Search results for "Fuzzy model"

showing 10 items of 12 documents

Parallel distributed compensation for voltage controlled active magnetic bearing system using integral fuzzy model

2018

Parallel Distributed Compensation (PDC) for current-controlled Active Magnetic Bearing System (AMBS) has been quite effective in recent years. However, this method does not take into account the dynamics associated with the electromagnet. This limits the method to smaller scale applications where the electromagnet dynamics can be neglected. Voltage-controlled AMBS is used to overcome this limitation but this comes with serious challenges such as complex mathematical modelling and higher order system control. In this work, a PDC with integral part is proposed for position and input tracking control of voltage-controlled AMBS. PDC method is based on nonlinear Takagi-Sugeno (T-S) fuzzy model. …

0209 industrial biotechnologyOperating pointElectromagnetComputer scienceAMB voltage-controlledFuzzy modelComputingMagnetic bearing020206 networking & telecommunications02 engineering and technologyFuzzy logiclaw.inventionActive Magnetic BearingsNonlinear system020901 industrial engineering & automationControl theorylawTakagi-Sugeno0202 electrical engineering electronic engineering information engineeringAir gap (plumbing)/dk/atira/pure/subjectarea/asjc/1700/dk/atira/pure/core/subjects/computingVoltageParallel Distributed CompensationComputer Science(all)
researchProduct

Fuzzy Portfolio Selection Models for Dealing with Investor’s Preferences

2017

This chapter provides an overview of the authors’ previous work about dealing with investor’s preferences in the portfolio selection problem. We propose a fuzzy model for dealing with the vagueness of investor preferences on the expected return and the assumed risk, and then we consider several modifications to include additional constraints and goals.

050208 finance021103 operations researchActuarial scienceFinancial economicsComputer science05 social sciencesFuzzy model0211 other engineering and technologiesVagueness02 engineering and technologyFuzzy logicInvestor profile0502 economics and businessPortfolioExpected returnPortfolio optimizationSelection (genetic algorithm)
researchProduct

H∞ fuzzy control of DC-DC converters with input constraint

2012

Published version of an article in the journal: Mathematical Problems in Engineering. Also available from the publisher at: http://dx.doi.org/10.1155/2012/973082 Open access This paper proposes a method for designing H∞ fuzzy control of DC-DC converters under actuator saturation. Because linear control design methods do not take into account the nonlinearity of the system, a T-S fuzzy model and a controller design approach is used. The designed control not only handles the external disturbance but also the saturation of duty cycle. The input constraint is first transformed into a symmetric saturation which is represented by a polytopic model. Stabilization conditions for the H∞ state feedba…

EngineeringArticle Subjectinput constraintsstate feedback systemGeneral Mathematicssimulation examplePlantControl theoryactuator saturationspolytopic modelsexternal disturbancesbusiness.industrylcsh:MathematicsGeneral EngineeringFuzzy control systemConvertersLyapunov approachlcsh:QA1-939VDP::Mathematics and natural science: 400::Mathematics: 410Constraint (information theory)Nonlinear systemDuty cyclelcsh:TA1-2040T-S fuzzy modelscontroller designsState (computer science)businessSaturation (chemistry)lcsh:Engineering (General). Civil engineering (General)linear control design
researchProduct

Robust Predictive Control of a variable speed wind turbine using the LMI formalism

2014

This paper proposes a Robust Fuzzy Multivariable Model Predictive Controller (RFMMPC) using Linear Matrix Inequalities (LMIs) formulation. The main idea is to solve at each time instant, an LMI optimization problem that incorporates input, output and Constrained Receding Horizon Predictive Control (CRHPC) constraints, and plant uncertainties, and guarantees certain robustness properties. The RFMMPC is easily designed by solving a convex optimization problem subject to LMI conditions. Then, the derived RFMMPC applied to a variable wind turbine with blade pitch and generator torque as two control inputs. The effectiveness of the proposed design is shown by simulation results.

EngineeringMathematical optimizationOptimization problembusiness.industryBlade pitchLMIs formalism; predictive control; quadratic program; T-S fuzzy model; Control and Systems EngineeringFuzzy logicVariable speed wind turbineModel predictive controlLMIs formalismControl and Systems EngineeringComputer Science::Systems and ControlControl theoryRobustness (computer science)Convex optimizationQuadratic programmingquadratic programT-S fuzzy modelbusinesspredictive control2014 European Control Conference (ECC)
researchProduct

Optimization Under Fuzzy Max-t-Norm Relation Constraints

2019

Fuzzy relation equations and inequalities play an important role in many tools of fuzzy modelling and have been extensively studied. In many practical applications they are used as constraints in optimization. Algorithms for specific objective functions have been proposed by many authors. In this paper we introduce a method to convert a system of fuzzy relation constraints with max-t-norm composition to a linear constraint system by adding integer variables. A numerical example is provided to illustrate the proposed method.

Fuzzy modellingConstraint (information theory)Mathematical optimizationRelation (database)Mathematics::Metric GeometryT-normComposition (combinatorics)Fuzzy logicMathematicsInteger (computer science)
researchProduct

Aspects and Potentiality of Unconventional Modelling of Processes in Sporting Events

1999

This paper describes how inexact processes as presented in sporting events can be recorded, analysed, and evaluated by means of neural networks and fuzzy modelling.

