Search results for "Fuzzy logic control"

showing 10 items of 14 documents

A Hybrid Architecture for Tiered Storage with Fuzzy Logic and AutoML

2020

The explosion of storage needs pauses a multifaceted challenge for organizations, not only it exerts a large pressure on precious resources, but also creates a sub-optimal data environment where the noise level may overwhelm the actual signal. However, despite the economies of scale achieved by major cloud platforms, the fundamental issue of storage optimization did not go away.

050101 languages & linguisticsComputer sciencebusiness.industryDistributed computing05 social sciencesSIGNAL (programming language)Cloud computing02 engineering and technologyFuzzy logicEconomies of scaleFuzzy logic controller0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processing0501 psychology and cognitive sciencesNoise levelArchitecturebusinessCloud storage
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Application of a fuzzy algorithm for pH control in a struvite crystallisation reactor

2006

A struvite crystallisation process is highly dependent on pH. To achieve a high phosphorus recovery as struvite it is important to have an accurate control of pH in the reactor. The high non-linear response of pH value makes manual pH control difficult. Therefore, a software based on fuzzy logic control (FLC) has been developed to maintain the pH at a set value in a stirred reactor to crystallise struvite. The FLC developed has been based on Larsen's inference. In order to confirm the improvement of the pH stability using FLC software, different experiments have been carried out with manual control of the pH value, and with the FLC software. It has been demonstrated that using FLC software …

EngineeringEnvironmental EngineeringStruvitePh controlMagnesium CompoundsFuzzy logic controlFuzzy logicPhosphatesWater Purificationlaw.inventionchemistry.chemical_compoundFuzzy LogiclawCrystallizationFertilizersProcess engineeringWater Science and Technologybusiness.industryPhosphorusHydrogen-Ion ConcentrationPh stabilitychemistryStruviteScientific methodCrystallizationbusinessAlgorithmsWater Pollutants ChemicalWater Science and Technology
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Energy saving in the aeration process by fuzzy logic control

1998

An aeration fuzzy logic based control system has been developed and tested in the main aerobic reactor of a BARDENPHO process pilot plant. This system has been compared with two ordinary aeration process controllers: one- and two-aeration-level on/off controllers. Energy savings of about 40% over the one-level on/off controller and a more stable closed-loop response have been obtained. Thus, an improvement of about 60% in average deviation can be accomplished by the use of an AFLBC.

EngineeringEnvironmental Engineeringbusiness.industryProcess (computing)Control engineeringFuzzy logic controlFuzzy logicPilot plantControl theoryControl systemAerationbusinessEnergy (signal processing)Water Science and TechnologyWater Science and Technology
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Type-2 fuzzy control of a fed-batch fermentation reactor

2010

Abstract The aim of the paper is to present the application of type-2 fuzzy logic controllers (T2FLCs) to the control of a fed-batch fermentation reactor in which the penicillin production is carried out. The performance of the control system using T2FLCs is compared by simulation with that of a control system using type-1 fuzzy logic controllers (T1FLCs). The non linear model used for the simulation study is an unstructured model characterized by the presence of non linearities, parameter uncertainty and measurement noise. Simulation results confirm the robustness of the T2FLC which shows a better performance than its type-1 counterpart particularly when uncertainties are present in the co…

EngineeringSettore ING-IND/26 - Teoria Dello Sviluppo Dei Processi ChimiciBatch fermentationbusiness.industryNon linear modelControl engineeringFuzzy control systemType (model theory)Fuzzy logicNoiseControl theoryRobustness (computer science)Control systemtype-2 fuzzy logic controller uncertainties non linear system fed batch fermentation reactorbusiness
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Control of the Biodegradation of Mixed Wastes in a Continuous Bioreactor by a Type-2 Fuzzy Logic Controller

2009

Abstract Type-2 fuzzy logic control is proposed for nonlinear processes characterized by bifurcations. A control simulation study was conducted for a bioreactor with cell recycle containing phenol and glucose as carbon and energy sources in which a pure culture of Pseudomonas putida is carried out. The model developed by Ajbar [Ajbar, A. (2001). Stability analysis of the biodegradation of mixed wastes in a continuous bioreactor with cell recycle. Water Research, 35 (5), 1201–1208] was used for the simulations. The particular dynamics of the bioreactor, characterized by two saddle-node bifurcations, makes its control difficult, since it may become unstable also for small variations of some p…

