On fuzzy alternate control systems

被引：0

作者：

Onasanya, Babatunde Oluwaseun ^{[1
,2
]}

Feng, Yuming ^{[3
]}

Zhang, Wei ^{[4
]}

Wen, Shiping ^{[5
]}

Tang, Ning ^{[6
]}

机构：

[1] Chongqing Three Gorges Univ, Key Lab Intelligent Informat Proc & Control, Chongqing 404100, Peoples R China

[2] Univ Ibadan, Dept Math, Ibadan, Nigeria

[3] Chongqing Three Gorges Univ, Chongqing Engn Res Ctr Internet Things & Intellig, Chongqing 404100, Peoples R China

[4] Chongqing Three Gorges Univ, Sch Comp Sci & Engn, Chongqing 404100, Peoples R China

[5] Univ Technol, Fac Engn & Informat Technol, Australian AI Inst, Sydney, NSW 2007, Australia

[6] Chongqing Three Gorges Univ, Sch Three Gorges Artificial Intelligence, Chongqing 404100, Peoples R China

来源：

2021 13TH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTATIONAL INTELLIGENCE (ICACI) | 2021年

关键词：

alternate systems; intermittent control systems; fuzzy alternate control systems; fuzzy control matrix; tolerance of changeability of control; INTERMITTENT CONTROL; NONLINEAR-SYSTEMS; IMPULSIVE CONTROL; CHAOTIC SYSTEMS; SYNCHRONIZATION; STABILIZATION;

D O I：

10.1109/ICACI52617.2021.9435911

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Some researchers have worked on intermittent control and alternate control. In both cases, the choice of the control was a constant quantity. But, in real life, this situation is hard to come by for the reason that control may vary with time and circumstances owing to machine or human errors or both. Hence is the need to employ a method in which the control matrix is rather uncertain as is obtainable in real life.

引用

页码：172 / 178

页数：7

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