallel processing, and learning capabilities that outperform other intelligent control methods in more complex systems. Borrowing from Biology Examining neurocontroller design in discrete-time for the first time, Neural Network Control of Nonlinear Discrete-Time Systems presents powerful modern control techniques based on the parallelism and adaptive capabilities of biological nervous systems. At every step, the author derives rigorous stability proofs and presents simulation examples to demonstrate the concepts. Progressive Development After an introduction to neural networks, dynamical systems, control of nonlinear systems, and feedback linearization, the book builds systematically from actuator nonlinearities and strict feedback in nonlinear systems to nonstrict feedback, system identification, model reference adaptive control, and novel optimal control using the Hamilton-Jacobi-Bellman formulation. The author concludes by developing a framework for implementing intelligent control in actual industrial systems using embedded hardware. Neural Network Control of Nonlinear Discrete-Time Systems fosters an understanding of neural network controllers and explains how to build them using detailed derivations, stability analysis, and computer simulations.
| Author | : Mohd. Samar Ansari |
| Publisher | : Springer |
| Total Pages | : 217 |
| Release | : 2013-09-03 |
| Genre | : Technology & Engineering |
| ISBN | : 813221563X |
Download Non-Linear Feedback Neural Networks Book in PDF, ePub and Kindle
This book aims to present a viable alternative to the Hopfield Neural Network (HNN) model for analog computation. It is well known the standard HNN suffers from problems of convergence to local minima, and requirement of a large number of neurons and synaptic weights. Therefore, improved solutions are needed. The non-linear synapse neural network (NoSyNN) is one such possibility and is discussed in detail in this book. This book also discusses the applications in computationally intensive tasks like graph coloring, ranking, and linear as well as quadratic programming. The material in the book is useful to students, researchers and academician working in the area of analog computation.
| Author | : Alexander S. Poznyak |
| Publisher | : World Scientific |
| Total Pages | : 464 |
| Release | : 2001 |
| Genre | : Science |
| ISBN | : 9789812811295 |
Download Differential Neural Networks for Robust Nonlinear Control Book in PDF, ePub and Kindle
This book deals with continuous time dynamic neural networks theory applied to the solution of basic problems in robust control theory, including identification, state space estimation (based on neuro-observers) and trajectory tracking. The plants to be identified and controlled are assumed to be a priori unknown but belonging to a given class containing internal unmodelled dynamics and external perturbations as well. The error stability analysis and the corresponding error bounds for different problems are presented. The effectiveness of the suggested approach is illustrated by its application to various controlled physical systems (robotic, chaotic, chemical, etc.). Contents: Theoretical Study: Neural Networks Structures; Nonlinear System Identification: Differential Learning; Sliding Mode Identification: Algebraic Learning; Neural State Estimation; Passivation via Neuro Control; Neuro Trajectory Tracking; Neurocontrol Applications: Neural Control for Chaos; Neuro Control for Robot Manipulators; Identification of Chemical Processes; Neuro Control for Distillation Column; General Conclusions and Future Work; Appendices: Some Useful Mathematical Facts; Elements of Qualitative Theory of ODE; Locally Optimal Control and Optimization. Readership: Graduate students, researchers, academics/lecturers and industrialists in neural networks.
| Author | : Murad Abu-Khalaf |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 218 |
| Release | : 2006-08-02 |
| Genre | : Technology & Engineering |
| ISBN | : 1846283507 |
Download Nonlinear H2/H-Infinity Constrained Feedback Control Book in PDF, ePub and Kindle
This book provides techniques to produce robust, stable and useable solutions to problems of H-infinity and H2 control in high-performance, non-linear systems for the first time. The book is of importance to control designers working in a variety of industrial systems. Case studies are given and the design of nonlinear control systems of the same caliber as those obtained in recent years using linear optimal and bounded-norm designs is explained.
| Author | : Johan A.K. Suykens |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 242 |
| Release | : 2012-12-06 |
| Genre | : Technology & Engineering |
| ISBN | : 1475724934 |
Download Artificial Neural Networks for Modelling and Control of Non-Linear Systems Book in PDF, ePub and Kindle
Artificial neural networks possess several properties that make them particularly attractive for applications to modelling and control of complex non-linear systems. Among these properties are their universal approximation ability, their parallel network structure and the availability of on- and off-line learning methods for the interconnection weights. However, dynamic models that contain neural network architectures might be highly non-linear and difficult to analyse as a result. Artificial Neural Networks for Modelling and Control of Non-Linear Systems investigates the subject from a system theoretical point of view. However the mathematical theory that is required from the reader is limited to matrix calculus, basic analysis, differential equations and basic linear system theory. No preliminary knowledge of neural networks is explicitly required. The book presents both classical and novel network architectures and learning algorithms for modelling and control. Topics include non-linear system identification, neural optimal control, top-down model based neural control design and stability analysis of neural control systems. A major contribution of this book is to introduce NLq Theory as an extension towards modern control theory, in order to analyze and synthesize non-linear systems that contain linear together with static non-linear operators that satisfy a sector condition: neural state space control systems are an example. Moreover, it turns out that NLq Theory is unifying with respect to many problems arising in neural networks, systems and control. Examples show that complex non-linear systems can be modelled and controlled within NLq theory, including mastering chaos. The didactic flavor of this book makes it suitable for use as a text for a course on Neural Networks. In addition, researchers and designers will find many important new techniques, in particular NLq emTheory, that have applications in control theory, system theory, circuit theory and Time Series Analysis.
