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Industrial PID controller tuning = w...

Rojas, Jose David.

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Industrial PID controller tuning = with a multiobjective framework using MATLAB /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Industrial PID controller tuning/ by Jose David Rojas, Orlando Arrieta, Ramon Vilanova.
Reminder of title:	with a multiobjective framework using MATLAB /
Author:	Rojas, Jose David.
other author:	Arrieta, Orlando.
Published:	Cham :Springer International Publishing : : 2021.,
Description:	xiv, 148 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- Process Control as a Multi-Objective Problem -- Multi-Objective Optimization Methods -- Implementation of the Multi-Objective Optimization Methods Using MATLAB -- Application Examples.
Contained By:	Springer Nature eBook
Subject:	PID controllers. -
Online resource:	https://doi.org/10.1007/978-3-030-72311-8
ISBN:	9783030723118

Industrial PID controller tuning = with a multiobjective framework using MATLAB /
Rojas, Jose David.

Industrial PID controller tuningwith a multiobjective framework using MATLAB /[electronic resource] :by Jose David Rojas, Orlando Arrieta, Ramon Vilanova. - Cham :Springer International Publishing :2021. - xiv, 148 p. :ill., digital ;24 cm. - Advances in industrial control,1430-9491. - Advances in industrial control..

Introduction -- Process Control as a Multi-Objective Problem -- Multi-Objective Optimization Methods -- Implementation of the Multi-Objective Optimization Methods Using MATLAB -- Application Examples.

Industrial PID Controller Tuning presents a different view of the servo/regulator compromise that has been studied for a long time in industrial control research. Optimal tuning generally involves comparison of cost functions (e.g., a quadratic function of the error or a time-weighted absolute value of the error) but without taking advantage of available multi-objective optimization methods. The book does make use of multi-objective optimization to account for several sources of disturbance, applying them to a more realistic problem: how to select the tuning of a controller when both servo and regulator responses are important. The authors review the different deterministic multi-objective optimization methods. In order to ameliorate the consequences of the computational expense typically involved in their use-specifically the generation of multiple solutions among which the control engineer still has to choose-algorithms for two-degree-of-freedom PID control are implemented in MATLAB. MATLAB code and a MATLAB-compatible program are provided for download and will help readers to adapt the ideas presented in the text for use in their own systems. Further practical guidance is offered by the inclusion of several examples of common industrial processes amenable to the use of the authors' methods. Researchers interested in non-heuristic approaches to controller tuning or in decision-making after a Pareto set has been established and graduate students interested in beginning a career working with PID control and/or industrial controller tuning will find this book a valuable reference and source of ideas. Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.

ISBN: 9783030723118

Standard No.: 10.1007/978-3-030-72311-8doiSubjects--Topical Terms:

921970
PID controllers.

LC Class. No.: TJ223.P55 / R65 2021

Dewey Class. No.: 629.8

Industrial PID controller tuning = with a multiobjective framework using MATLAB /
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520 $a Industrial PID Controller Tuning presents a different view of the servo/regulator compromise that has been studied for a long time in industrial control research. Optimal tuning generally involves comparison of cost functions (e.g., a quadratic function of the error or a time-weighted absolute value of the error) but without taking advantage of available multi-objective optimization methods. The book does make use of multi-objective optimization to account for several sources of disturbance, applying them to a more realistic problem: how to select the tuning of a controller when both servo and regulator responses are important. The authors review the different deterministic multi-objective optimization methods. In order to ameliorate the consequences of the computational expense typically involved in their use-specifically the generation of multiple solutions among which the control engineer still has to choose-algorithms for two-degree-of-freedom PID control are implemented in MATLAB. MATLAB code and a MATLAB-compatible program are provided for download and will help readers to adapt the ideas presented in the text for use in their own systems. Further practical guidance is offered by the inclusion of several examples of common industrial processes amenable to the use of the authors' methods. Researchers interested in non-heuristic approaches to controller tuning or in decision-making after a Pareto set has been established and graduate students interested in beginning a career working with PID control and/or industrial controller tuning will find this book a valuable reference and source of ideas. Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
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