Fuzzy modellingProcess modelingArtificial neural networkComputer sciencebusiness.industryComputingMethodologies_GENERALArtificial intelligencebusiness
researchProduct

Design of unknown inputs proportional integral observers for TS fuzzy models

2014

In this paper the design of unknown inputs proportional integral observers for Takagi-Sugeno (TS) fuzzy models subject to unmeasurable decision variables is proposed. These unknown inputs affect both state and output of the system. The synthesis of these observers is based on two hypotheses that the unknown inputs are under the polynomials form with their kth derivatives zero for the first one and bounded norm for the second one, hence two approaches. The Lyapunov theory and L"2-gain technique are used to develop the stability conditions of such observers in LMIs (linear matrix inequality) formulation. A simulation example is given to validate and compare the proposed design conditions for …

Lyapunov functionUnknown inputs reconstructionCognitive NeuroscienceLinear matrix inequalityComputer Science Applications1707 Computer Vision and Pattern RecognitionFuzzy logicComputer Science ApplicationsStability conditionssymbols.namesakeDecision variablesComputer Science::Systems and ControlArtificial IntelligenceControl theoryBounded functionNorm (mathematics)Unmeasurable decision variablessymbolsTS fuzzy modelsProportional integral observer; TS fuzzy models; Unknown inputs reconstruction; Unmeasurable decision variables; Artificial Intelligence; Computer Science Applications1707 Computer Vision and Pattern Recognition; Cognitive NeuroscienceProportional integral observerMathematicsNeurocomputing
researchProduct

Fuzzy modelling of HEART methodology: application in safety analyses of accidental exposure in irradiation plants

2009

The present paper refers to the obtained results by using Fuzzy Fault Tree analyses of accidental scenarios which entail the potential exposure of operators working in irradiation industrial plants. For these analyses the HEART methodology, a first generation of the Human Reliability Analysis method, has been employed to evaluate the probability of human erroneous actions. This technique has been modified by us on the basis of fuzzy set concept to more directly take into account the uncertainties of the so called error-promoting factors, on which the method is grounded. The results allow also to provide some recommendations on procedures and safety equipments to reduce the radiological expo…

Nuclear and High Energy PhysicsRisk analyses Irradiation plant Human error Fuzzy Fault Tree.RadiationBasis (linear algebra)Settore ING-IND/20 - Misure E Strumentazione NucleariComputer scienceHuman errorFuzzy setCondensed Matter PhysicsFuzzy fault treeReliability engineeringAccidental exposureFuzzy modellingSafety EquipmentGeneral Materials ScienceSettore ING-IND/19 - Impianti NucleariHuman reliabilityRadiation Effects and Defects in Solids
researchProduct

Comments on “Finite-Time $H_{\infty }$ Fuzzy Control of Nonlinear Jump Systems With Time Delays Via Dynamic Observer-Based State Feedback”

2014

This paper investigates a defect appearing in “Finite-time H∞ fuzzy control of nonlinear jump systems with time delays via dynamic observer-based state feedback,” which the observer-based finite-time H∞ controller via dynamic observer-based state feedback could not ensuring stochastic finite-time boundedness, and satisfying a prescribed level of H∞ disturbance attenuation for the resulting closed-loop error fuzzy Markov jump systems. The corrected results are presented, and the improved optimal algorithms and new simulation results are also provided in this paper.

Observer (quantum physics)Applied MathematicsFinite-time H controlMarkov processTakagi-Sugeno (T-S) fuzzy modelFuzzy control systemState (functional analysis)Fuzzy logicNonlinear systemsymbols.namesakeComputational Theory and MathematicsArtificial IntelligenceControl and Systems EngineeringControl theoryMarkov jump systems (MJS)observer-based state feedbacksymbolsJumplinear matrix inequalities (LMIs)Finite-time H control; linear matrix inequalities (LMIs); Markov jump systems (MJS); observer-based state feedback; Takagi-Sugeno (T-S) fuzzy model; Control and Systems Engineering; Artificial Intelligence; Computational Theory and Mathematics; Applied MathematicsMathematicsIEEE Transactions on Fuzzy Systems
researchProduct

Polynomial Fuzzy Models for Nonlinear Control: A Taylor Series Approach

2009

Classical Takagi-Sugeno (T-S) fuzzy models are formed by convex combinations of linear consequent local models. Such fuzzy models can be obtained from nonlinear first-principle equations by the well-known sector-nonlinearity modeling technique. This paper extends the sector-nonlinearity approach to the polynomial case. This way, generalized polynomial fuzzy models are obtained. The new class of models is polynomial, both in the membership functions and in the consequent models. Importantly, T-S models become a particular case of the proposed technique. Recent possibilities for stability analysis and controller synthesis are also discussed. A set of examples shows that polynomial modeling is…

Polynomial regressionMathematical optimizationPolynomialApplied Mathematicsfuzzy controlpolynomial fuzzy systemsFuzzy logicfuzzy modelingrelaxed stability conditionsMatrix polynomialSquare-free polynomialComputational Theory and MathematicsArtificial IntelligenceControl and Systems EngineeringHomogeneous polynomialsum of squares (SOS)Applied mathematicsFuzzy numberMathematicsWilkinson's polynomialIEEE Transactions on Fuzzy Systems
researchProduct