Fuzzy control system performance enhancement by iterative learning control

被引：91

作者：

Precup, Radu-Emil ^{[1
]}

Preitl, Stefan ^{[1
]}

Tar, Jozsef K. ^{[2
]}

Tomescu, Marius L. ^{[3
]}

Takacs, Marta ^{[2
]}

Korondi, Peter ^{[4
]}

Baranyi, Peter ^{[5
]}

机构：

[1] Politehn Univ Timisoara, Dept Automat & Appl Informat, Timisoara 300223, Romania

[2] John von Neumann Fac Informat, Budapest Tech Polytech Inst, Inst Intelligent Engn Syst, H-1034 Budapest, Hungary

[3] Aurel Vlaicu Univ Arad, Dept Comp Sci, Arad 310130, Romania

[4] Budapest Univ Technol & Econ, Dept Automat & Appl Informat, H-1117 Budapest, Hungary

[5] Hungarian Acad Sci, Comp & Automat Res Inst, Cognit Vis Res Grp, H-1111 Budapest, Hungary

来源：

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS | 2008年 / 55卷 / 09期

关键词：

fuzzy control; iterative methods; learning control systems (CSs); servo systems; stability;

D O I：

10.1109/TIE.2008.925322

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper suggests low-cost fuzzy control solutions that ensure the improvement of control system (CS) performance indices by merging the benefits of fuzzy control and iterative learning control (ILC). The solutions are expressed in terms of three fuzzy CS (FCS) structures that employ ILC algorithms and a unified design method focused on Takagi-Sugeno proportional-integral fuzzy controllers (PI-FCs). The PI-FCs are dedicated to a class of servo systems with linear/linearized controlled plants characterized by second-order dynamics and integral type. The invariant set theorem by Krasovskii and LaSalle with quadratic Lyapunov function candidates is applied to guarantee the convergence of the ILC algorithms and enable proper setting of the PI-FC parameters. The linear PI controller parameters tuned by the extended symmetrical optimum method are mapped onto the PI-FC ones by the modal equivalence principle. Real-time experimental results for a dc-based servo speed CS are included.

引用

页码：3461 / 3475

页数：15

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