A Review of Fuzzy Logic and Neural Network Based Intelligent Control Design for Discrete-Time Systems
Over the last few decades, the intelligent control methods such as fuzzy logic control (FLC) and neural network (NN) control have been successfully used in various applications. The rapid development of digital computer based control systems requires control signals to be calculated in a digital or...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2016-01-01
|
| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2016/7217364 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832561634139176960 |
|---|---|
| author | Yiming Jiang Chenguang Yang Hongbin Ma |
| author_facet | Yiming Jiang Chenguang Yang Hongbin Ma |
| author_sort | Yiming Jiang |
| collection | DOAJ |
| description | Over the last few decades, the intelligent control methods such as fuzzy logic control (FLC) and neural network (NN) control have been successfully used in various applications. The rapid development of digital computer based control systems requires control signals to be calculated in a digital or discrete-time form. In this background, the intelligent control methods developed for discrete-time systems have drawn great attentions. This survey aims to present a summary of the state of the art of the design of FLC and NN-based intelligent control for discrete-time systems. For discrete-time FLC systems, numerous remarkable design approaches are introduced and a series of efficient methods to deal with the robustness, stability, and time delay of FLC discrete-time systems are recommended. Techniques for NN-based intelligent control for discrete-time systems, such as adaptive methods and adaptive dynamic programming approaches, are also reviewed. Overall, this paper is devoted to make a brief summary for recent progresses in FLC and NN-based intelligent control design for discrete-time systems as well as to present our thoughts and considerations of recent trends and potential research directions in this area. |
| format | Article |
| id | doaj-art-50358f0c6a36477db711a95005dd1ba4 |
| institution | Kabale University |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-50358f0c6a36477db711a95005dd1ba42025-02-03T01:24:31ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2016-01-01201610.1155/2016/72173647217364A Review of Fuzzy Logic and Neural Network Based Intelligent Control Design for Discrete-Time SystemsYiming Jiang0Chenguang Yang1Hongbin Ma2Key Lab of Autonomous Systems and Networked Control (MOE), School of Automation Science and Engineering, South China University of Technology, Guangzhou 510640, ChinaKey Lab of Autonomous Systems and Networked Control (MOE), School of Automation Science and Engineering, South China University of Technology, Guangzhou 510640, ChinaState Key Lab of Intelligent Control and Decision of Complex Systems, Beijing Institute of Technology, Beijing 100081, ChinaOver the last few decades, the intelligent control methods such as fuzzy logic control (FLC) and neural network (NN) control have been successfully used in various applications. The rapid development of digital computer based control systems requires control signals to be calculated in a digital or discrete-time form. In this background, the intelligent control methods developed for discrete-time systems have drawn great attentions. This survey aims to present a summary of the state of the art of the design of FLC and NN-based intelligent control for discrete-time systems. For discrete-time FLC systems, numerous remarkable design approaches are introduced and a series of efficient methods to deal with the robustness, stability, and time delay of FLC discrete-time systems are recommended. Techniques for NN-based intelligent control for discrete-time systems, such as adaptive methods and adaptive dynamic programming approaches, are also reviewed. Overall, this paper is devoted to make a brief summary for recent progresses in FLC and NN-based intelligent control design for discrete-time systems as well as to present our thoughts and considerations of recent trends and potential research directions in this area.http://dx.doi.org/10.1155/2016/7217364 |
| spellingShingle | Yiming Jiang Chenguang Yang Hongbin Ma A Review of Fuzzy Logic and Neural Network Based Intelligent Control Design for Discrete-Time Systems Discrete Dynamics in Nature and Society |
| title | A Review of Fuzzy Logic and Neural Network Based Intelligent Control Design for Discrete-Time Systems |
| title_full | A Review of Fuzzy Logic and Neural Network Based Intelligent Control Design for Discrete-Time Systems |
| title_fullStr | A Review of Fuzzy Logic and Neural Network Based Intelligent Control Design for Discrete-Time Systems |
| title_full_unstemmed | A Review of Fuzzy Logic and Neural Network Based Intelligent Control Design for Discrete-Time Systems |
| title_short | A Review of Fuzzy Logic and Neural Network Based Intelligent Control Design for Discrete-Time Systems |
| title_sort | review of fuzzy logic and neural network based intelligent control design for discrete time systems |
| url | http://dx.doi.org/10.1155/2016/7217364 |
| work_keys_str_mv | AT yimingjiang areviewoffuzzylogicandneuralnetworkbasedintelligentcontroldesignfordiscretetimesystems AT chenguangyang areviewoffuzzylogicandneuralnetworkbasedintelligentcontroldesignfordiscretetimesystems AT hongbinma areviewoffuzzylogicandneuralnetworkbasedintelligentcontroldesignfordiscretetimesystems AT yimingjiang reviewoffuzzylogicandneuralnetworkbasedintelligentcontroldesignfordiscretetimesystems AT chenguangyang reviewoffuzzylogicandneuralnetworkbasedintelligentcontroldesignfordiscretetimesystems AT hongbinma reviewoffuzzylogicandneuralnetworkbasedintelligentcontroldesignfordiscretetimesystems |