Search results for " Fuzzy Systems"

showing 9 items of 9 documents

Relaxed Stability and Performance LMI Conditions for Takagi-Sugeno Fuzzy Systems With Polynomial Constraints on Membership Function Shapes

2008

Most linear matrix inequality (LMI) fuzzy control results in literature are valid for any membership function, i.e., independent of the actual membership shape. Hence, they are conservative (with respect to other nonlinear control approaches) when specific knowledge of the shapes is available. This paper presents relaxed LMI conditions for fuzzy control that incorporate such shape information in the form of polynomial constraints, generalizing previous works by the authors. Interesting particular cases are overlap (product) bounds and ellipsoidal regions. Numerical examples illustrate the achieved improvements, as well as the possibilities of solving some multiobjective problems. The result…

Mathematical optimizationPolynomialApplied MathematicsPolynomial fuzzy systemsQuadratic stabilityLinear matrix inequalityFuzzy control systemNonlinear controlLinear matrix inequalityRelaxed conditionTakagi–Sugeno fuzzy controlDefuzzificationComputational Theory and MathematicsArtificial IntelligenceControl and Systems EngineeringRelaxed stabilityFuzzy numberParallel distributed compensationMembership functionMathematics
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Algorithme pour la résolution des systèmes flous

1978

Sanchez formulated conditions and theoretical methods to resolve fuzzy relations. The purpose of this study is to give an algorithm which would actual- ly enable us to determine the functions of appartenance of unknown relations.

fuzzy relations algorithm fuzzy systems[ SHS.ECO ] Humanities and Social Sciences/Economies and finances[SHS.ECO] Humanities and Social Sciences/Economics and Finance[SHS.ECO]Humanities and Social Sciences/Economics and Finance
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Stability and l1-gain analysis for positive 2D T–S fuzzy state-delayed systems in the second FM model

2014

This paper considers the problems of delay-dependent stability and l"1-gain analysis for a class of positive two-dimensional (2D) Takagi-Sugeno (T-S) fuzzy linear systems with state delays described by the second FM model. Firstly, the co-positive type Lyapunov function method is applied to establish sufficient conditions of asymptotical stability for the addressed positive 2D T-S fuzzy system. Then, the l"1-gain performance analysis for the positive 2D T-S fuzzy delayed system is studied. All the obtained results are formulated in the form of linear matrix inequalities (LMIs) which are computationally tractable. Finally, an illustrative example is given to verify the effectiveness of the p…

Positive 2D systemsLyapunov functionT-S fuzzy systemsCognitive NeuroscienceLinear systemLinear matrix inequalityDelay-dependent stabilityComputer Science Applications1707 Computer Vision and Pattern RecognitionFuzzy control systemState (functional analysis)Fuzzy logicStability (probability)Computer Science Applicationssymbols.namesakeArtificial IntelligenceControl theorysymbolsCo-positive type Lyapunov functionFuzzy numberCo-positive type Lyapunov function; Delay-dependent stability; Positive 2D systems; T-S fuzzy systems; Computer Science Applications1707 Computer Vision and Pattern Recognition; Cognitive Neuroscience; Artificial IntelligenceMathematicsNeurocomputing
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A fog-based hybrid intelligent system for energy saving in smart buildings

2019

In recent years, the widespread diffusion of pervasive sensing devices and the increasing need for reducing energy consumption have encouraged research in the energy-aware management of smart environments. Following this direction, this paper proposes a hybrid intelligent system which exploits a fog-based architecture to achieve energy efficiency in smart buildings. Our proposal combines reactive intelligence, for quick adaptation to the ever-changing environment, and deliberative intelligence, for performing complex learning and optimization. Such hybrid nature allows our system to be adaptive, by reacting in real time to relevant events occurring in the environment and, at the same time, …

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniQA75General Computer ScienceAmbient Intelligence Fuzzy Systems Fog Computing Energy Efficiencybusiness.industryComputer scienceDistributed computingComputational intelligence02 engineering and technologyEnergy consumptionHybrid intelligent systemHome automation020204 information systems0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingSmart environmentbusinessAdaptation (computer science)Efficient energy useBuilding automationJournal of Ambient Intelligence and Humanized Computing
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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
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D-stability for discrete-time t-s fuzzy descriptor systems with multiple delays

