Adaptive fuzzy control of DC motors using state and output feedback

被引：66

作者：

Rigatos, Gerasimos G. ^{[1
]}

机构：

[1] Ind Syst Inst, Unit Ind Automat, Rion 26504, Greece

来源：

ELECTRIC POWER SYSTEMS RESEARCH | 2009年 / 79卷 / 11期

关键词：

DC motors; Adaptive fuzzy control; State feedback; Output feedback; H infinity tracking; Neuro-fuzzy approximators; State observer; Field-oriented induction motors; NEURAL-NETWORK CONTROL; H-INFINITY TRACKING; NONLINEAR-SYSTEMS; IMPLEMENTATION; IDENTIFICATION; ROBUST;

D O I：

10.1016/j.epsr.2009.06.007

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Conventional PID of state feedback controllers for DC motors have poor performance when changes of the motor or load dynamics take place. To handle this shortcoming adaptive fuzzy control of DC motors is proposed. Neuro-fuzzy networks are used to approximate the unknown motor dynamics. The information needed to generate the control signal comes from feedback of the full state vector or from feedback of only the system's output. In the latter case a state observer is used to estimate the parameters of the state vector. The stability of the closed-loop system is proved with the use of Lyapunov analysis. The performance of the proposed control approach is evaluated through simulation tests. (C) 2009 Elsevier B.V. All rights reserved.

引用

页码：1579 / 1592

页数：14

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