4483

4211

كارشناسي ارشد

كنترل

اصفهان: دانشگاه صنعتي اصفهان، دانشكده برق وكامپيوتر

1387

ده، 99،[II]ص: مصور، جدول، نمودار

ص.ع. به انگليسي و فارسي

سعيد حسين نيا، فريد شيخ الاسلام

جواد عسكري

29/2/1388

محمدرضا احمد زاده، مريم ذكري

مهندسي برق و كامپيوتر

ID4211

به فارسي وانگليسي: قابل رويت درنسخه ديجيتال

100 Granular Computing Rough and Fuzzy Rough System Identification and Controller Design Reza Amini Reza Amini@yahoo com March 14 2009 Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan 84156 83111 Iran Degree M Sc Language FarsiSupervisors F Sheikholeslam Sheikh@cc iut ac irS Hosseinnia hoseinia@cc iut ac irAbstract Models of many industrial complex systems are not completely identified yet socontroller design for these systems encounter some problems These systems have workedsatisfactorily for many years under the supervision of operators but in some cases it isnecessary to make them automated On the other hand the cost of identification anddesigning computer based controllers with common methods will be so high for them Scince fuzzy controllers can be designed without knowing the mathematical model of thesystem just based on rules extracted from experts experience this kind of controllers haslots of applications in complex systems with high non linearity and delay That how wecan convert the experts experience to the the fuzzy rules is an important issue in fuzzyidentification and controller design Rough sets theory is a new algorithm for extractingfuzzy rules directly out of observed data To reduce the computation burden this theoryextracts the minimal set of relations between the previous and current mesurments andcontrol actions Both fuzzy and rough sets are able to face problems with uncertainity andcan be good complement for each other Lately reasearchers are working on combiningthese two sets which result in fuzzy rough sets So the way we combine the rough sets withother theories to face uncertainity is a valuable field of research Additionally using thesenew sets in system identification and controller design are useful applications of this study In this thesis controller rules and rule base model of a sample system are extractedout of a huge amount of input output data using rough sets theory and its combinationwith fuzzy sets i e fuzzy rough sets Additionally it is shown that the performance of theresultant rule base controller is improved in comparison with the former controller Also itis more robust in facing disturbances In this way the application of rough sets and itscombination with fuzzy sets in identification and controller design is shown Key WordsGranular Computing Rough Sets System Identification Controller

سعيد حسين نيا، فريد شيخ الاسلام

جواد عسكري

محمدرضا احمد زاده، مريم ذكري