Search results for "Fuzzy control system"

showing 10 items of 96 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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Stability analysis and controller design for a class of T-S fuzzy Markov jump system with uncertain expectation of packet dropouts

2013

This paper is concerned with an H∞ control for a class of Takagi-Sugeno (T-S) fuzzy Markov jump system under unreliable communication links. It is assumed that the transition probabilities determining the dynamical behavior of the underlying system are partially unknown and the communication links between the plant and the controller are imperfect (the packet dropouts occur intermittently). In this paper, a more practical scenario is considered in the setting, i.e., the expectation of packet losses represented as a description of Bernoulli-distributed stochastic process is uncertain. Attention is focused on the design of H∞ controllers such that the closed-loop system is stochastically stab…

Lyapunov functionsymbols.namesakeMathematical optimizationControl theoryStochastic processNetwork packetsymbolsStability (learning theory)Markov processFuzzy control systemFuzzy logicMathematics2013 American Control Conference
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Trajectory Decentralized Fuzzy Control of Multiple UAVs.

2008

This paper considers a complete position and heading rate control system for multiple unmanned aerial vehicles (UAVs) with constant altitude. A decentralized trajectory planning algorithm is proposed, where the UAVs will avoid collisions while moving. In order to stabilize the UAVs in the reference planned trajectories and ensure the boundedness of the control velocities, a fuzzy control law is proposed with Lyapunov's stability proof. Simulation experiments developed in Matlab environment confirm the effectiveness and the robustness of the proposed control algorithm with respect to possible turbulence disturbances perturbing the nominal motion of the UAVs.

Lyapunov stabilityLyapunov functionAutomatic controlComputer scienceTrajectory Decentralized Fuzzy Control Multiple UAVFuzzy control systemMotion controlComputer Science::Multiagent SystemsComputer Science::Roboticssymbols.namesakeSettore ING-INF/04 - AutomaticaComputer Science::Systems and ControlControl theoryControl systemTrajectorysymbolsMotion planning
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Dynamic Output-Feedback Passivity Control for Fuzzy Systems under Variable Sampling

2013

Published version of an article in the journal: Mathematical Problems in Engineering. Also available from the publisher at: http://dx.doi.org/10.1155/2013/767093 Open Access This paper concerns the problem of dynamic output-feedback control for a class of nonlinear systems with nonuniform uncertain sampling via Takagi-Sugeno (T-S) fuzzy control approach. The sampling is not required to be periodic, and the state variables are not required to be measurable. A new type fuzzy dynamic output-feedback sampled-data controller is constructed, and a novel time-dependent Lyapunov-Krasovskii functional is chosen for fuzzy systems under variable sampling. By using Lyapunov stability theory, a sufficie…

Lyapunov stabilityState variableMathematical optimizationArticle Subjectlcsh:MathematicsGeneral MathematicsGeneral EngineeringSampling (statistics)Fuzzy control systemlcsh:QA1-939Fuzzy logicNonlinear systemlcsh:TA1-2040Control theoryConvex optimizationVDP::Matematikk og Naturvitenskap: 400::Matematikk: 410::Anvendt matematikk: 413lcsh:Engineering (General). Civil engineering (General)MathematicsMathematical Problems in Engineering
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A Self-Adapting Approach for Forecast-Less Scheduling of Electrical Energy Storage Systems in a Liberalized Energy Market

2013

In this paper, an original scheduling approach for optimal dispatch of electrical Energy Storage Systems (ESS) in modern distribution networks is proposed. The control system is based on fuzzy rules and does not use forecasts since it repairs the past history according to the real time data on the electrical energy cost, renewable energy production and load. When the system detects a worsening of performances, the fuzzy logic rule-based control system self-adapts its membership functions using an economic indicator. The common use, in the relevant literature, of forecasted values in such systems can lead to large errors and economic losses. Moreover the speed of calculation guaranteed by th…

Mathematical optimizationEngineeringControl and OptimizationEnergy Engineering and Power TechnologyFuzzy logiclcsh:TechnologyScheduling (computing)jel:Q40EEconomic indicatorjel:Qjel:Q43heuristic repairjel:Q42jel:Q41jel:Q48ESSEnergy marketjel:Q47Real-time dataschedulingElectrical and Electronic EngineeringEngineering (miscellaneous)jel:Q49scheduling; ESS; fuzzy logic; heuristic repair; rolling horizonRenewable Energy Sustainability and the Environmentbusiness.industrylcsh:Tjel:Q0Fuzzy control systemrolling horizonjel:Q4Renewable energySettore ING-IND/33 - Sistemi Elettrici Per L'EnergiaControl systemfuzzy logicbusinessEnergy (miscellaneous)Energies
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Improving Performance of Evolutionary Algorithms with Application to Fuzzy Control of Truck Backer-Upper System

