Fuzzy Systems by Ahmad Taher Azar

By Ahmad Taher Azar

Show description

Read Online or Download Fuzzy Systems PDF

Similar control systems books

Adaptive Control of Ill-Defined Systems

There are a few kinds of advanced structures which are outfitted like clockwork, with well-defined elements that have interaction in well-defined methods, in order that the motion of the full should be accurately analyzed and expected with accuracy and precision. a few structures should not themselves so well-defined, yet they are often modeled in ways in which are like expert pilots in well-built planes, or electrolyte stability in fit people.

Modeling and Control of Economic Systems 2001. A Proceedings volume from the 10th IFAC Symposium, Klagenfurt, Austria, 6 – 8 September 2001

This quantity comprises papers awarded on the IFAC symposium on Modeling and keep an eye on of monetary platforms (SME 2001), which used to be held on the college of Klagenfurt, Austria. The symposium introduced jointly scientists and clients to discover present theoretical advancements of modeling suggestions for financial structures.

Cyber Security: Analytics, Technology and Automation

The ebook, as well as the cyber threats and know-how, procedures cyber protection from many aspects as a social phenomenon and the way the implementation of the cyber defense method is conducted. The ebook provides a profound proposal of the main spoken phenomenon of this time. The ebook is appropriate for a wide-ranging viewers from graduate to professionals/practitioners and researchers.

Additional info for Fuzzy Systems

Example text

Thus, we shall also focus on taking advantage of the FWLF approach to derive less conservative conditions for the solvability of the stabilization problem (for lack of space, the PLF approach will be not discussed in this chapter). B. Main issues Most stabilization conditions based on the FWLF are formulated in terms of parameterized linear matrix inequalities (PLMIs), which causes the following primary practical difficulty: the PLMI-based condition involves an infinite number of LMI-based conditions and thus the task of establishing a controller is intractable numerically.

Then, the robust stability with H∞ disturbance attenuation problem of fuzzy system is converted as the robust stability and robust stability with H∞ disturbance attenuation problems of equivalent uncertain system. Since λi ( x( k )) satisfies (13), we have λr ( x( k )) = 1 − [ λ1 ( x( k )) + λ2 ( x( k )) + " + λr −1 ( x( k ))]. It follows from this relationship that r ∑ λi ( x( k ))( Ai + ΔAi ) = Ar + H 1r F( k )E1r + λ1 ( x( k ))[ A1r + H 1r F1r ( k )E1r ] i =1 + " + λ r − 1 ( x( k ))[ Ar − 1 ,r + H r − 1 ,r Fr − 1 ,r ( k )Er − 1 ,r ] ~ ~ = Ar + H 1F ( k ) A where Air = Ai − Ar , i = 1 ," , r − 1 H 1 = [ I I " I H 11 H 12 " H 1r ],  F( k ) = diag [λ1 ( k )I " λr − 1 ( k )I λ1 (t )F1 ( k ) " λr (t )Fr ( k )], ~ T T A = [ A1Tr AT2 r " ArT− 1,r E11 E12 " E1Tr ]T .

Thus, we consider local sector nonlinearity. This is reasonable as variables of physical systems are always bounded. 1- (b) shows the local sector nonlinearity, where two lines become the local sectors under x(t ) ∈ [t1 , t2 ] . The T-S fuzzy model exactly represents the nonlinear system in the “local” region, that is, x(t ) ∈ [t1 , t2 ] , which is described as follows: 2 ∇x(t ) = f ( x(t )) = ∑θi (t )ai x(t ), (16) i =1 where θ 1 (t ) = f ( x(t )) − a2 x(t ) w2 = , w1 + w2 a1x(t ) − a2 x(t ) (17) θ 2 (t ) = a x(t ) − f ( x(t )) w1 = 1 .

Download PDF sample

Rated 4.44 of 5 – based on 14 votes