| Author | : Rui J. P. DeFigueiredo |
| Publisher | : |
| Total Pages | : 240 |
| Release | : 1993 |
| Genre | : Mathematics |
| ISBN | : |
Download Nonlinear Feedback Control Systems Book in PDF, ePub and Kindle
Nonlinear analytic mappings. Nonlinear Lipschitz operators. Nonlinear feedback systems. Optimal design of nonlinear feedback control systems. Coprime factorizations of nonlinear mappings for control systems. Nonlinear system identification.
| Author | : Irwin W. Sandberg |
| Publisher | : John Wiley & Sons |
| Total Pages | : 316 |
| Release | : 2001-02-21 |
| Genre | : Technology & Engineering |
| ISBN | : 9780471349112 |
Download Nonlinear Dynamical Systems Book in PDF, ePub and Kindle
Sechs erfahrene Autoren beschreiben in diesem Band ein Spezialgebiet der neuronalen Netze mit Anwendungen in der Signalsteuerung, Signalverarbeitung und Zeitreihenanalyse. Ein zeitgemäßer Beitrag zur Behandlung nichtlinear-dynamischer Systeme!
| Author | : F W Lewis |
| Publisher | : CRC Press |
| Total Pages | : 470 |
| Release | : 1998-11-30 |
| Genre | : Technology & Engineering |
| ISBN | : 9780748405961 |
Download Neural Network Control Of Robot Manipulators And Non-Linear Systems Book in PDF, ePub and Kindle
There has been great interest in "universal controllers" that mimic the functions of human processes to learn about the systems they are controlling on-line so that performance improves automatically. Neural network controllers are derived for robot manipulators in a variety of applications including position control, force control, link flexibility stabilization and the management of high-frequency joint and motor dynamics. The first chapter provides a background on neural networks and the second on dynamical systems and control. Chapter three introduces the robot control problem and standard techniques such as torque, adaptive and robust control. Subsequent chapters give design techniques and Stability Proofs For NN Controllers For Robot Arms, Practical Robotic systems with high frequency vibratory modes, force control and a general class of non-linear systems. The last chapters are devoted to discrete- time NN controllers. Throughout the text, worked examples are provided.
| Author | : Kasra Esfandiari |
| Publisher | : Springer Nature |
| Total Pages | : 181 |
| Release | : 2021-06-18 |
| Genre | : Technology & Engineering |
| ISBN | : 3030731367 |
Download Neural Network-Based Adaptive Control of Uncertain Nonlinear Systems Book in PDF, ePub and Kindle
The focus of this book is the application of artificial neural networks in uncertain dynamical systems. It explains how to use neural networks in concert with adaptive techniques for system identification, state estimation, and control problems. The authors begin with a brief historical overview of adaptive control, followed by a review of mathematical preliminaries. In the subsequent chapters, they present several neural network-based control schemes. Each chapter starts with a concise introduction to the problem under study, and a neural network-based control strategy is designed for the simplest case scenario. After these designs are discussed, different practical limitations (i.e., saturation constraints and unavailability of all system states) are gradually added, and other control schemes are developed based on the primary scenario. Through these exercises, the authors present structures that not only provide mathematical tools for navigating control problems, but also supply solutions that are pertinent to real-life systems.
| Author | : Anna Esposito |
| Publisher | : Springer |
| Total Pages | : 318 |
| Release | : 2018-07-21 |
| Genre | : Technology & Engineering |
| ISBN | : 3319950983 |
Download Neural Advances in Processing Nonlinear Dynamic Signals Book in PDF, ePub and Kindle
This book proposes neural networks algorithms and advanced machine learning techniques for processing nonlinear dynamic signals such as audio, speech, financial signals, feedback loops, waveform generation, filtering, equalization, signals from arrays of sensors, and perturbations in the automatic control of industrial production processes. It also discusses the drastic changes in financial, economic, and work processes that are currently being experienced by the computational and engineering sciences community. Addresses key aspects, such as the integration of neural algorithms and procedures for the recognition, the analysis and detection of dynamic complex structures and the implementation of systems for discovering patterns in data, the book highlights the commonalities between computational intelligence (CI) and information and communications technologies (ICT) to promote transversal skills and sophisticated processing techniques. This book is a valuable resource for a. The academic research community b. The ICT market c. PhD students and early stage researchers d. Companies, research institutes e. Representatives from industry and standardization bodies