2013

Published version of an article in the journal: Mathematical Problems in Engineering. Also available from the publisher at: http://dx.doi.org/10.1155/2013/709027 Open access We propose a method to improve the performance of evolutionary algorithms (EA). The proposed approach defines operators which can modify the performance of EA, including Levy distribution function as a strategy parameters adaptation, calculating mean point for finding proper region of breeding offspring, and shifting strategy parameters to change the sequence of these parameters. Thereafter, a set of benchmark cost functions is utilized to compare the results of the proposed method with some other well-known algorithms.…

Mathematical optimizationEngineeringSequenceArticle Subjectbusiness.industryGeneral Mathematicslcsh:MathematicsLévy distributionGeneral EngineeringEvolutionary algorithmfuzzy controlFuzzy control systemFunction (mathematics)lcsh:QA1-939shifting strategyVDP::Mathematics and natural science: 400::Mathematics: 410Set (abstract data type)lcsh:TA1-2040improving performanceBenchmark (computing)Point (geometry)trucksevolutionary algorithmsbusinesslcsh:Engineering (General). Civil engineering (General)Mathematical Problems in Engineering
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Controller Design Under Fuzzy Pole-Placement Specifications: An Interval Arithmetic Approach

2006

This paper discusses fuzzy specifications for robust controller design, as a way to define different specification levels for different plants in a family and allow the control of performance degradation. Controller synthesis will be understood as mapping a fuzzy plant onto a desired fuzzy set of closed-loop specifications. In this context, a fuzzy plant is considered as a possibility distribution on a given plant space. In particular, pole placement in linear plants with fuzzy parametric uncertainty is discussed, although the basic idea is general and could be applied to other settings. In the case under consideration, the controller coefficients are the solution of a fuzzy linear system o…

Mathematical optimizationFuzzy classificationNeuro-fuzzyApplied MathematicsFuzzy control systemType-2 fuzzy sets and systemsDefuzzificationFuzzy logicComputational Theory and MathematicsArtificial IntelligenceControl and Systems EngineeringControl theoryFuzzy set operationsFuzzy numberComputingMethodologies_GENERALMathematicsIEEE Transactions on Fuzzy Systems
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Solving a class of fuzzy linear programs by using semi-infinite programming techniques

2004

This paper deals with a class of Fuzzy Linear Programming problems characterized by the fact that the coefficients in the constraints are modeled as LR-fuzzy numbers with different shapes. Solving such problems is usually more complicated than finding a solution when all the fuzzy coefficients have the same shape. We propose a primal semi-infinite algorithm as a valuable tool for solving this class of Fuzzy Linear programs and, we illustrate it by means of several examples.

Mathematical optimizationLinear programmingMathematics::General MathematicsArtificial IntelligenceLogicFuzzy setFuzzy numberFuzzy set operationsFuzzy control systemDefuzzificationFuzzy logicSemi-infinite programmingMathematicsFuzzy Sets and Systems
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A Stochastic Soft Constraints Fuzzy Model for a Portfolio Selection Problem

2006

The financial market behavior is affected by several non-probabilistic factors such as vagueness and ambiguity. In this paper we develop a multistage stochastic soft constraints fuzzy program with recourse in order to capture both uncertainty and imprecision as well as to solve a portfolio management problem. The results we obtained confirm the studies carried out in literature addressed to integrate stochastic and possibilistic programming.

Mathematical optimizationLogicStochastic modellingmedia_common.quotation_subjectFuzzy setAmbiguityFuzzy control systemFuzzy logicStochastic programmingFuzzy optimization multistage stochastic programming portfolio managementArtificial IntelligencePortfolioProject portfolio managementMathematical economicsmedia_commonMathematics
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Notice of Violation of IEEE Publication Principles: Robust Observer Design for Unknown Inputs Takagi–Sugeno Models

2013

This paper deals with the observer design for Takagi-Sugeno (T-S) fuzzy models subject to unknown inputs and disturbance affecting both states and outputs of the system. Sufficient conditions to design an unknown input T-S observer are given in linear matrix inequality (LMI) terms. Both continuous-time and discrete-time cases are studied. Relaxations are introduced by using intermediate variables. Extension to the case of unmeasured decision variables is also given. A numerical example is given to illustrate the effectiveness of the given results.

Mathematical optimizationObserver (quantum physics)Applied MathematicsDecision theoryLinear matrix inequalityFuzzy control systemExtension (predicate logic)Fuzzy logicDecision variablesComputational Theory and MathematicsTakagi sugenoComputer Science::Systems and ControlArtificial IntelligenceControl and Systems EngineeringControl theoryMathematicsIEEE Transactions on Fuzzy Systems
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