Learning Based Adaptive Control

Adaptive control has been one of the main problems studied in control theory. The subject is well understood, yet it has a very active research frontier. This book focuses on a specific subclass of adaptive control, namely, learning-based adaptive control. As systems evolve during time or are exposed to unstructured environments, it is expected that some of their characteristics may change. This book offers a new perspective about how to deal with these variations. By merging together Model-Free and Model-Based learning algorithms, the author demonstrates, using a number of mechatronic examples, how the learning process can be shortened and optimal control performance can be reached and maintained. Includes a good number of Mechatronics Examples of the techniques. Compares and blends Model-free and Model-based learning algorithms. Covers fundamental concepts, state-of-the-art research, necessary tools for modeling, and control.

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  • Author : Mouhacine Benosman
  • Publisher : Butterworth-Heinemann
  • Pages : 282 pages
  • ISBN : 0128031514
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKLearning Based Adaptive Control

Learning-Based Adaptive Control

Learning-Based Adaptive Control
  • Author : Mouhacine Benosman
  • Publisher : Butterworth-Heinemann
  • Release : 02 August 2016
GET THIS BOOKLearning-Based Adaptive Control

Adaptive control has been one of the main problems studied in control theory. The subject is well understood, yet it has a very active research frontier. This book focuses on a specific subclass of adaptive control, namely, learning-based adaptive control. As systems evolve during time or are exposed to unstructured environments, it is expected that some of their characteristics may change. This book offers a new perspective about how to deal with these variations. By merging together Model-Free and Model-Based

Adaptive Control for Robotic Manipulators

Adaptive Control for Robotic Manipulators
  • Author : Dan Zhang,Bin Wei
  • Publisher : CRC Press
  • Release : 10 November 2016
GET THIS BOOKAdaptive Control for Robotic Manipulators

The robotic mechanism and its controller make a complete system. As the robotic mechanism is reconfigured, the control system has to be adapted accordingly. The need for the reconfiguration usually arises from the changing functional requirements. This book will focus on the adaptive control of robotic manipulators to address the changed conditions. The aim of the book is to summarise and introduce the state-of-the-art technologies in the field of adaptive control of robotic manipulators in order to improve the methodologies

A Learning Based Adaptive Cruise and Lane Control System

A Learning Based Adaptive Cruise and Lane Control System
  • Author : Peng Xu
  • Publisher : Unknown Publisher
  • Release : 17 April 2021
GET THIS BOOKA Learning Based Adaptive Cruise and Lane Control System

The present thesis describes the design of a learning based autonomous driving system mainly on adaptive cruise control (ACC) and lane control (LC). In this study a simulated highway environment is created for the vehicles to capture online training data. A Deep Q-Learning algorithm is proposed to train two agents respectively, an ACC agent and an integrated agent (ACC and LC). The results show behavioral adaptation with an ACC in terms of the speed of the preceding vehicle and emergence

Cognitive Informatics, Computer Modelling, and Cognitive Science

Cognitive Informatics, Computer Modelling, and Cognitive Science
  • Author : Ganesh R. Sinha,Jasjit S. Suri
  • Publisher : Academic Press
  • Release : 17 March 2020
GET THIS BOOKCognitive Informatics, Computer Modelling, and Cognitive Science

Cognitive Informatics, Computer Modelling, and Cognitive Science: Theory, Case Studies, and Applications presents the theoretical background and history of cognitive science to help readers understand its foundations, philosophical and psychological aspects, and applications in a wide range of engineering and computer science case studies. Cognitive science, a cognitive model of the brain, knowledge representation, and information processing in the human brain are discussed, as is the theory of consciousness, neuroscience, intelligence, decision-making, mind and behavior analysis, and the various ways

Adaptive Learning Methods for Nonlinear System Modeling

Adaptive Learning Methods for Nonlinear System Modeling
  • Author : Danilo Comminiello,Jose C. Principe
  • Publisher : Butterworth-Heinemann
  • Release : 11 June 2018
GET THIS BOOKAdaptive Learning Methods for Nonlinear System Modeling

Adaptive Learning Methods for Nonlinear System Modeling presents some of the recent advances on adaptive algorithms and machine learning methods designed for nonlinear system modeling and identification. Real-life problems always entail a certain degree of nonlinearity, which makes linear models a non-optimal choice. This book mainly focuses on those methodologies for nonlinear modeling that involve any adaptive learning approaches to process data coming from an unknown nonlinear system. By learning from available data, such methods aim at estimating the nonlinearity

