Search results for "Fuzzy systems"

showing 10 items of 14 documents

Novel Stability Criteria for T--S Fuzzy Systems

2014

In this paper, novel stability conditions for Takagi-Sugeno (T-S) fuzzy systems are presented. The so-called nonquadratic membership-dependent Lyapunov function is first proposed, which is formulated in a higher order form of both the system states and the normalized membership functions than existing techniques in the literature. Then, new membership-dependent stability conditions are developed by the new Lyapunov function approach. It is shown that the conservativeness of the obtained criteria can be further reduced as the degree of the Lyapunov function increases. Two numerical examples are given to demonstrate the effectiveness and less conservativeness of the obtained theoretical resul…

Lyapunov functionpolynomialsFuzzy setStability (learning theory)Lyapunov function; membership-dependent; stability; Takagi-Sugeno (T-S) fuzzy system; Control and Systems Engineering; Computational Theory and Mathematics; Artificial Intelligence; Applied Mathematicssymbols.namesakevectorsTakagi-Sugeno (T-S) fuzzy systemComputer Science::Systems and ControlArtificial IntelligenceControl theoryLyapunov equationLyapunov redesignLyapunov methodsMathematicsLyapunov functionDegree (graph theory)membership-dependentstability criteriaApplied Mathematicseducational institutionsFuzzy control systemstabilityStability conditionsComputational Theory and MathematicsControl and Systems Engineeringfuzzy systemssymbolsIEEE Transactions on Fuzzy Systems
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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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Neural Petri Control: an application on a mobile robot

2006

In the present work, an innovative nonlinear controller of nonholonomic mechanical systems, characterized by a dynamic not well known model a priori, using a new neural model obtained by the combination of a Petri net with a neural network, is proposed. The performances of the control algorithm are evaluated for tasks of tracking of time trajectories. The study of the stability of the total system to closed loop is based on the Lyapunov theory. Simulation experiments, made taking into consideration a nonholonomic mobile robot, to two wheels, allowed to verify the theoretical results.

Lyapunov functionArtificial neural networkComputer scienceStability (learning theory)Mobile robotControl engineeringPetri netsFuzzy systemsPetri netfuzzy reasoningComputer Science::Roboticssymbols.namesakeNonlinear systemControl theorysymbolsNonholonomic mobile robot
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Asymptotic comparison of the implicative fragments of certain fuzzy logics

2022

An asymptotic similarity of some fragments of two fuzzy logics is proved. We focus on two 3-valued fuzzy logics: the Gödel-Dummett one and the Łukasiewicz one and we consider their purely implicative fragments of two variables. This paper shows the existence of the densities of truth of these logics and determines their values. For this purpose we build the appropriate Tarski-Lindenbaum algebra and use extensively generating functions. Our method can be generalized to n-valued logics, n > 3, but all computations will be extremely complicated.

Fuzzy logicAlgebraFuzzy systems
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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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Design on fuzzy control for a class of stochastic nonlinear systems

2014

The problem of Hankel-norm output feedback control is solved for a class of T-S fuzzy stochastic systems. The dynamic output feedback controller design technique is proposed by employing fuzzy-basis-dependent Lyapunov function approach and the conversion on the Hankel-norm controller parameters. Sufficient conditions are established to design the controllers such that the resulting closed-loop system is stochastically stable and satisfies a prescribed performance. The desired output feedback controller can be obtained by solving a convex optimization problem, which can be efficiently solved by standard numerical algorithms Refereed/Peer-reviewed

Lyapunov functionOutput feedbackStochastic stabilityClass (computer programming)Mathematical optimizationLMIsStochastic systemsFuzzy control systemFuzzy systemssymbols.namesakeNonlinear systemControl theoryFuzzy systems; LMIs; Stochastic systems; Electrical and Electronic EngineeringConvex optimizationsymbolsElectrical and Electronic EngineeringMathematics
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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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