2018-12-16T13:18:43Z
http://ijfs.usb.ac.ir/?_action=export&rf=summon&issue=283
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2014
11
5
Cover vol. 11, no. 5, October 2014
2014
10
29
0
http://ijfs.usb.ac.ir/article_2683_cc8b69bce4395e0f795ef058c1b724a7.pdf
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2014
11
5
Indirect Adaptive Interval Type-2 Fuzzy PI Sliding Mode Control for a Class of Uncertain Nonlinear Systems
Mostafa
Ghaemi
Mohammad-Reza
Akbarzadeh-Totonchi
Controller design remains an elusive and challenging problem foruncertain nonlinear dynamics. Interval type-2 fuzzy logic systems (IT2FLS) incomparison with type-1 fuzzy logic systems claim to effectively handle systemuncertainties especially in the presence of disturbances and noises, but lack aformal mechanism to guarantee performance. In contrast, adaptive sliding modecontrol (ASMC) provides a robust mechanism to provide system stability againstparameter changes and uncertainties, but suffers from chattering phenomenon.In this paper, a stable indirect adaptive interval type-2 fuzzy PI sliding modecontroller (AIT2FSMC) is investigated for a class of nonlinear systems in thepresence of system's unmodeled dynamics and external disturbances. The addedProportional Integral (PI) structure is used to further attenuate the chatteringproblem that is common in sliding mode control systems. The interval type-2fuzzy adaptation law adjusts the consequent parameters of the rules based on aLyapunov synthesis approach. Mathematical analysis proves the closed loopasymptotic stability, while benefiting from human expert knowledge to improvetransient response of the system. Application to two nonlinear systems verifiesthe robustness of the proposed AIT2FSMC approach in the presence ofuncertainties and bounded external disturbances, especially when disturbanceshave fast changes and large magnitudes.
Interval type-2 fuzzy logic systems
Sliding mode control
Uncertainty
Adaptive PI control
Lyapunov theory
Nonlinear systems
2014
10
30
1
21
http://ijfs.usb.ac.ir/article_1698_6cd8c0b441200a1b59cf32f2e4deb60a.pdf
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2014
11
5
FUZZY AHP METHOD FOR PLANT SPECIES SELECTION IN MINE RECLAMATION PLANS: CASE STUDY SUNGUN COPPER MINE
Iraj
Alavi
All steps of a mining project generally disturb the environment'soriginal condition during construction. Therefore, it is crucial toimplement an appropriate mine reclamation plan throughout all mineplanning stages from sustainable and environmental point of view.Planting the suitable plant species in each step of any reclamationplan and each area is one of the necessities in this respect.Selecting of plant species is carried out on the basis of theprimary factors. After that priorities between the selected speciesare defined on account of the secondary factors by a MCDM model. Inthis regard, a Fuzzy AHP approach was used. This method was appliedto Sungun open pit copper mine in Iran as a case study. Decisionmaking was conducted on the basis of oral judgments and groupexpertise in the case study. The results achieved from the analysesshowed that the priorities of alternatives are as Maple, Ash, Oak,Barberry, Paliurus spina -Christi, Sloe, respectively.
Mine reclamation
Plant species selection
MCDM
Fuzzy AHP
Sungun open pit copper mine
Maple
2014
10
30
23
38
http://ijfs.usb.ac.ir/article_1699_4f6219400db3a73b14fe1ac316969856.pdf
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2014
11
5
Some Remarks on Generalized Sequence Space of Bounded Variation of Sequences of Fuzzy Numbers
H.
Altinok
M.
Et
R.
Colak
The idea of difference sequences of real (or complex) numbers was introducedby Ki zmaz cite{Kizmaz}. In this paper, using the difference operator and alacunary sequence, we introduce and examine the class of sequence $bv_{theta}left( Delta,mathcal{F}right) .$ We study some of its properties likesolidity, symmetricity, etc.
Fuzzy number
Difference operator
Lacunary
sequence
2014
10
30
39
46
http://ijfs.usb.ac.ir/article_1700_270f02138ecd150c48eccb6291138b41.pdf
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2014
11
5
Characterizations and properties of bounded $L$-fuzzy sets
Hua-Peng
Zhang
In 1997, Fang proposed the concept of boundedness of $L$-fuzzy setsin $L$-topological vector spaces. Since then, this concept has beenwidely accepted and adopted in the literature. In this paper,several characterizations of bounded $L$-fuzzy sets in$L$-topological vector spaces are obtained and some properties ofbounded $L$-fuzzy sets are investigated.
