Adaptive Regulation PDF Download
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Author | : Vladimir Nikiforov |
Publisher | : Springer Nature |
Total Pages | : 369 |
Release | : 2022-08-18 |
Genre | : Technology & Engineering |
ISBN | : 3030960919 |
Download Adaptive Regulation Book in PDF, ePub and Kindle
This monograph is focused on control law design methods for asymptotic tracking and disturbance rejection in the presence of uncertainties. The methods are based on adaptive implementation of the Internal Model Principle (IMP). The monograph shows how this principle can be applied to the problems of asymptotic rejection/tracking of a priori uncertain exogenous signals for linear and nonlinear plants with known and unknown parameters. The book begins by introducing the problems of adaptive control, the challenges that are faced, modern methods and an overview of the IMP. It then introduces special observers for uncertain exogeneous signals affecting linear and nonlinear systems with known and unknown parameters. The basic algorithms of adaptation applied to the canonical closed-loop error models are presented. The authors then address the systematic design of adaptive systems for asymptotic rejection/tracking of a priori uncertain exosignals. The monograph also discusses the adaptive rejection/tracking of a priori uncertain exogenous signals in systems with input delay, the problems of performance improvement in disturbance rejection and reference tracking and the issue of robustness of closed-loop systems. Adaptive Regulation provides a systematic discussion of the IMP applied to a variety of control problems, making it of interest to researchers and industrial practitioners.
Author | : John T. Wen |
Publisher | : |
Total Pages | : 84 |
Release | : 1985 |
Genre | : |
ISBN | : |
Download New methods in adaptive regulation and MARC Book in PDF, ePub and Kindle
Author | : Hartmut Logemann |
Publisher | : |
Total Pages | : |
Release | : 1993 |
Genre | : |
ISBN | : |
Download Adaptive Regulation for a Class of Infinite-dimensional Systems Book in PDF, ePub and Kindle
Author | : Thomas Parr |
Publisher | : MIT Press |
Total Pages | : 313 |
Release | : 2022-03-29 |
Genre | : Science |
ISBN | : 0262362287 |
Download Active Inference Book in PDF, ePub and Kindle
The first comprehensive treatment of active inference, an integrative perspective on brain, cognition, and behavior used across multiple disciplines. Active inference is a way of understanding sentient behavior—a theory that characterizes perception, planning, and action in terms of probabilistic inference. Developed by theoretical neuroscientist Karl Friston over years of groundbreaking research, active inference provides an integrated perspective on brain, cognition, and behavior that is increasingly used across multiple disciplines including neuroscience, psychology, and philosophy. Active inference puts the action into perception. This book offers the first comprehensive treatment of active inference, covering theory, applications, and cognitive domains. Active inference is a “first principles” approach to understanding behavior and the brain, framed in terms of a single imperative to minimize free energy. The book emphasizes the implications of the free energy principle for understanding how the brain works. It first introduces active inference both conceptually and formally, contextualizing it within current theories of cognition. It then provides specific examples of computational models that use active inference to explain such cognitive phenomena as perception, attention, memory, and planning.
Author | : Ivan Tyukin |
Publisher | : Cambridge University Press |
Total Pages | : 429 |
Release | : 2011-02-17 |
Genre | : Science |
ISBN | : 1139494163 |
Download Adaptation in Dynamical Systems Book in PDF, ePub and Kindle
In the context of this book, adaptation is taken to mean a feature of a system aimed at achieving the best possible performance, when mathematical models of the environment and the system itself are not fully available. This has applications ranging from theories of visual perception and the processing of information, to the more technical problems of friction compensation and adaptive classification of signals in fixed-weight recurrent neural networks. Largely devoted to the problems of adaptive regulation, tracking and identification, this book presents a unifying system-theoretic view on the problem of adaptation in dynamical systems. Special attention is given to systems with nonlinearly parameterized models of uncertainty. Concepts, methods and algorithms given in the text can be successfully employed in wider areas of science and technology. The detailed examples and background information make this book suitable for a wide range of researchers and graduates in cybernetics, mathematical modelling and neuroscience.
Author | : George A. Rovithakis |
Publisher | : Springer Science & Business Media |
Total Pages | : 203 |
Release | : 2012-12-06 |
Genre | : Computers |
ISBN | : 1447107853 |
Download Adaptive Control with Recurrent High-order Neural Networks Book in PDF, ePub and Kindle
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.
