On monotonicity of takagi-sugeno fuzzy systems with ellipsoidal regions

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F16%3A00307108" target="_blank" >RIV/68407700:21230/16:00307108 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/TFUZZ.2016.2540064" target="_blank" >http://dx.doi.org/10.1109/TFUZZ.2016.2540064</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TFUZZ.2016.2540064" target="_blank" >10.1109/TFUZZ.2016.2540064</a>

Jazyk výsledku

angličtina

Název v původním jazyce

On monotonicity of takagi-sugeno fuzzy systems with ellipsoidal regions

Popis výsledku v původním jazyce

This paper presents sufficient conditions on monotonicity of a Takagi-Sugeno (T-S) fuzzy system with linear submodels in the consequents of the rules where the input space is considered to be partitioned to ellipsoidal regions. Such regions commonly arise in practice if clustering algorithms are used to identify a fuzzy model from measured data. By the monotonicity, it is meant that the partial derivatives of the output of the mapping represented by the fuzzy model with respect to all inputs are nonnegative on a given universe of discourse. The conditions are given in the form of linear matrix inequalities with respect to the parameters of the submodels that may be useful in solving associated optimization problems via efficient semidefinite programming techniques. The proposed conditions reduce conservatism of the existing ones from two reasons. First, the conservatism is introduced only once, since the conditions are not separated between antecedent and consequent parts of fuzzy rules. Second, the domain of interest where monotonicity is enforced may be restricted. The proposed algorithm is illustrated on least-squares approximation of a multivariate function by a monotonic T-S fuzzy system.

Název v anglickém jazyce

On monotonicity of takagi-sugeno fuzzy systems with ellipsoidal regions

Popis výsledku anglicky

This paper presents sufficient conditions on monotonicity of a Takagi-Sugeno (T-S) fuzzy system with linear submodels in the consequents of the rules where the input space is considered to be partitioned to ellipsoidal regions. Such regions commonly arise in practice if clustering algorithms are used to identify a fuzzy model from measured data. By the monotonicity, it is meant that the partial derivatives of the output of the mapping represented by the fuzzy model with respect to all inputs are nonnegative on a given universe of discourse. The conditions are given in the form of linear matrix inequalities with respect to the parameters of the submodels that may be useful in solving associated optimization problems via efficient semidefinite programming techniques. The proposed conditions reduce conservatism of the existing ones from two reasons. First, the conservatism is introduced only once, since the conditions are not separated between antecedent and consequent parts of fuzzy rules. Second, the domain of interest where monotonicity is enforced may be restricted. The proposed algorithm is illustrated on least-squares approximation of a multivariate function by a monotonic T-S fuzzy system.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

BC - Teorie a systémy řízení

OECD FORD obor

—

Projekt

<a href="/cs/project/GA16-21961S" target="_blank" >GA16-21961S: Mechatronické struktury se silně distribuovanými aktuátory a senzory</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

IEEE Transactions on Fuzzy Systems

ISSN

1063-6706

e-ISSN

—

Svazek periodika

24

Číslo periodika v rámci svazku

6

Stát vydavatele periodika

JP - Japonsko

Počet stran výsledku

6

Strana od-do

1673-1678

Kód UT WoS článku

000391718300002

EID výsledku v databázi Scopus

2-s2.0-85008430164