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4 edition of Adaptive control for partially known systems found in the catalog.

Adaptive control for partially known systems

theory and applications

by Carlos A. Canudas de Wit

  • 340 Want to read
  • 18 Currently reading

Published by Elsevier in Amsterdam, New York .
Written in English

    Subjects:
  • Adaptive control systems.

  • Edition Notes

    StatementCarlos A. Canudas de Wit.
    SeriesStudies in automation and control ;, v. 7
    Classifications
    LC ClassificationsTJ217 .C28 1988
    The Physical Object
    Paginationxvii, 264 p. :
    Number of Pages264
    ID Numbers
    Open LibraryOL2053120M
    ISBN 100444871365
    LC Control Number88031002

    Follow Carlos A. Canudas de Wit and explore their bibliography from 's Carlos A. Canudas de Wit Author g: Adaptive control.   1. “Robust Adaptive Control” by P. Ioannou and J. Sun Book Review: The book presents fundamental techniques and algorithms in the field of adaptive control. The book demonstrates the design, analysis and application of a range of algorithms that are used to manage dynamical systems with unknown parameters.

    The control design method has two stages. First, the known dynamics are separated out and used to perform a global linearization on the nonlinear system. Second, a model-reference adaptive control, based on the Lyapunov stability criterion, is designed for the remaining unknown portion of the plant. 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 .

    Salgado I, Yañez C, Camacho O and Chairez I () Adaptive control of discrete-time nonlinear systems by recurrent neural networks in quasi-sliding mode like regime, International Journal of Adaptive Control and Signal Processing, , (), Online publication date: 1-Jan springer, Presenting current trends in the development and applications of intelligent systems in engineering, this monograph focuses on recent research results in system identification and control. The recurrent neurofuzzy and the fuzzy cognitive network (FCN) models are presented. Both models are suitable for partially-known or unknown complex time-varying systems.


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Adaptive control for partially known systems by Carlos A. Canudas de Wit Download PDF EPUB FB2

The recurrent neurofuzzy and the fuzzy cognitive network (FCN) models are presented. Both models are suitable for partially-known or unknown complex time-varying systems.

Neurofuzzy Adaptive Control contains rigorous proofs of its statements which result in concrete conclusions for the selection of the design parameters of the algorithms by: 4. Introduction and background. A new estimation algorithm. User guidelines and some examples.

Final remarks. Hybrid Estimation for Systems with Variable Time-Delay. Plant model. Parameter estimation. Conclusions. Hybrid Adaptive Control for Partially Known Systems. Fixed control strategy. Estimation scheme and adaptive control law. An in-depth examination of intelligent approaches to increasing the accuracy of a variety of system components.

Utilizing a unified, adaptive, inverse approach, the book offers electrical, mechanical, chemical, aeronautical and computer engineers methods for controlling many of the hard nonlinearities of frequently-employed control systems such as dead-zone, backlash and hysteresis.

The unique feature of the localization-based switching adaptive control, proposed in the chapter, is its rapid model falsification capability. In the LTI case this is manifested in the ability of the switching controller to quickly converge to a suitable stabilizing controller.

The main objective of this monograph is to develop efficient techniques for tackling the control problems of partially-known dynamical systems. This broad class of systems has a fundamental feature: Knowledge of the dynamic characteristics of the control plant is not complete.

Adaptive control of partially known systems Abstract: First presents modified parametrizations for model reference adaptive control of linear plants with partial knowledge. An approach is developed for the adaptive model-reference control of the continuous-time systems consisting of known and unknown subsystems.

It is assumed that the plant is composed of the cascade, parallel or feedback interconnection of known and unknown subsystems. Many physical control systems can be modeled by such interconnections. In our approach, by using the prior knowledge. Adaptive control of partially known continuous-time systems Abstract: An approach is developed for the adaptive model-reference control of the continuous-time systems consisting of known and unknown subsystems.

Purchase Adaptive Control Systems - 1st Edition. Print Book & E-Book. ISBNsystems and therefore, simplifying the adaptive algorithm. In this work, we study adaptive control design in partially known continuous-time systems.

Similar to the approach in [4], we use a block-diagram representation for characterization of partial plant knowledge, and extend the results of [4] to continuous-time systems.

We assume that the. In this paper, we propose a design method of model reference adaptive control systems for non-minimum phase systems by utilizing 2-delay input control. In our method, the poles and zeros of the controlled systems are relocated by the 2-delay feedback control laws with 2-delay sampling.

The recurrent neurofuzzy and the fuzzy cognitive network (FCN) models are presented. Both models are suitable for partially-known or unknown complex time-varying systems.

Neurofuzzy Adaptive Control contains rigorous proofs of its statements which result in concrete conclusions for the selection of the design parameters of the algorithms presented. CHAPTER 9: ADAPTIVE CONTROL Adaptive control for industrial use 1 A high-performance control system must also include all the logics, filtering and computations the needed for a good control design.

The MicroController contains an extensive function library or known gain changes. Not truly adaptiveFile Size: KB. Both models are suitable for partially-known or unknown complex time-varying systems. Neurofuzzy Adaptive Control contains rigorous proofs of its statements which result in concrete conclusions for the selection of the design parameters of the algorithms presented.

An in-depth examination of intelligent approaches to increasing the accuracy of a variety of system components. Utilizing a unified, adaptive, inverse approach, the book offers electrical, mechanical, chemical, aeronautical and computer engineers methods for controlling many of the "hard" nonlinearities of frequently-employed control systems such as dead-zone, backlash and hysteresis.

This chapter is devoted to Bayesian adaptive control problems. These can be viewed as optimal control problems of partially observed systems and studied using dynamic programming. A complete theory is presented for a special class of such problems known as bandit problems.

The area of adaptive systems, which encompasses recursive identification, adaptive control, filtering, and signal processing, has been one of the most active areas of the past decade. Since adaptive controllers are fundamentally nonlinear controllers which are applied to nominally linear, possibly.

Nonlinear and Adaptive Control Systems treats nonlinear control and adaptive control in a unified framework, presenting the major results at a moderate mathematical level, suitable for MSc Author: Zhengtao Ding. An adaptive, ergodic cost stochastic control problem for a partially known, semilinear, stochastic system in an infinite dimensional space is formulated and solved.

The solutions of the Hamilton--J Cited by: 9. Both models are suitable for partially-known or unknown complex time-varying systems. Neurofuzzy Adaptive Control contains rigorous proofs of its statements which result in concrete conclusions for.

Nonlinear and adaptive control de-sign Miroslav Krstic, Ioannis Kanellakopoulos, Peter V. Kokotovic From the Publisher: Using a pedagogical style along with detailed proofs and illustrative examples, this book opens a view to the largely unexplored area of nonlinear systems with uncertainties.IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL.

10, NO. 3, MAY Direct Adaptive Control of Partially Known Nonlinear Systems Richard .along with Truxal’s definition in (given earlier) that adaptive control is only in the eye of the designer, is quoted often in control circles and both have stood the test of time. The close connection between identification and control in the context of partially known systems was stated succinctly around this time () by Feldbaum, who.