Author | : Jwu-Sheng Hu |
Publisher | : |
Total Pages | : 356 |
Release | : 1990 |
Genre | : |
ISBN | : |
Download Adaptive Regulation and Tracking Under Periodic Disturbances Book in PDF, ePub and Kindle
Author | : National Aeronautics and Space Administration (NASA) |
Publisher | : Createspace Independent Publishing Platform |
Total Pages | : 34 |
Release | : 2018-07-11 |
Genre | : |
ISBN | : 9781722745097 |
Download Robust Adaptive Regulation Without Persistent Excitation Book in PDF, ePub and Kindle
A globally convergent adaptive regulator for minimum or nonminimum phase systems subject to bounded distrubances and unmodeled dynamics is presented. The control strategy is designed for a particular input-output representation obtained from the state space representation of the system. The leading coefficient of the new representation is the product of the observability and controllability matrices of the system. The controller scheme uses a Least Squares identification algorithm with a dead zone. The dead zone is chosen to obtain convergence properties on the estimates and on the covariance matrix as well. This allows the definition of modified estimates which secure well-conditioned matrices in the adaptive control law. Explicit bounds on the plant output are given. Lozano-Leal, Rogelio Langley Research Center RTOP 506-45-11-01...
Author | : Ioan Doré Landau |
Publisher | : Springer Science & Business Media |
Total Pages | : 595 |
Release | : 2011-06-06 |
Genre | : Technology & Engineering |
ISBN | : 0857296647 |
Download Adaptive Control Book in PDF, ePub and Kindle
Adaptive Control (second edition) shows how a desired level of system performance can be maintained automatically and in real time, even when process or disturbance parameters are unknown and variable. It is a coherent exposition of the many aspects of this field, setting out the problems to be addressed and moving on to solutions, their practical significance and their application. Discrete-time aspects of adaptive control are emphasized to reflect the importance of digital computers in the application of the ideas presented. The second edition is thoroughly revised to throw light on recent developments in theory and applications with new chapters on: multimodel adaptive control with switching, direct and indirect adaptive regulation and adaptive feedforward disturbance compensation. Many algorithms are newly presented in MATLAB® m-file format to facilitate their employment in real systems. Classroom-tested slides for instructors to use in teaching this material are also now provided. All of this supplementary electronic material can be downloaded from fill in URL. The core material is also up-dated and re-edited to keep its perspective in line with modern ideas and more closely to associate algorithms with their applications giving the reader a solid grounding in: synthesis and analysis of parameter adaptation algorithms, recursive plant model identification in open and closed loop, robust digital control for adaptive control; • robust parameter adaptation algorithms, practical considerations and applications, including flexible transmission systems, active vibration control and broadband disturbance rejection and a supplementary introduction on hot dip galvanizing and a phosphate drying furnace. Control researchers and applied mathematicians will find Adaptive Control of significant and enduring interest and its use of example and application will appeal to practitioners working with unknown- and variable-parameter plant. Praise for the first edition: ...well written, interesting and easy to follow, so that it constitutes a valuable addition to the monographies in adaptive control for discrete-time linear systems... suitable (at least in part) for use in graduate courses in adaptive control.
Author | : Eric Dean Peterson |
Publisher | : |
Total Pages | : 222 |
Release | : 2014 |
Genre | : Adaptive control systems |
ISBN | : |
Download Multiple Model Adaptive Regulation Book in PDF, ePub and Kindle
A single controller may be inadequate for systems that experience structural changes that arise, for example, from component failures. Such systems are often modeled by a family of plants with structural diversity. At any given time the appropriate plant model is uncertain. Adaptation is required for the parameter dependent family of plants but continuous adaptive regulation is limited by relative degree and right half plane zeros. A form of adaptive regulation is presented that accommodates these changes. The Multiple Model Adaptive Regulator selects a controller from a predefined set to achieve performance goals. In general, the set of controllers is finite although the family of plants may be continuous. The set of controllers accommodates a structurally diverse family of plants. A multiple model controller design has two subproblems, covering and switching. The covering subproblem is to design a small set of controllers such that each possible plant is stabilized by at least one controller. The switching subproblem is to select a stabilizing controller from the set of controllers. In this research, the covering and switching subproblems are solved with LQR state feedback and Lyapunov function switch logic respectively. The LQR and Common Quadratic Lyapunov Function design problems are combined into a set of Linear Matrix Inequalities (LMI) and concurrently solved. Design constraints on the open loop plant and the regulator are presented. The multiple model adaptive regulator is applied to systems with diverse zero structure.