Fuzzy Logic Control Design Based on the Genetic Algorithm for a Modular Servo System

Ivanova, Donka; Dejanov, Martin

doi:10.1109/elma52514.2021.9503052

Cited by 4 publications

(2 citation statements)

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“…Although fuzzy logic does not require an exact mathematical model, tuning this method is quite labor-intensive. The development of the method is also influenced by the difficulty of predicting its behavior under different conditions and achieving optimal performance without loss of computational efficiency [89,92].…”

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confidence: 99%

“…The use of this type of control allows for adapting the control system to operate in changing conditions, even under the influence of various stochastic disturbances such as changes in load, detection of mechanical errors, etc. Fuzzy logic control is effective in situations where predicting the behavior of the mathematical model of the system is challenging, and there is no possibility of its precise determination [89,92].…”

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confidence: 99%

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Principles and Methods of Servomotor Control: Comparative Analysis and Applications

Autsou,

Kudelina,

Vaimann

et al. 2024

Applied Sciences

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Servomotors have found widespread application in many areas, such as manufacturing, robotics, automation, and others. Thus, the control of servomotors is divided into various principles and methods, leading to a high diversity of control systems. This article provides an overview of types of servomotors and their basic principles and control methods. Principles such as digital signal processing, feedback control principle, field-oriented control, and integration with Industry 4.0 are discussed. Based on these control principles, the article presents popular control methods: PWM control, current control, two-loop control, fuzzy-logic control, and programmable control. The article concludes with a comparison of the presented methods on several criteria, and as an example, it includes the results of modeling a servomotor using the fuzzy-logic control method.

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