Discrete Time High Order Neural Control

Neural networks have become a well-established methodology as exempli?ed by their applications to identi?cation and control of general nonlinear and complex systems; the use of high order neural networks for modeling and learning has recently increased. Usingneuralnetworks,controlalgorithmscanbedevelopedtoberobustto uncertainties and modeling errors. The most used NN structures are Feedf- ward networks and Recurrent networks. The latter type o?ers a better suited tool to model and control of nonlinear systems. There exist di?erent training algorithms for neural networks, which, h- ever, normally encounter some technical problems such as local minima, slow learning, and high sensitivity to initial conditions, among others. As a viable alternative, new training algorithms, for example, those based on Kalman ?ltering, have been proposed. There already exists publications about trajectory tracking using neural networks; however, most of those works were developed for continuous-time systems. On the other hand, while extensive literature is available for linear discrete-timecontrolsystem,nonlineardiscrete-timecontroldesigntechniques have not been discussed to the same degree. Besides, discrete-time neural networks are better ?tted for real-time implementations.

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  • Author : Edgar N. Sanchez
  • Publisher : Springer Science & Business Media
  • Pages : 110 pages
  • ISBN : 3540782885
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKDiscrete Time High Order Neural Control

Discrete-Time High Order Neural Control

Discrete-Time High Order Neural Control
  • Author : Edgar N. Sanchez,Alma Y. Alanís,Alexander G. Loukianov
  • Publisher : Springer Science & Business Media
  • Release : 29 April 2008
GET THIS BOOKDiscrete-Time High Order Neural Control

Neural networks have become a well-established methodology as exempli?ed by their applications to identi?cation and control of general nonlinear and complex systems; the use of high order neural networks for modeling and learning has recently increased. Usingneuralnetworks,controlalgorithmscanbedevelopedtoberobustto uncertainties and modeling errors. The most used NN structures are Feedf- ward networks and Recurrent networks. The latter type o?ers a better suited tool to model and control of nonlinear systems. There exist di?erent training algorithms for neural

Discrete-Time Neural Observers

Discrete-Time Neural Observers
  • Author : Alma Y. Alanis,Edgar N Sanchez
  • Publisher : Academic Press
  • Release : 06 February 2017
GET THIS BOOKDiscrete-Time Neural Observers

Discrete-Time Neural Observers: Analysis and Applications presents recent advances in the theory of neural state estimation for discrete-time unknown nonlinear systems with multiple inputs and outputs. The book includes rigorous mathematical analyses, based on the Lyapunov approach, that guarantee their properties. In addition, for each chapter, simulation results are included to verify the successful performance of the corresponding proposed schemes. In order to complete the treatment of these schemes, the authors also present simulation and experimental results related to their

Discrete-Time Neural Observers

Discrete-Time Neural Observers
  • Author : Edgar Sanchez,Alma Alanis
  • Publisher : Academic Press
  • Release : 01 March 2017
GET THIS BOOKDiscrete-Time Neural Observers

Discrete-Time Neural Observers: Analysis and Applications presents recent advances in the theory of neural state estimation for discrete-time unknown nonlinear systems with multiple inputs and outputs. The book includes rigorous mathematical analyses, based on the Lyapunov approach, that guarantee their properties. In addition, for each chapter, simulation results are included to verify the successful performance of the corresponding proposed schemes. In order to complete the treatment of these schemes, the authors also present simulation and experimental results related to their

Neural Networks Modeling and Control

Neural Networks Modeling and Control
  • Author : Jorge D. Rios,Alma Y. Alanis,Nancy Arana-Daniel,Carlos Lopez-Franco
  • Publisher : Academic Press
  • Release : 15 January 2020
GET THIS BOOKNeural Networks Modeling and Control

Neural Networks Modelling and Control: Applications for Unknown Nonlinear Delayed Systems in Discrete Time focuses on modeling and control of discrete-time unknown nonlinear delayed systems under uncertainties based on Artificial Neural Networks. First, a Recurrent High Order Neural Network (RHONN) is used to identify discrete-time unknown nonlinear delayed systems under uncertainties, then a RHONN is used to design neural observers for the same class of systems. Therefore, both neural models are used to synthesize controllers for trajectory tracking based on

Artificial Neural Networks for Engineering Applications

Artificial Neural Networks for Engineering Applications
  • Author : Alma Y. Alanis,Nancy Arana-Daniel,Carlos Lopez-Franco
  • Publisher : Academic Press
  • Release : 07 February 2019
GET THIS BOOKArtificial Neural Networks for Engineering Applications

Artificial Neural Networks for Engineering Applications presents current trends for the solution of complex engineering problems that cannot be solved through conventional methods. The proposed methodologies can be applied to modeling, pattern recognition, classification, forecasting, estimation, and more. Readers will find different methodologies to solve various problems, including complex nonlinear systems, cellular computational networks, waste water treatment, attack detection on cyber-physical systems, control of UAVs, biomechanical and biomedical systems, time series forecasting, biofuels, and more. Besides the real-time implementations, the

Applied Artificial Higher Order Neural Networks for Control and Recognition

Applied Artificial Higher Order Neural Networks for Control and Recognition
  • Author : Zhang, Ming
  • Publisher : IGI Global
  • Release : 05 May 2016
GET THIS BOOKApplied Artificial Higher Order Neural Networks for Control and Recognition

In recent years, Higher Order Neural Networks (HONNs) have been widely adopted by researchers for applications in control signal generating, pattern recognition, nonlinear recognition, classification, and predition of control and recognition scenarios. Due to the fact that HONNs have been proven to be faster, more accurate, and easier to explain than traditional neural networks, their applications are limitless. Applied Artificial Higher Order Neural Networks for Control and Recognition explores the ways in which higher order neural networks are being integrated

