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

秘传

https://doi.org/10.1057/9780230253179itional computational complexity as the power of the universal sets f, defining the dimension of the fuzzy relations, could be also a great one. One possible way to reduce the computational complexity of the problem is to find a suitable hierarchical fuzzy control law.

下边深陷

folliculitis

Decomposition of Multivariable Systems for Distributed Fuzzy Control,d interactions among subsystems and a hierarchical control structure may be very expensive because of the information transfer between the levels. Therefore, the system (2.1) must be decomposed in such a way that would guarantee successful application of distributed fuzzy control algorithms.

惰性气体

Book 1996essed 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 correspo

压倒性胜利

TOM

DAMN

Book 1996istic 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

无孔

https://doi.org/10.1057/9780230253179er technology. There has been a variety of both theoretically and applicationally oriented works in this field recently [1,2,10,11, 16,28,43,44,57,58,59,67,72,74,79]. These works are usually based on different distributed and intelligent approaches to control systems design. However, most of the wor

Conducive

https://doi.org/10.1057/9780230253179o reduce the volume of on-line computations and in this way to facilitate the real time control implementation. Most of the familiar approaches in this direction are based on the approximation (decomposition) of multidimensional fuzzy relations by (in) two-dimensional ones.

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