{"title":"Synthesis and Initialization of Adaptive Neuro-Fuzzy Control Based on the SDRE Technique for a Two-Link Manipulator","authors":"D. A. Makarov, V. A. Puzach","doi":"10.1134/s0361768823100031","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>One of the open problems in modern control theory is synthesis of adaptive control for nonlinear systems with parametric uncertainty and analysis of stability of the corresponding closed-loop system. Fuzzy logic is one of the approaches that can take into account nonlinearity and uncertainty of the plant. Affine systems constitute a class of nonlinear systems often used to solve various practical problems. For this class, there are a number of methods for synthesis of controllers, in particular, a method based on the matrix Riccati equation with state-dependent coefficients. In this paper, for a given class of nonlinear systems, an adaptation mechanism of a neuro-fuzzy controller that approximates the control synthesized by the SDRE method is used for the first time. The main contribution of this work is the architecture of the neuro-fuzzy network and methods for its initialization. The proposed approach is applied to the model of a two-link manipulator with uncertain coefficients. The conducted numerical experiments demonstrate the effectiveness of the synthesized control in terms of the selected quality criteria.</p>","PeriodicalId":54555,"journal":{"name":"Programming and Computer Software","volume":"17 1","pages":""},"PeriodicalIF":0.7000,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Programming and Computer Software","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1134/s0361768823100031","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0
Abstract
One of the open problems in modern control theory is synthesis of adaptive control for nonlinear systems with parametric uncertainty and analysis of stability of the corresponding closed-loop system. Fuzzy logic is one of the approaches that can take into account nonlinearity and uncertainty of the plant. Affine systems constitute a class of nonlinear systems often used to solve various practical problems. For this class, there are a number of methods for synthesis of controllers, in particular, a method based on the matrix Riccati equation with state-dependent coefficients. In this paper, for a given class of nonlinear systems, an adaptation mechanism of a neuro-fuzzy controller that approximates the control synthesized by the SDRE method is used for the first time. The main contribution of this work is the architecture of the neuro-fuzzy network and methods for its initialization. The proposed approach is applied to the model of a two-link manipulator with uncertain coefficients. The conducted numerical experiments demonstrate the effectiveness of the synthesized control in terms of the selected quality criteria.
期刊介绍：
Programming and Computer Software is a peer reviewed journal devoted to problems in all areas of computer science: operating systems, compiler technology, software engineering, artificial intelligence, etc.
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