Advances in Computational Intelligence

Advances in Computational Intelligence
  • Author : Wen Yu,Edgar N. Sanchez
  • Publisher : Springer Science & Business Media
  • Release : 18 August 2009
GET THIS BOOKAdvances in Computational Intelligence

This book constitutes the proceedings of the second International Workshop on Advanced Computational Intelligence (IWACI 2009), with a sequel of IWACI 2008 successfully held in Macao, China. IWACI 2009 provided a high-level international forum for scientists, engineers, and educators to present state-of-the-art research in computational intelligence and related fields. Over the past decades, computational intelligence community has witnessed t- mendous efforts and developments in all aspects of theoretical foundations, archit- tures and network organizations, modelling and simulation, empirical study, as well as a

Emerging Capabilities and Applications of Artificial Higher Order Neural Networks

Emerging Capabilities and Applications of Artificial Higher Order Neural Networks
  • Author : Zhang, Ming
  • Publisher : IGI Global
  • Release : 05 February 2021
GET THIS BOOKEmerging Capabilities and Applications of Artificial Higher Order Neural Networks

Artificial neural network research is one of the new directions for new generation computers. Current research suggests that open box artificial higher order neural networks (HONNs) play an important role in this new direction. HONNs will challenge traditional artificial neural network products and change the research methodology that people are currently using in control and recognition areas for the control signal generating, pattern recognition, nonlinear recognition, classification, and prediction. Since HONNs are open box models, they can be easily accepted

Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications

Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications
  • Author : Management Association, Information Resources
  • Publisher : IGI Global
  • Release : 26 July 2016
GET THIS BOOKNature-Inspired Computing: Concepts, Methodologies, Tools, and Applications

As technology continues to become more sophisticated, mimicking natural processes and phenomena also becomes more of a reality. Continued research in the field of natural computing enables an understanding of the world around us, in addition to opportunities for man-made computing to mirror the natural processes and systems that have existed for centuries. Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications takes an interdisciplinary approach to the topic of natural computing, including emerging technologies being developed for the purpose of simulating

Network and Communication Technology Innovations for Web and IT Advancement

Network and Communication Technology Innovations for Web and IT Advancement
  • Author : Alkhatib, Ghazi I.
  • Publisher : IGI Global
  • Release : 31 October 2012
GET THIS BOOKNetwork and Communication Technology Innovations for Web and IT Advancement

With the steady stream of new web based information technologies being introduced to organizations, the need for network and communication technologies to provide an easy integration of knowledge and information sharing is essential. Network and Communication Technology Innovations for Web and IT Advancement presents studies on trends, developments, and methods on information technology advancements through network and communication technology. This collection brings together integrated approaches for communication technology and usage for web and IT advancements.

Robust Discrete-Time Flight Control of UAV with External Disturbances

Robust Discrete-Time Flight Control of UAV with External Disturbances
  • Author : Shuyi Shao,Mou Chen,Peng Shi
  • Publisher : Springer Nature
  • Release : 26 September 2020
GET THIS BOOKRobust Discrete-Time Flight Control of UAV with External Disturbances

This book studies selected discrete-time flight control schemes for fixed-wing unmanned aerial vehicle (UAV) systems in the presence of system uncertainties, external disturbances and input saturation. The main contributions of this book for UAV systems are as follows: (i) the proposed integer-order discrete-time control schemes are based on the designed discrete-time disturbance observers (DTDOs) and the neural network (NN); and (ii) the fractional-order discrete-time control schemes are developed by using the fractional-order calculus theory, the NN and the DTDOs. The

Issues in Tissue Engineering and Transplant and Transfusion Medicine: 2011 Edition

Issues in Tissue Engineering and Transplant and Transfusion Medicine: 2011 Edition
  • Author : Anonim
  • Publisher : ScholarlyEditions
  • Release : 09 January 2012
GET THIS BOOKIssues in Tissue Engineering and Transplant and Transfusion Medicine: 2011 Edition

Issues in Tissue Engineering and Transplant and Transfusion Medicine: 2011 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Tissue Engineering and Transplant and Transfusion Medicine. The editors have built Issues in Tissue Engineering and Transplant and Transfusion Medicine: 2011 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Tissue Engineering and Transplant and Transfusion Medicine in this eBook to be deeper than what you can access anywhere else, as well as consistently

Intelligent Automatic Generation Control

Intelligent Automatic Generation Control
  • Author : Hassan Bevrani,Takashi Hiyama
  • Publisher : CRC Press
  • Release : 19 December 2017
GET THIS BOOKIntelligent Automatic Generation Control

Automatic generation control (AGC) is one of the most important control problems in the design and operation of interconnected power systems. Its significance continues to grow as a result of several factors: the changing structure and increasing size, complexity, and functionality of power systems, the rapid emergence (and uncertainty) of renewable energy sources, developments in power generation/consumption technologies, and environmental constraints. Delving into the fundamentals of power system AGC, Intelligent Automatic Generation Control explores ways to make the infrastructures

Nonlinear Control and Filtering Using Differential Flatness Approaches

Nonlinear Control and Filtering Using Differential Flatness Approaches
  • Author : Gerasimos G. Rigatos
  • Publisher : Springer
  • Release : 05 June 2015
GET THIS BOOKNonlinear Control and Filtering Using Differential Flatness Approaches

This monograph presents recent advances in differential flatness theory and analyzes its use for nonlinear control and estimation. It shows how differential flatness theory can provide solutions to complicated control problems, such as those appearing in highly nonlinear multivariable systems and distributed-parameter systems. Furthermore, it shows that differential flatness theory makes it possible to perform filtering and state estimation for a wide class of nonlinear dynamical systems and provides several descriptive test cases. The book focuses on the design of