NDLI: New Elite Multi-Parent Crossover Evolutionary Optimization Algorithm of Parameters Tuning of Fractional-Order PID Controller and Its Application

Content Provider	IEEE Xplore Digital Library
Author	Mingshan Cai Xianggao Pan Yunfeng Du
Copyright Year	2009
Abstract	PID control is one of the most common control method used for process control and fractional-order PIλDβ control that is the promotion and development of general integer-order PID control1. Compared to integer-order PID controller, fractional-order PIλDβ controller has more advantages that integer-order PID controller does not have, but the tuning method of fractional-order PID control is still a topic to be resolved, and it is rarely studied so far. In this paper, based on filtering algorithms and adopting the Matlab/Simulink software, a new method to effectively solve optimization problem of function is proposed, that is, on the basis of multi-parent crossover evolutionary optimization algorithm and by introduction of the elite-preservation strategy to enhance the selection pressure of parents in the process of crossover, the elite multi-parent crossover evolutionary optimization algorithm is constructed and the program EMPCOA1.0 is developed for the optimization of parameters tuning. Simulation results show that it is an effective tuning strategy, it also can be seen that better control quality can be achieved by using fractional-order PIλDβcontroller for nonlinear systems.
Starting Page	64
Ending Page	67
File Size	309888
Page Count	4
File Format	PDF
ISBN	9781424455430
e-ISBN	9781424455447
DOI	10.1109/ICICIC.2009.277
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-12-07
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Art Proportional control Three-term control Optimization methods Optimal control Filtering algorithms Automatic control Nonlinear control systems Control systems Fractional calculus
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Optimization for PID Control Parameters on Hydraulic Servo Control System Based on the Elite Multi-parent Crossover Evolutionary Algorithm

The controlling parameters tuning and its application of fractional order PID bacterial foraging-based oriented by particle swarm optimization

Tuning fractional order proportional integral controllers for fractional order systems

Design of an optimal fractional-order PID controller using multi-objective GA optimization

Optimal Tuning of Fractional Order PID Controller for DC Motor Speed Control Using Particle Swarm Optimization

Advanced particle swarm optimization-based PID controller parameters tuning

Optimization of fractional order PID controllers based on genetic algorithms

Optimal Genetic Algorithm for the Nonlinear PID Controller

Fractional-order [proportional derivative] controller for robust motion control: Tuning procedure and validation

New Elite Multi-Parent Crossover Evolutionary Optimization Algorithm of Parameters Tuning of Fractional-Order PID Controller and Its Application

Similar Documents

Optimization for PID Control Parameters on Hydraulic Servo Control System Based on the Elite Multi-parent Crossover Evolutionary Algorithm

The controlling parameters tuning and its application of fractional order PID bacterial foraging-based oriented by particle swarm optimization

Tuning fractional order proportional integral controllers for fractional order systems

Design of an optimal fractional-order PID controller using multi-objective GA optimization

Optimal Tuning of Fractional Order PID Controller for DC Motor Speed Control Using Particle Swarm Optimization

Advanced particle swarm optimization-based PID controller parameters tuning

Optimization of fractional order PID controllers based on genetic algorithms

Optimal Genetic Algorithm for the Nonlinear PID Controller

Fractional-order [proportional derivative] controller for robust motion control: Tuning procedure and validation

New Elite Multi-Parent Crossover Evolutionary Optimization Algorithm of Parameters Tuning of Fractional-Order PID Controller and Its Application