伺服机构的模糊控制:使用Mamdani和Takagi- Sugeno控制器的实用方法

IF 1.5 Q2 COMPUTER SCIENCE, THEORY & METHODS

International Journal of Fuzzy Logic and Intelligent Systems Pub Date : 2021-10-30 DOI:10.5121/ijfls.2021.11402

Renato A. Aguiar, Izabella Sirqueira

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引用次数: 0

摘要

本工作的主要目的是提出两种模糊控制器:一种基于Mamdani推理方法，另一种基于Takagi- Sugeno推理方法，这两种控制器都将被设计用于伺服机构的位置控制系统。为了确定Takagi- Sugeno方法在系统存在干扰和非线性时相对于Mamdani方法的优势，将对上述方法进行一些关于系统性能的比较。给出了仿真和实际应用结果，结果表明基于Takagi- Sugeno方法的控制器比基于Mamdani方法的控制器更有效。

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Fuzzy Control of a Servomechanism: Practical Approach using Mamdani and Takagi- Sugeno Controllers

The main objective of this work is to propose two fuzzy controllers: one based on the Mamdani inference method and another controller based on the Takagi- Sugeno inference method, both will be designed for application in a position control system of a servomechanism. Some comparations between the methods mentioned above will be made with regard to the performance of the system in order to identify the advantages of the Takagi- Sugeno method in relation to the Mamdani method in the presence of disturbances and nonlinearities of the system. Some results of simulation and practical application are presented and results obtained showed that controllers based on Takagi- Sugeno method is more efficient than controllers based on Mamdani method for this specific application.

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来源期刊

International Journal of Fuzzy Logic and Intelligent Systems COMPUTER SCIENCE, THEORY & METHODS-

CiteScore

2.80

自引率

23.10%

发文量

期刊介绍： The International Journal of Fuzzy Logic and Intelligent Systems (pISSN 1598-2645, eISSN 2093-744X) is published quarterly by the Korean Institute of Intelligent Systems. The official title of the journal is International Journal of Fuzzy Logic and Intelligent Systems and the abbreviated title is Int. J. Fuzzy Log. Intell. Syst. Some, or all, of the articles in the journal are indexed in SCOPUS, Korea Citation Index (KCI), DOI/CrossrRef, DBLP, and Google Scholar. The journal was launched in 2001 and dedicated to the dissemination of well-defined theoretical and empirical studies results that have a potential impact on the realization of intelligent systems based on fuzzy logic and intelligent systems theory. Specific topics include, but are not limited to: a) computational intelligence techniques including fuzzy logic systems, neural networks and evolutionary computation; b) intelligent control, instrumentation and robotics; c) adaptive signal and multimedia processing; d) intelligent information processing including pattern recognition and information processing; e) machine learning and smart systems including data mining and intelligent service practices; f) fuzzy theory and its applications.