Intelligent Control

Intelligent Control
  • Author : Kaushik Das Sharma,Amitava Chatterjee,Anjan Rakshit
  • Publisher : Springer
  • Release : 28 August 2018
GET THIS BOOKIntelligent Control

This book discusses systematic designs of stable adaptive fuzzy logic controllers employing hybridizations of Lyapunov strategy-based approaches/H∞ theory-based approaches and contemporary stochastic optimization techniques. The text demonstrates how candidate stochastic optimization techniques like Particle swarm optimization (PSO), harmony search (HS) algorithms, covariance matrix adaptation (CMA) etc. can be utilized in conjunction with the Lyapunov theory/H∞ theory to develop such hybrid control strategies. The goal of developing a series of such hybridization processes is to combine the strengths of

Model Free Adaptive Control

Model Free Adaptive Control
  • Author : Zhongsheng Hou,Shangtai Jin
  • Publisher : CRC Press
  • Release : 24 September 2013
GET THIS BOOKModel Free Adaptive Control

Model Free Adaptive Control: Theory and Applications summarizes theory and applications of model-free adaptive control (MFAC). MFAC is a novel adaptive control method for the unknown discrete-time nonlinear systems with time-varying parameters and time-varying structure, and the design and analysis of MFAC merely depend on the measured input and output data of the controlled plant, which makes it more applicable for many practical plants. This book covers new concepts, including pseudo partial derivative, pseudo gradient, pseudo Jacobian matrix, and generalized

Machine Vision Inspection Systems, Machine Learning-Based Approaches

Machine Vision Inspection Systems, Machine Learning-Based Approaches
  • Author : Muthukumaran Malarvel,Soumya Ranjan Nayak,Prasant Kumar Pattnaik,Surya Narayan Panda
  • Publisher : John Wiley & Sons
  • Release : 24 February 2021
GET THIS BOOKMachine Vision Inspection Systems, Machine Learning-Based Approaches

Machine Vision Inspection Systems (MVIS) is a multidisciplinary research field that emphasizes image processing, machine vision and, pattern recognition for industrial applications. Inspection techniques are generally used in destructive and non-destructive evaluation industry. Now a day's the current research on machine inspection gained more popularity among various researchers, because the manual assessment of the inspection may fail and turn into false assessment due to a large number of examining while inspection process. This volume 2 covers machine learning-based approaches in MVIS

Adaptive Systems in Control and Signal Processing 1992

Adaptive Systems in Control and Signal Processing 1992
  • Author : L. Dugard,M. MʼSaad
  • Publisher : Pergamon
  • Release : 17 April 1993
GET THIS BOOKAdaptive Systems in Control and Signal Processing 1992

Adaptive Systems remain a very interesting field of theoretical research, extended by methodological studies and an increasing number of applications. The plenary papers, invited sessions and contributed sessions focused on many aspects of adaptive systems, such as systems identification and modelling, adaptive control of nonlinear systems and theoretical issues in adaptive control. Also covered were methodological aspects and applications of adaptive control, intelligent tuning and adaptive signal processing.

Adaptive Control

Adaptive Control
  • Author : Karl J. Åström,Björn Wittenmark
  • Publisher : Courier Corporation
  • Release : 26 April 2013
GET THIS BOOKAdaptive Control

Suitable for advanced undergraduates and graduate students, this overview introduces theoretical and practical aspects of adaptive control, with emphasis on deterministic and stochastic viewpoints. 1995 edition.

Applications of Neural Adaptive Control Technology

Applications of Neural Adaptive Control Technology
  • Author : Jens Kalkkuhl,Rafal Zbikowski
  • Publisher : World Scientific
  • Release : 17 April 1997
GET THIS BOOKApplications of Neural Adaptive Control Technology

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

Nonlinear and Adaptive Control Design

Nonlinear and Adaptive Control Design
  • Author : Miroslav Krstic,Ιωάννης Κανελλακόπουλος,Petar V. Kokotovic,Petar V. Kokotović
  • Publisher : Wiley-Interscience
  • Release : 14 June 1995
GET THIS BOOKNonlinear and Adaptive Control Design

An introduction to a new design for nonlinear control systems--backstepping--written by its own architects. This innovative book breaks new ground in nonlinear and adaptive control design for systems with uncertainties. Introducing the recursive backstepping methodology, it shows--for the first time--how uncertain systems with severe nonlinearities can be successfully controlled with this new powerful design tool. Communicative and accessible at a level not usually present in research texts, Nonlinear and Adaptive Control Design can be used as either a stand-alone or