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Titlebook: Distributed Fuzzy Control of Multivariable Systems; Alexander Gegov Book 1996 Springer Science+Business Media Dordrecht 1996 algorithms.an

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发表于 2025-3-21 16:34:02 | 显示全部楼层 |阅读模式
书目名称Distributed Fuzzy Control of Multivariable Systems
编辑Alexander Gegov
视频video
丛书名称International Series in Intelligent Technologies
图书封面Titlebook: Distributed Fuzzy Control of Multivariable Systems;  Alexander Gegov Book 1996 Springer Science+Business Media Dordrecht 1996 algorithms.an
描述It is known that many control processes are characterized by both quantitative and qualitative complexity. Tbe quantitative complexity is usually expressed in a large number of state variables, respectively high dimensional mathematical model. Tbe qualitative complexity is usually associated with uncertain behaviour, respectively approximately known mathematical model. If the above two aspects of complexity are considered separately, the corresponding control problem can be easily solved. On one hand, large scale systems theory has existed for more than 20 years and has proved its capabilities in solving high dimensional control problems on the basis of decomposition, hierarchy, decentralization and multilayers. On the other hand, the fuzzy linguistic approach is almost at the same age and has shown its advantages in solving approximately formulated control problems on the basis of linguistic reasoning and logical inference. However, if both aspects of complexity are considered together, the corresponding control problem becomes non-trivial and does not have an easy solution. Modem control theory and practice have reacted accordingly to the above mentioned new cballenges of tbe day
出版日期Book 1996
关键词algorithms; analog; applied mathematics; diagnosis; fuzzy; system
版次1
doihttps://doi.org/10.1007/978-94-015-8640-5
isbn_softcover978-90-481-4652-9
isbn_ebook978-94-015-8640-5Series ISSN 1382-3434
issn_series 1382-3434
copyrightSpringer Science+Business Media Dordrecht 1996
The information of publication is updating

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Decomposition of Multivariable Systems for Distributed Fuzzy Control,lations in this case will be n.m. However, this may be quite a great number and therefore time constraints in on-line control computations may be violated. On the other hand, an arbitrary decomposition of the system with the purpose of applying decentralized or hierarchical fuzzy control algorithms
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Hierarchical Fuzzy Control of Multivariable Systems, n.m. This could be obviously quite a great number and time constraints in on-line control computations may be violated. Moreover, the problem has additional computational complexity as the power of the universal sets f, defining the dimension of the fuzzy relations, could be also a great one. One p
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Decentralized Fuzzy Control of Multivariable Systems by Direct Decomposition,e-output, single-input-multiple-output or multiple-input-multiple-output subsystems. In the case of Siso subsystems, the original system is supposed to possess N inputs and outputs. In the case of Nsiso subsystems, the original system possesses a number of inputs or / and outputs, bigger than N.
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Multilayer Fuzzy Control of Multivariable Systems By Passive Decomposition,e-output systems. In this case, the “if” parts in (2.1) are repeated for each output variable u., i=1,m and the control law (2.2) is obtained where the two-dimensional relations R., j = 1,n, i=1,m are calculated by (2.3).
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Introduction,59,67,72,74,79]. These works are usually based on different distributed and intelligent approaches to control systems design. However, most of the works use the fuzzy linguistic approach as a synonym of “intelligence” because of its human-like capabilities of approximate reasoning and logical inference.
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