EngineeringSettore ING-IND/26 - Teoria Dello Sviluppo Dei Processi Chimicibusiness.industryGeneral Chemical EngineeringOpen-loop controllerPID controllerControl engineeringFuzzy control systemFuzzy logicComputer Science ApplicationsNonlinear systemBifurcation Bioreactor control Stability Type-2 fuzzy logic controllerControl theoryRobustness (computer science)Energy sourcebusiness
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Adaptive type-2 fuzzy control of non-linear systems

2009

The paper describes the development of two different type-2 adaptive fuzzy logic controllers and their use for the control of a non linear system that is characterized by the presence of bifurcations and parameter uncertainty. Although a type-2 fuzzy logic controller is able to handle the non linearities and the uncertainties present in a system, its robustness and effectiveness can be increased by the use of an opportune adaptive algorithm. A simulation study was conducted to compare the behavior of adaptive controllers with that of simple type-1 and type-2 fuzzy logic controllers. The system to be controlled, used for the simulation, is a continuous bioreactor for the treatment of mixed w…

Settore ING-IND/26 - Teoria Dello Sviluppo Dei Processi ChimiciAdaptive neuro fuzzy inference systemAdaptive controlAdaptive algorithmUncertaintyFuzzy control systemFuzzy logicType-2 fuzzy logic controlControl theoryNon linear systems Adaptive control.Control systemRobust controlEnergy sourceMathematics2009 IEEE International Conference on Intelligent Computing and Intelligent Systems
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Adaptive type-2 fuzzy logic control of a bioreactor

2010

Two adaptive type-2 fuzzy logic controllers with minimum number of rules are developed and compared by simulation for control of a bioreactor in which aerobic alcoholic fermentation for the growth of Saccharomyces cerevisiae takes place. The bioreactor model is characterized by nonlinearity and parameter uncertainty. The first adaptive fuzzy controller is a type-2 fuzzy-neuro-predictive controller (T2FNPC) that combines the capability of type-2 fuzzy logic to handle uncertainties, with the ability of predictive control to predict future plant performance making use of a neural network model of the nonlinear system. The second adaptive fuzzy controller is instead a self-tuning type-2 PI cont…

Settore ING-IND/26 - Teoria Dello Sviluppo Dei Processi ChimiciAdaptive neuro fuzzy inference systemEngineeringAdaptive controlNeuro-fuzzybusiness.industryApplied MathematicsGeneral Chemical EngineeringNonlinear dynamicBioreactorAdaptive controlPID controllerControl engineeringGeneral ChemistryFuzzy control systemFuzzy logicDefuzzificationIndustrial and Manufacturing EngineeringType-2 fuzzy logic controlControl theoryProcess controlbusinessStabilityProcess control; Adaptive control; Type-2 fuzzy logic control; Stability; Nonlinear dynamics; BioreactorChemical Engineering Science
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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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Control of a Non-isothermal CSTR by Type-2 Fuzzy Logic Controllers

2009

The paper describes the application of a type-2 fuzzy logic controller (FLC) to a non-isothermal continuous stirred tank reactor (CSTR) characterized by the presence of saddle node and Hopf bifurcations. Its performance is compared with a type-1 fuzzy logic controller performance. A full analysis of the uncontrolled CSTR dynamic was carried out and used for the feedback-feedforward fuzzy controllers development. Simulation results confirm the effectiveness and the robustness of the type-2 FLCs which outperform their type-1 counterparts, particularly when uncertainties are present in the system.

Settore ING-IND/26 - Teoria Dello Sviluppo Dei Processi ChimiciComputer scienceContinuous stirred-tank reactorSaddle-node bifurcationFuzzy logicIsothermal processType-2 fuzzy logic controllerFuzzy logic controllerNon-isothermal CSTRControl theoryRobustness (computer science)BifurcationNon-linear system.Bifurcation
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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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