An adaptive extended fuzzy function state-observer based control with unknown control direction

Beyhan, Selami

doi:10.5505/pajes.2016.06887

Cited by 1 publication

(1 citation statement)

References 19 publications

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“…Various methods are proposed in literature to improve the performance of fuzzy controls. Beyhan aims to apply adaptive expanded fuzzy function observer based controller, proposed for the control of nonlinear unknown and uncertain systems, and adaptive extended fuzzy function observer based controller to real-time system and provide control in the direction of the unknown control signal [1]. In the studies of Gencer et al, A proportional-derivative (PD) controller was designed and digital signal processor based position control of Brushless Direct Current Motors (BDCM) was realized [2].…”

Section: Introductionmentioning

confidence: 99%

Optimal Adjustment of Fuzzy Controller Based Evolutionary Algorithms For Driving Electric Motor with Computer Interface

Bulut¹

2020

Preprint

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This study focused on the development of a system based on evolutionary Algorithms to obtain the optimum parameters of the fuzzy controller to increase the convergence speed and accuracy of the controller. The aim of the study is to design fuzzy controller without expert’s knowledge by using evolutionary genetic algorithms and carry out on a DC motor. The design is based on optimization of rule bases of fuzzy controller. In the learning stage, the obtained rule base fitness values are measured by working the rule base on the controller. The learning stage is repeated the termination criteria. The proposed fuzzy controller is performed on the dc motor from a PC program using a interface circuit.

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Section: Introductionmentioning

confidence: 99%