Identification and Control of Dynamic Systems Via Adaptive Neural Networks

Identification and Control of Dynamic Systems Via Adaptive Neural Networks PDF Author: E. Colina Morles
Publisher:
ISBN:
Category : Automatic control
Languages : en
Pages :

Get Book Here

Book Description

Identification and Control of Dynamic Systems Via Adaptive Neural Networks

Identification and Control of Dynamic Systems Via Adaptive Neural Networks PDF Author: E. Colina Morles
Publisher:
ISBN:
Category : Automatic control
Languages : en
Pages :

Get Book Here

Book Description


Identification and Control of Non-linear Time-varying Dynamical Systems Using Artificial Neural Networks

Identification and Control of Non-linear Time-varying Dynamical Systems Using Artificial Neural Networks PDF Author: Shahar Dror
Publisher:
ISBN:
Category : Adaptive control systems
Languages : en
Pages : 258

Get Book Here

Book Description


Differential Neural Networks for Robust Nonlinear Control

Differential Neural Networks for Robust Nonlinear Control PDF Author: Alexander S. Poznyak
Publisher: World Scientific
ISBN: 9789812811295
Category : Science
Languages : en
Pages : 464

Get Book Here

Book Description
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.

Identification and Control of Dynamic Systems Using Neural Networks

Identification and Control of Dynamic Systems Using Neural Networks PDF Author: S. J. Oh
Publisher:
ISBN:
Category :
Languages : en
Pages :

Get Book Here

Book Description


Adaptive Control of Nonsmooth Dynamic Systems

Adaptive Control of Nonsmooth Dynamic Systems PDF Author: Gang Tao
Publisher: Springer Science & Business Media
ISBN: 9781852333843
Category : Technology & Engineering
Languages : en
Pages : 430

Get Book Here

Book Description
Many of the non-smooth, non-linear phenomena covered in this well-balanced book are of vital importance in almost any field of engineering. Contributors from all over the world ensure that no one area’s slant on the subjects predominates.

Applications of Neural Adaptive Control Technology

Applications of Neural Adaptive Control Technology PDF Author: Jens Kalkkuhl
Publisher: World Scientific
ISBN: 9789810231514
Category : Technology & Engineering
Languages : en
Pages : 328

Get Book Here

Book Description
This book presents the results of the second workshop on Neural Adaptive Control Technology, NACT II, held on September 9-10, 1996, in Berlin. The workshop was organised in connection with a three-year European-Union-funded Basic Research Project in the ESPRIT framework, called NACT, a collaboration between Daimler-Benz (Germany) and the University of Glasgow (Scotland).The NACT project, which began on 1 April 1994, is a study of the fundamental properties of neural-network-based adaptive control systems. Where possible, links with traditional adaptive control systems are exploited. A major aim is to develop a systematic engineering procedure for designing neural controllers for nonlinear dynamic systems. The techniques developed are being evaluated on concrete industrial problems from within the Daimler-Benz group of companies.The aim of the workshop was to bring together selected invited specialists in the fields of adaptive control, nonlinear systems and neural networks. The first workshop (NACT I) took place in Glasgow in May 1995 and was mainly devoted to theoretical issues of neural adaptive control. Besides monitoring further development of theory, the NACT II workshop was focused on industrial applications and software tools. This context dictated the focus of the book and guided the editors in the choice of the papers and their subsequent reshaping into substantive book chapters. Thus, with the project having progressed into its applications stage, emphasis is put on the transfer of theory of neural adaptive engineering into industrial practice. The contributors are therefore both renowned academics and practitioners from major industrial users of neurocontrol.

Identification and Control of Dynamic Systems Using Neural Networks

Identification and Control of Dynamic Systems Using Neural Networks PDF Author: E. Colina Morles
Publisher:
ISBN:
Category :
Languages : en
Pages :

Get Book Here

Book Description


Adaptive Control with Recurrent High-order Neural Networks

Adaptive Control with Recurrent High-order Neural Networks PDF Author: George A. Rovithakis
Publisher: Springer Science & Business Media
ISBN: 1447107853
Category : Computers
Languages : en
Pages : 203

Get Book Here

Book Description
The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies ... , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. Neural networks is one of those areas where an initial burst of enthusiasm and optimism leads to an explosion of papers in the journals and many presentations at conferences but it is only in the last decade that significant theoretical work on stability, convergence and robustness for the use of neural networks in control systems has been tackled. George Rovithakis and Manolis Christodoulou have been interested in these theoretical problems and in the practical aspects of neural network applications to industrial problems. This very welcome addition to the Advances in Industrial Control series provides a succinct report of their research. The neural network model at the core of their work is the Recurrent High Order Neural Network (RHONN) and a complete theoretical and simulation development is presented. Different readers will find different aspects of the development of interest. The last chapter of the monograph discusses the problem of manufacturing or production process scheduling.

IDENTIFICATION AND CONTROL OF DYNAMICAL SYSTEMS USING NEURAL NETWORKS.

IDENTIFICATION AND CONTROL OF DYNAMICAL SYSTEMS USING NEURAL NETWORKS. PDF Author: K. NARENDA
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

Get Book Here

Book Description


Stable Adaptive Control of Unknown Nonlinear Dynamic Systems Using Neural Networks

Stable Adaptive Control of Unknown Nonlinear Dynamic Systems Using Neural Networks PDF Author: Olawale Adetona
Publisher:
ISBN:
Category : Adaptive control systems
Languages : en
Pages : 218

Get Book Here

Book Description