Fuzzy controller with stability and performance rules for nonlinear systems

Lam, Hak‐Keung; Leung, F.H.F.

doi:10.1016/j.fss.2006.06.005

Cited by 45 publications

(18 citation statements)

References 23 publications

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“…Fuzzy logic [1,5,6,16] plays an important role in accounting for uncertainty when making decisions in control systems. Until 2013, all studies on fuzzy derivative, fuzzy integral and fuzzy differential equations had been conducted based on type-1 fuzzy sets (T1FSs).…”

Section: Introductionmentioning

confidence: 99%

A photovoltaic array simulator based on current feedback fuzzy PID control

Shao

Meng

Zhou

et al. 2015

IFS

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Abstract.A photovoltaic array simulator is designed based on a Buck DC converter with a fuzzy PID control algorithm to account for current feedback. The conventional PID controller cannot self-tune the parameters, therefore the new algorithm uses a fuzzy controller to solve the problem. The difference between the reference current and the real-time feedback current of the Buck converter and its rate of change are regarded as two input variables of the fuzzy controller. The fuzzy controller outputs the adjustment quantities, which are then used to adjust the PID parameters. Next, the duty cycle of the electronic power switch is adjusted by a closed-loop fuzzy PID algorithm to make the output current of the simulator work at the anticipated point of the photovoltaic array on the I-V characteristic curve and realize the simulation of photovoltaic characteristics. Results of the simulation and experiment indicate that the proposed fuzzy PID control simulator can not only accurately simulate the static output characteristics of a photovoltaic cell, but can also rapidly realize the dynamic characteristics when the load or the external environment changes. The approximate error was less than 3.6%, the overshoot was less than 3.5%, the ripple coefficient was less than 3%, and the tracking time was approximately 0.3s. The fuzzy PID control simulator can work well as PV array experiment equipment for the research and development of photovoltaic systems.

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Section: Introductionmentioning

confidence: 99%

A photovoltaic array simulator based on current feedback fuzzy PID control

Shao

Meng

Zhou

et al. 2015

IFS

View full text Add to dashboard Cite

show abstract

“…To solve this problem, since the integration of the FC in the control laws of the systems, several researchers tried to develop practical methods for the study of systems stability [2,4,5,10,15,40]. In their studies, the majority of these researchers used, for the modeling and the control of the nonlinear systems, the TSK fuzzy inference which system.…”

Section: Introductionmentioning

confidence: 99%

Stability and robustness of fuzzy adaptive control of nonlinear systems

Ketata

Rezgui

Derbel

2011

Applied Soft Computing

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“…Stability of both linear and nonlinear uncertain systems has received a considerable attention in the past decades (see for example, Tanaka & Sugeno, 1992;Tanaka, Ikeda, & Wang, 1996;Feng, Cao, Kees, et al 1997;Teixeira & Zak, 1999;Lee, Park, & Chen, 2001;Park, Kim, & Park, 2001;Chen, Liu, & Tong, 2006;Lam & Leung, 2007, and references therein). Fuzzy logical control (FLC) has proved to be a successful control approach for a great many complex nonlinear systems.…”

Section: Introductionmentioning

confidence: 99%

Robust Fuzzy Control of Parametric Uncertain Nonlinear Systems Using Robust Reliability Method

Guo¹

2011

Robust Control, Theory and Applications

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Fuzzy controller with stability and performance rules for nonlinear systems

Cited by 45 publications

References 23 publications

A photovoltaic array simulator based on current feedback fuzzy PID control

A photovoltaic array simulator based on current feedback fuzzy PID control

Stability and robustness of fuzzy adaptive control of nonlinear systems

Robust Fuzzy Control of Parametric Uncertain Nonlinear Systems Using Robust Reliability Method

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