2014

In this work, the D-stability problem is considered for a class of discrete-time Takagi-Sugeno (T-S) fuzzy descriptor systems with multiple state delays. In terms of linear matrix inequality, sufficient conditions are proposed to ensure that all poles of the descriptor T-S fuzzy system are located within a disk contained in the unit circle. Moreover, a sufficient condition is presented such that the singular system is regular, causal and D-stable in spite of multiple state delays. Finally, an example is given to show the effectiveness and advantages of the proposed techniques Refereed/Peer-reviewed

Stability of linear systemsDescriptor systemsFuzzy systemsFuzzy control systemstability of linear systemsFuzzy logicDelay systems; Fuzzy systems; Stability of linear systems; Electrical and Electronic EngineeringDiscrete time and continuous timeControl theoryfuzzy systemsFuzzy numberFuzzy associative matrixElectrical and Electronic EngineeringAlgorithmdealy systemsD stabilityDelay systemsMathematics2014 American Control Conference
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On stability and stabilization of singular uncertain Takagi-Sugeno fuzzy systems

2014

This paper deals with the problem of robust stability and robust stabilization for a class of continuous-time singular Takagi-Sugeno fuzzy systems. Sufficient conditions on stability and stabilization are proposed in terms of strict LMI (Linear Matrix Inequality) for uncertain T-S fuzzy models. In order to reduce the conservatism of results developed using quadratic method, an approach based on non-quadratic Lyapunov functions and S-procedure is proposed. Illustrative examples are given to show the effectiveness of the given results Refereed/Peer-reviewed

Lyapunov functionComputer Networks and CommunicationsApplied MathematicsMathematicsofComputing_NUMERICALANALYSISStability (learning theory)Linear matrix inequalityrobust stabilityFuzzy control systemControl and Systems Engineering; Signal Processing; Computer Networks and Communications; Applied MathematicsFuzzy logicstabilizationsymbols.namesakeQuadratic equationTakagi sugenoControl and Systems EngineeringControl theoryComputer Science::Systems and ControlSignal ProcessingsymbolsTakagi-Sugeno fuzzy systemsMathematics
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Probabilistic Fuzzy Approach to Evaluation of Logistics Service Effectiveness

2014

Received: 9 September 2014 Abstract Accepted: 11 October 2014 Logistics service providers offer a whole or partial logistics business service over a certain time period. Between such companies, the effectiveness of specific logistics services can vary. Logistics service providers seek the effective performance of logistics service. The purpose of this paper is to present a new approach for the evaluation of logistics service effectiveness, along with a specific computer system implementing the proposed approach – a sophisticated inference system, an extension of the Mamdani probabilistic fuzzy system. The paper presents specific knowledge concerning the relationships between effectiveness i…

Organizational Behavior and Human Resource ManagementOperations researchComputer scienceeffectivenessInferenceParameterized complexityManagement Science and Operations ResearchFuzzy logicIndustrial and Manufacturing EngineeringManagement of Technology and Innovationlcsh:Production management. Operations managementBusiness and International Managementprobability of fuzzy eventService (business)Probabilistic logicConditional probabilityFuzzy control systemService providerReliability engineeringlogistics service providerlogistics serviceprobabilistic fuzzy systemsfuzzy expert systemslogistics companylcsh:TS155-194fuzzy hybrid systemsManagement and Production Engineering Review
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Stability analysis of type-2 fuzzy logic controllers

2009

The application of the direct Lyapunov method to the stability analysis of systems controlled by type-2 fuzzy logic controllers (FLC) is presented. The method is an extension of a method proposed for type-1 fuzzy systems. It is usually applied to systems described by state equations and controlled by fuzzy controllers using state variables as inputs but has been extended to controllers that have the error and the integral of error of the controlled variable as inputs. The proposed method allows to modify the controller rule base so that the controlled system is stable in the operating range defined by the manipulative variable constraints. The method is applied to the stability analysis of …

Settore ING-IND/26 - Teoria Dello Sviluppo Dei Processi Chimicilcsh:Computer engineering. Computer hardwareStability Type-2 fuzzy systems Lyapunov methodlcsh:TP155-156lcsh:TK7885-7895lcsh:Chemical engineering
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