Search results for "Fuzzy control system"

showing 10 items of 96 documents

Nonlinear fuzzy control of a fed-batch reactor for penicillin production

2012

Abstract The process of penicillin production is characterized by nonlinearities and parameter uncertainties that make it difficult to control. In the paper the development and testing of a multivariable fuzzy control system that makes use of type-2 fuzzy sets for the control of pH and temperature are described. The performance of the type-2 fuzzy logic control system (T2FLCS) is compared by simulation with that of a type-1 fuzzy logic control system (T1FLCS) and that of a control system with traditional proportional-integral-derivative (PID) controllers proposed in the literature. The fuzzy controllers are optimized using an ANFIS algorithm. The best results are obtained with the T2FLCS pa…

Settore ING-IND/26 - Teoria Dello Sviluppo Dei Processi ChimiciAdaptive neuro fuzzy inference systemEngineeringbusiness.industryGeneral Chemical EngineeringMultivariable calculusFuzzy setnon linear systemPID controllerControl engineeringFuzzy control systemFuzzy logicComputer Science ApplicationsNonlinear systemControl theorytype-2 fuzzy logic controllerControl systemfed batch fermentoruncertaintybusinessComputers & Chemical Engineering
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Experimental Comparison of Type-1 and Type-2 Fuzzy Logic Controllers for the Control of Level and Temperature in a Vessel

2011

Abstract The objective of this experimental study is to compare the performance of type-1 and type-2 fuzzy logic controllers on a real system where the control of liquid level and temperature are considered. By the use of genetic algorithms it is possible to optimize the fuzzy sets of each fuzzy controller assuring high control performance. The experimental results show that a better control in terms of robustness can be achieved by type-2 fuzzy logic controllers.

Settore ING-IND/26 - Teoria Dello Sviluppo Dei Processi ChimiciFuzzy classificationNeuro-fuzzyComputer scienceControl engineeringFuzzy control systemFuzzy logicDefuzzificationFuzzy electronicsControl theoryFuzzy set operationsFuzzy numberType-1 fuzzy logic controller type-2 fuzzy logic controller genetic algorithms.
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A genetic algorithm for the design of a fuzzy controller for active queue management

2003

Active queue management (AQM) policies are those\ud policies of router queue management that allow for the detection of network congestion, the notification of such occurrences to the\ud hosts on the network borders, and the adoption of a suitable control\ud policy. This paper proposes the adoption of a fuzzy proportional\ud integral (FPI) controller as an active queue manager for Internet\ud routers. The analytical design of the proposed FPI controller is\ud carried out in analogy with a proportional integral (PI) controller,\ud which recently has been proposed for AQM. A genetic algorithm is\ud proposed for tuning of the FPI controller parameters with respect\ud to optimal disturbance rej…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniRouterQueue management systemComputer sciencePID controllerFuzzy control systemRandom early detectionTCP Congestion ControlActive queue managementNetwork CongestionFuzzy logicComputer Science ApplicationsHuman-Computer InteractionNetwork congestionControl and Systems EngineeringControl theoryElectrical and Electronic EngineeringTail dropActive Queue ManagementSoftwareFuzzy Controllers.Information SystemsIEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews)
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Observer-based finite-time fuzzy H∞ control for discrete-time systems with stochastic jumps and time-delays

2014

This paper is concerned with the problem of observer-based finite-time H ∞ control for a family of discrete-time Markovian jump nonlinear systems with time-delays represented by Takagi-Sugeno (T-S) model. The main contribution of this paper is to design an observer-based finite-time H ∞ controller such that the resulting closed-loop system is stochastic finite-time bounded and satisfies a prescribed H ∞ disturbance attenuation level over the given finite-time interval. Sufficient criteria on stochastic finite-time H ∞ stabilization via observer-based fuzzy state feedback are presented for the solvability of the problem, which can be tackled by a feasibility problem in terms of linear matrix…

Signal processingObserver (quantum physics)Finite-time H∞ controlTakagi-Sugeno (T-S) modelMarkovian jump systemsFuzzy control systemFuzzy logicFinite-time H∞ control; Markovian jump systems; Observer-based control; Takagi-Sugeno (T-S) model; Electrical and Electronic Engineering; Control and Systems Engineering; Software; Signal Processing; 1707Nonlinear systemobserver-based controlTakagi–Sugeno (T–S) modelDiscrete time and continuous timeControl and Systems EngineeringControl theoryBounded functionSignal ProcessingComputer Vision and Pattern RecognitionState observerElectrical and Electronic Engineeringfinite-time H∞ controlfinite-time H infinity controlObserver-based controlSoftware1707Mathematics
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Fuzzy filter design for discrete-time delayed systems with distributed probabilistic sensor faults

