A comparative study of self-adaptive long-range predictive control methods

Keyser, R.M.C. De; Velde, Ph.G.A. Van de; Dumortier, F.

doi:10.1016/0005-1098(88)90024-6

Cited by 141 publications

(9 citation statements)

References 6 publications

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“…113,166,458 The internal model used may be a state-space model, a convolution-type (integral) model, or a recursive discrete-time model.…”

Section: Predictive Controlmentioning

confidence: 99%

Human and Nature Minding Automation

Tzafestas

2010

Intelligent Systems, Control and Automation: Science and Engineering

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this work may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, microfilming, recording or otherwise, without written permission from the Publisher, with the exception of any material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work.Cover design: eStudio Calamar S.L. PrefaceMan is the best thing in the World. Nature does nothing uselessly. AristotleThere is a pleasure in the pathless woods, There is rapture on the lonely shore, There is society, where none intrudes, By the deep sea, and music in its roar: I love not Man the less, but Nature more. John BurroughsThe basic purpose of development is to enlarge people's choices. The objective of development is to create an enabling environment for people to enjoy long, healthy and creative lives. Mahbub ul Hag Founder of the Human Development ReportThe aim of this book is to provide a compiled set of concepts, principles, methods and issues used for studying, designing and operating human-minding and natureminding automation and industrial systems. The depth of presentation is sufficient for the reader to understand the problems involved and the solution approaches, and appreciate the need of human-automation cooperative interaction, and the importance of the efforts required for environment and ecosystem protection during any technological and development process in the society. Humans and technology are living and have to live together in a sustainable society and nature. Humans must not be viewed as components of automation and technology in the same way as machines. Automation and technology must incorporate the humans' needs and preferences, and radiate "beauty" in all ways, namely functionally, technically and humanistically. In overall, automation and technology should create comfort and give pleasure.The achievement of human-minding or human-centered automation was made possible by employing concepts and techniques of the human factors and ergonomics field. This is the easy part of the human-and nature minding-automation and technology story. To achieve truly nature-minding industry and automation, more complex and difficult decisions and tools are required. The partners here are not only the machines and the scientists or engineers, but also the politicians and vii viii Preface governors worldwide. Nature-minding design has to determine the way a product is produced on the basis of its impact to the nature and ecosystem, including pollution, waste generation, biodiversity decrease, and consumption of the earth resources. A society can be developed in a truly sustainable way if it adopts as a whole the human, economic, natural and cultural resources, not only in the short term but also in the long term. In our time the problems of human, automation/technology, and nature sustainable symbiosis have become more difficult and crucial than ever.This book provides a consolidated tutorial overview of the...

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“…113,166,458 The internal model used may be a state-space model, a convolution-type (integral) model, or a recursive discrete-time model.…”

Section: Predictive Controlmentioning

confidence: 99%

Human and Nature Minding Automation

Tzafestas

2010

Intelligent Systems, Control and Automation: Science and Engineering

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“…The combination of the on-line parameter estimation and control results in an adaptive or self-learning controller (see Section 5.2 for more details). It has been shown that it is possible to find an algorithm such that parameter-adaptive control systems converge to satisfactory control behavior [149,126]. However, several problems limit the application of parameter adaptive controllers to real processes.…”

Section: Fuzzy Model-based Controlmentioning

confidence: 99%

Fuzzy Model Identification for Control

Abonyi¹

2003

130

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“…Taking the expectation in (16) and assuming that the expected density for the parameters is approximated by N(C(k), P(k#i)), this leads to…”

Section: Controller Based On the Bicriterial Approach The Bicriteriamentioning

confidence: 99%

Adaptive predictive controllers based on orthonormal series representation

Sbárbaro

Filatov

Unbehauen

1999

Int. J. Adapt. Control Signal Process.

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This work presents and compares a set of active and passive adaptive predictive controllers based on orthonormal series representations. The controllers are designed according to the receding thorizon principle, where the parameters of the predictive model are considered as random variables. This general framework allows the design of active and passive adaptive controllers, according to the assumptions made over the prediction of the posterior densities of the random variables. Several simulated examples illustrate the characteristics for each algorithm and the performance improvement obtained by active adaptive controllers.

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A comparative study of self-adaptive long-range predictive control methods

Cited by 141 publications

References 6 publications

Human and Nature Minding Automation

Human and Nature Minding Automation

Fuzzy Model Identification for Control

Adaptive predictive controllers based on orthonormal series representation

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