6533b824fe1ef96bd127ff82
RESEARCH PRODUCT
Modeling and control of uncertain nonlinear systems
Satyam PaulSina RazvarzAlexander GegovRaheleh Jafarisubject
0209 industrial biotechnologyMathematical optimizationArtificial neural networkComputer scienceComputingUncertain systemsComputational mathematics02 engineering and technologyFuzzy control systemFuzzy logicControllabilitymodellingNonlinear system020901 industrial engineering & automationuncertain systems0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingfuzzy equationsnonlinear systemsControl (linguistics)control/dk/atira/pure/subjectarea/asjc/1700/dk/atira/pure/core/subjects/computingComputer Science(all)description
A survey of the methodologies associated with the modeling and control of uncertain nonlinear systems has been given due importance in this paper. The basic criteria that highlights the work is relied on the various patterns of techniques incorporated for the solutions of fuzzy equations that corresponds to fuzzy controllability subject. The solutions which are generated by these equations are considered to be the controllers. Currently, numerical techniques have come out as superior techniques in order to solve these types of problems. The implementation of neural networks technique is contributed in the complex way of dealing the appropriate coefficients and solutions of the fuzzy systems.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2018-09-01 |