Identification of Nonlinear Control Models Using Volterra-Laguerre Series. PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Identification of Nonlinear Control Models Using Volterra-Laguerre Series. PDF full book. Access full book title Identification of Nonlinear Control Models Using Volterra-Laguerre Series. by Dale A. Smith. Download full books in PDF and EPUB format.
Author: Dale A. Smith
Publisher:
ISBN: 9781243773258
Category : Volterra series
Languages : en
Pages : 122
Get Book Here
Book Description
Linear model predictive control has been widely accepted in industry as an important tool for the operation of difficult interacting processes. Linear identification and control techniques are well developed and well understood. In the industry, it is rare to find a system that is truly linear. While for many systems linear modeling and control can approximate their performance in certain regions, there exist some systems whose nonlinearity is great enough that an approximate linear model and control scheme cannot yield the desired accuracy. In order to control these more complex nonlinear systems, significant research has been dedicated to extending model predictive control to nonlinear systems. The problem of implementing nonlinear model predictive control can be split into two main tasks: making the nonlinear model and calculating control inputs. The significant contributions of this dissertation are in the area of identification of nonlinear Volterra models from input-output data. Historically, the identification of Volterra models has been limited to lower order models because of the large amount of model parameters that need to be identified. By using the Laguerre polynomials, the number of model parameters can be greatly reduced, which limits the required input-output tests. The goal of this dissertation is to move nonlinear multivariable control closer to industrial application by addressing practical model identification questions. Results from three test cases are presented and discussed. The results have shown a decrease in parameters of as much as 99% without a significant loss in model fidelity.
Author: Dale A. Smith
Publisher:
ISBN: 9781243773258
Category : Volterra series
Languages : en
Pages : 122
Get Book Here
Book Description
Linear model predictive control has been widely accepted in industry as an important tool for the operation of difficult interacting processes. Linear identification and control techniques are well developed and well understood. In the industry, it is rare to find a system that is truly linear. While for many systems linear modeling and control can approximate their performance in certain regions, there exist some systems whose nonlinearity is great enough that an approximate linear model and control scheme cannot yield the desired accuracy. In order to control these more complex nonlinear systems, significant research has been dedicated to extending model predictive control to nonlinear systems. The problem of implementing nonlinear model predictive control can be split into two main tasks: making the nonlinear model and calculating control inputs. The significant contributions of this dissertation are in the area of identification of nonlinear Volterra models from input-output data. Historically, the identification of Volterra models has been limited to lower order models because of the large amount of model parameters that need to be identified. By using the Laguerre polynomials, the number of model parameters can be greatly reduced, which limits the required input-output tests. The goal of this dissertation is to move nonlinear multivariable control closer to industrial application by addressing practical model identification questions. Results from three test cases are presented and discussed. The results have shown a decrease in parameters of as much as 99% without a significant loss in model fidelity.
Author: F.J.III Doyle
Publisher: Springer Science & Business Media
ISBN: 1447101073
Category : Technology & Engineering
Languages : en
Pages : 319
Get Book Here
Book Description
This book covers recent results in the analysis, identification and control of systems described by Volterra models. Topics covered include: qualitative behavior of finite Volterra models compared and contrasted with other nonlinear model classes, structural restrictions and extensions to Volterra model class, least squares and stochastic identification approaches, model inversion issues, and direct synthesis and model predictive control design, guidelines for practical applications. Examples are drawn from Chemical, Biological and Electrical Engineering. The book is suitable as a text for a graduate control course, or as a reference for both research and practice.
Author: Robert Haber
Publisher: Springer Science & Business Media
ISBN: 9780792358565
Category : Nonlinear theories
Languages : en
Pages : 432
Get Book Here
Book Description
Author: A. Isidori
Publisher: Elsevier
ISBN: 1483298922
Category : Technology & Engineering
Languages : en
Pages : 429
Get Book Here
Book Description
In the last two decades, the development of specific methodologies for the control of systems described by nonlinear mathematical models has attracted an ever increasing interest. New breakthroughs have occurred which have aided the design of nonlinear control systems. However there are still limitations which must be understood, some of which were addressed at the IFAC Symposium in Capri. The emphasis was on the methodological developments, although a number of the papers were concerned with the presentation of applications of nonlinear design philosophies to actual control problems in chemical, electrical and mechanical engineering.