$L$-topological vector space
Bounded $L$-fuzzy set
Induced $L$-topology
2014
10
30
47
53
http://ijfs.usb.ac.ir/article_1721_1b512eacef6bd80d8d50286d0e43cd01.pdf
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2014
11
5
Fuzzy rules for fuzzy $overline{X}$ and $R$ control charts
M.
Khademi
V.
Amirzadeh
Statistical process control ($SPC$), an internationally recognized technique for improving product quality and productivity, has been widely employed in various industries. $SPC$ relies on the use of control charts to monitor a manufacturing process for identifying causes of process variation and signaling the necessity of corrective action for the process. Fuzzy data exist ubiquitously in the modern manufacturing process, and in this paper, two alternative approaches to fuzzy control charts are developed for monitoring sample averages and range. These approaches are based on "fuzzy mode" and "fuzzy rules" methods, when the measures are expressed by non-symmetric triangular fuzzy numbers. In contrast to the existing fuzzy control charts, the proposed approach does not require the use of the defuzzification and this prevents the loss of information included in samples. A numeric example illustrates the performance of the method and interprets the results.
Fuzzy control charts
Fuzzy rules
Fuzzy numbers
Fuzzy mode
2014
10
30
55
66
http://ijfs.usb.ac.ir/article_1722_b706f471fcd59f5cefef2e6ebb39ab63.pdf
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2014
11
5
Weighted similarity measure on interval-valued fuzzy sets and its application to pattern recognition
M.
Arefi
S. M.
Taheri
A new approach to define the similarity measure betweeninterval-valued fuzzy sets is presented. The proposed approach isbased on a weighted measure in which the normalized similaritiesbetween lower functions and also between upper functions arecombined by a weight parameter. The properties of this similaritymeasure are investigated. It is shown that, the proposed measurehas some advantages in comparison with the commonly usedsimilarity measures.
Interval-valued fuzzy set
Intuitionistic fuzzy set
Pattern
recognition
Similarity measure
2014
10
30
67
79
http://ijfs.usb.ac.ir/article_1723_990861478a72bbd5c595d6077a046f00.pdf
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2014
11
5
Fixed point results in fuzzy metric-like spaces
Satish
Shukla
Mujahid
Abbas
In this paper, the concept of fuzzy metric-like spaces is introduced which generalizes the notion of fuzzy metric spaces given by George and Veeramani cite{Vee1}. Some fixed point results for fuzzy contractive mappings on fuzzy metric-like spaces are derived. These results generalize several comparable results from the current literature. We also provide illustrative examples in support of our new results where result from current literature are not applicable.
Fuzzy metric space
Fuzzy metric-like space
Fuzzy contractive mapping
Fixed point
2014
10
30
81
92
http://ijfs.usb.ac.ir/article_1724_8623f897d8bd53f9f275d919ae8777d9.pdf
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2014
11
5
$L$-enriched topological systems---a common framework of $L$-topology and $L$-frames
M.
Liu
Employing the notions of the strong $L$-topology introduced by Zhangand the $L$-frame introduced by Yao and the concept of $L$-enrichedtopological system defined in the present paper, we constructadjunctions among the categories {bf St$L$-Top} of strong$L$-topological spaces, {bf S$L$-Loc} of strict $L$-locales and{bf $L$-EnTopSys} of $L$-enriched topological systems. All of theseconcepts are essentially based on the theory of $L$-enrichedcategories, thus we obtain a unified enriched-categorical version ofthe classical adjunctions among the categories {bf Top} oftopological spaces, {bf Loc} of locales and {bf TopSys} oftopological systems, as well as a unified enriched-categoricalapproach to treating these concepts.
Enriched category
Adjunction
$L$-ordered set
Strong
$L$-topology
$L$-enriched topological system
$L$-frame
2014
10
30
93
103
http://ijfs.usb.ac.ir/article_1725_ad67a8fcc772d02492c67d93d348e9c0.pdf
Iranian Journal of Fuzzy Systems
IJFS
1735-0654
1735-0654
2014
11
5
Persian-translation vol. 11, no. 5, October 2014
2014
10
29
107
114
http://ijfs.usb.ac.ir/article_2684_3bc1329c2939f13fd5ee75e2b24c42d7.pdf