2013

In this paper, the problem of distributed fuzzy filter design has been solved for T-S fuzzy systems with time-varying delays and multiple probabilistic packet losses. Our attention is paid to designing the distributed fuzzy filters to guarantee the filtering error dynamic system to be mean-square asymptotically stable with an average ℋ∞ performance. Sufficient conditions for the obtained filtering error dynamic system are proposed by applying a comparison model and the scaled small gain theorem. Based on the measurements and estimates of the system states for each sensor and its neighbors, the solution of the parameters of the distributed fuzzy filters is characterized in terms of the feasi…

Small-gain theoremDiscrete time and continuous timeExponential stabilityControl theoryConvex optimizationProbabilistic logicFuzzy numberFuzzy control systemFuzzy logicMathematics2013 American Control Conference
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Applying Cathegorical Metrics on Fuzzy Systems

2007

This work analyzes the categorical metrics usage on a very specific subset of Intelligent Systems: Fuzzy Systems. Several characteristics for such systems must be carefully evaluated when metrics and indicators are defined, in order to consider the fuzzy essence as part of the evaluation result. A set of metrics and indicators are defined and applied to the classical inverted pendulum problem. The paper does not intend to provide an exhaustive analysis of the quality evaluation on soft computing problem. It just presents a way to start the study of quality measure in that area.

Soft computingGeneral Computer ScienceNeuro-fuzzyComputer scienceIntelligent decision support systemFuzzy control systemcomputer.software_genreFuzzy logicFuzzy electronicsFuzzy set operationsData miningElectrical and Electronic EngineeringCategorical variablecomputerIEEE Latin America Transactions
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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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How can we apply the models of the quality of life and the quality of life management in an economy based on knowledge?

2017

The scientific substantiations of quality have been applied to models that pertain to mathematical statistics, the probability theory, the information theory, fuzzy systems, graphic methods, time series, and algebraic and numerical methods. To these, this article aims to present a new method of applying mathematical modelling in an economy based on knowledge, by using the concept of the definite integral, the composite function, and mathematical optimisation. The research methods used in the realisation of this article are bibliographic research, creation of new models, and problem-solving. Mathematical modelling, the simulation of the quality of life, etc. are methods and techniques of bot…

Sustainable developmentEconomics and EconometricsManagement scienceComputer sciencemedia_common.quotation_subjectRealisation05 social sciencesMathematical statistics050401 social sciences methods050109 social psychologyFuzzy control systemInformation theoryField (computer science)0504 sociologyEconomyProbability theoryQuality of life; management of the quality of life; indicators; simulation; economy based on knowledge0501 psychology and cognitive sciencesQuality (business)media_commonEconomic Research-Ekonomska Istraživanja
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Fuzzy Integral Imaging Camera Calibration for Real Scale 3D Reconstructions

2014

In this paper, we present a quantitative analysis of the error in the reconstruction of a 3D scene which has been captured with Synthetic Aperture Integral Imaging system. The 3D information is obtained from 2D images for which the camera parameters are unknown. The model used for calibrating the Integral Imaging camera setup is based on fuzzy systems. These systems provide the opportunity for modeling of conditions which are inherently imprecisely defined. We demonstrate that the error in the 3D reconstruction not only depends on the number of cameras, but also to their relative positions. Our model is applied to a set of images captured experimentally from a real object. A true-color real…

Synthetic aperture radarIntegral imagingbusiness.industryComputer science3D reconstructionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONFuzzy control systemIterative reconstructionCondensed Matter PhysicsFuzzy logicElectronic Optical and Magnetic MaterialsCamera auto-calibrationComputer Science::Computer Vision and Pattern RecognitionComputer visionArtificial intelligenceElectrical and Electronic EngineeringbusinessCamera resectioningJournal of Display Technology
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Design of temperature control system using conventional PID and Intelligent Fuzzy Logic controller

2015

In this paper, we present the design of temperature control for industrial heat treating furnace by using Intelligent Fuzzy Logic and PID controllers. Temperature control is important in heating processes as it can disqualify materials in terms of their physical properties when not well performed. Obviously PID temperature controller is the most used in industries to control non-linear processes. Consequently, it has been found that the output response from Fuzzy Logic is very accurate in terms of overshoot and steady state error when compared to that of PID. Moreover, both temperature controllers are modeled and simulated using MATLAB software.

Temperature controlController; Furnace; Fuzzy Logic; PID; Temperature; Artificial Intelligence; Control and Optimization; Discrete Mathematics and CombinatoricsControl and OptimizationComputer sciencePIDTemperaturePID controllerFurnaceControl engineeringFuzzy control systemFuzzy logicControllerFuzzy LogicControl theoryArtificial IntelligenceControl systemOvershoot (signal)Process controlDiscrete Mathematics and Combinatorics
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