Author: Han-Xiong Li
Publisher: Springer Science & Business Media
ISBN: 940070741X
Category : Mathematics
Languages : en
Pages : 175
Get Book Here
Book Description
The purpose of this volume is to provide a brief review of the previous work on model reduction and identifi cation of distributed parameter systems (DPS), and develop new spatio-temporal models and their relevant identifi cation approaches. In this book, a systematic overview and classifi cation on the modeling of DPS is presented fi rst, which includes model reduction, parameter estimation and system identifi cation. Next, a class of block-oriented nonlinear systems in traditional lumped parameter systems (LPS) is extended to DPS, which results in the spatio-temporal Wiener and Hammerstein systems and their identifi cation methods. Then, the traditional Volterra model is extended to DPS, which results in the spatio-temporal Volterra model and its identification algorithm. All these methods are based on linear time/space separation. Sometimes, the nonlinear time/space separation can play a better role in modeling of very complex processes. Thus, a nonlinear time/space separation based neural modeling is also presented for a class of DPS with more complicated dynamics. Finally, all these modeling approaches are successfully applied to industrial thermal processes, including a catalytic rod, a packed-bed reactor and a snap curing oven. The work is presented giving a unifi ed view from time/space separation. The book also illustrates applications to thermal processes in the electronics packaging and chemical industry. This volume assumes a basic knowledge about distributed parameter systems, system modeling and identifi cation. It is intended for researchers, graduate students and engineers interested in distributed parameter systems, nonlinear systems, and process modeling and control.
Author: Juan Alejandro Vazquez Feijoo
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Get Book Here
Book Description
Author: Gurumurthy Thiagarajan
Publisher:
ISBN:
Category :
Languages : en
Pages : 136
Get Book Here
Book Description
Author: Amir Nassirharand
Publisher: Springer Science & Business Media
ISBN: 1447121481
Category : Computers
Languages : en
Pages : 189
Get Book Here
Book Description
A systematic computer-aided approach provides a versatile setting for the control engineer to overcome the complications of controller design for highly nonlinear systems. This book provides such an approach based on the use of describing functions.
Author: Haiquan Zhao
Publisher: Springer Nature
ISBN: 3031208188
Category : Technology & Engineering
Languages : en
Pages : 271
Get Book Here
Book Description
This book presents the design, analysis, and application of nonlinear adaptive filters with the goal of improving efficient performance (ie the convergence speed, steady-state error, and computational complexity). The authors present a nonlinear adaptive filter, which is an important part of nonlinear system and digital signal processing and can be applied to diverse fields such as communications, control power system, radar sonar, etc. The authors also present an efficient nonlinear filter model and robust adaptive filtering algorithm based on the local cost function of optimal criterion to overcome non-Gaussian noise interference. The authors show how these achievements provide new theories and methods for robust adaptive filtering of nonlinear and non-Gaussian systems. The book is written for the scientist and engineer who are not necessarily an expert in the specific nonlinear filtering field but who want to learn about the current research and application. The book is also written to accompany a graduate/PhD course in the area of nonlinear system and adaptive signal processing.
Author: Anita Khosla
Publisher: Springer Nature
ISBN: 9811646635
Category : Technology & Engineering
Languages : en
Pages : 188
Get Book Here
Book Description
This book gathers selected high-quality research papers presented at International Conference on Renewable Technologies in Engineering (ICRTE 2021) organized by Manav Rachna International Institute of Research & Studies, Faridabad, Haryana, India, during 15–16 April 2021. The book includes conference papers on the theme “Computational Techniques for Renewable Energy Optimization”, which aims to bring together leading academic scientists, researchers and research scholars to exchange and share their experiences and research results on all aspects of renewable energy integration, planning, control and optimization. It also provides a premier interdisciplinary platform for researchers, practitioners and educators to present and discuss the most recent innovations, trends and concerns as well as practical challenges encountered and solutions adopted in the fields of renewable energy and resources.
