Search results for "Fuzzy control system"

showing 10 items of 96 documents

Measure-free conditioning and extensions of additive measures on finite MV-algebras

2010

Using the well known representation of any finite MV-algebra as a product of finite MV-chains as factors, we obtain a representation of its canonical extension as a Girard algebra product of the canonical extensions of the MV-chain factors. Based on this representation and using the results from our last paper, we characterize the additive measures on any finite MV-algebra resp. the weakly and the strongly additive measures on its canonical Girard algebra extension, and that as convex combinations of the corresponding measures on the respective factors. After that we apply the results to measure-free defined conditional events which for this reason are considered as elements of the canonica…

Discrete mathematicsArtificial IntelligenceLogicLattice (order)Additive functionFuzzy setRegular polygonInformation processingConditional probabilityProbability distributionFuzzy control systemMathematicsFuzzy Sets and Systems
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Speed control design for a vehicle system using fuzzy logic and PID controller

2015

This paper consists of designing fuzzy and PID controllers for controlling the vehicle speed. The dynamic of the system is modeled to provide a transfer function for the plant. Fuzzy and PID controller are designed for linear model. The external disturbances such road grade is considered to stabilizing the system. Both controllers are modeled using MATLAB Simulink software. Finally, a comparative assessment of each simulated result is done based on the response characteristics.

Electronic speed controlControl and Optimizationbusiness.industryComputer sciencePID controllerFuzzy control systemFuzzy logicTransfer functionSoftwarecruise controlArtificial IntelligenceControl theoryControl systemcontroller; cruise control; fuzzy logic; PID control; Artificial Intelligence; Control and Optimization; Discrete Mathematics and CombinatoricsPID controlDiscrete Mathematics and Combinatoricsfuzzy logiccontrollerbusinessCruise control2015 International Conference on Fuzzy Theory and Its Applications (iFUZZY)
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Expert control of DO in the aerobic reactor of an activated sludge process

2001

Abstract An expert control structure is proposed for the control of dissolved oxygen (DO) in a Nitrification Denitrification Biological Excess Phosphorus Removal (NDBEPR) plant to account for the several processes that are influenced by the DO concentration in the aerator. In the scheme a supervisory fuzzy controller determines the set point of an inner DO control loop where an Adaptive Robust Generic Model Control (ARGMC) controller is used. The fuzzy supervisory control has a hierarchical structure. Off-line measurements of biological parameters of influent and effluent streams can be used to periodically update the set points of the fuzzy controllers. The complete control scheme has been…

EngineeringActivated sludgeSupervisory controlControl theorybusiness.industryGeneral Chemical EngineeringControl systemProcess (computing)Fuzzy control systemAerationbusinessFuzzy logicComputer Science ApplicationsComputers & Chemical Engineering
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A Laboratory Project for Advanced Control Methods: Control of a Neutralization Process

2003

Abstract A neutralization process is used in a laboratory project for experimenting advanced control techniques. Students may choose among several techniques to experience the behaviour of advanced controller action: adaptive control, GMG control, fuzzy control, self tuning fuzzy control, neural control, neuro-fuzzy control. The experience in advanced self tuning controller based on fuzzy logic is proposed for the control of a neutralization process. The test of a self tuning controller based on fuzzy logic is a very important case because the resulting structure of the controller is easy to implement and modify: the final results are compared with those deriving from the application of a c…

EngineeringAdaptive controlAutomatic controlControl theorybusiness.industrySelf-tuningProcess controlPID controllerControl engineeringFuzzy control systembusinessFuzzy logicIFAC Proceedings Volumes
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Adaptive control of hybrid vehicle depending on driving cycle analysis

2013

The most adapted energy management in hybrid electric vehicles depends on the current driving situation. This paper describes a novel control strategy based on driving cycle recognition. A Driving Cycle Recognition Algorithm (DCRA) is firstly presented. It allows recognition between three driving modes: urban, suburban and highway. A real-time control strategy is then defined based on fuzzy logic using DCRA. Results are presented and compared to fuzzy logic controllers parametrized for urban or highway cycles.

EngineeringAdaptive controlbusiness.industryEnergy managementControl (management)Control engineeringFuzzy control systemRecognition algorithmbusinessHybrid vehicleFuzzy logicDriving cycleIECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society
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The control of indoor thermal comfort conditions: introducing a fuzzy adaptive controller

2004

The control and the monitoring of indoor thermal conditions represents a pre-eminent task with the aim of ensuring suitable working and living spaces to people. Especially in industrialised countries, in fact, several rules and standards have been recently released in order of providing technicians with suitable design tools and effective indexes and parameters for the checking of the indoor microclimate. Among them, predicted mean vote (PMV) index is often adopted for assessing the thermal comfort conditions of thermal moderate environments. Unfortunately, the PMV index is characterised by non-linear features, that could determine some difficulties when monitoring and controlling HVAC equi…

EngineeringAdaptive controlbusiness.industryMechanical EngineeringControl (management)Thermal comfortPID controllerControl engineeringBuilding and ConstructionFuzzy control systemFuzzy logicControl theoryPMVFuzzy controllerHVACPID controllerElectrical and Electronic EngineeringbusinessAdaptive controllerCivil and Structural Engineering
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Control Design for Discrete-Time Fuzzy Systems with Disturbance Inputs via Delta Operator Approach

2013

Published version of an article in the journal: Mathematical Problems in Engineering. Also available from the publisher: http://dx.doi.org/10.1155/2013/724918 Open Access This paper is concerned with the problem of passive control design for discrete-time Takagi-Sugeno (T-S) fuzzy systems with time delay and disturbance input via delta operator approach. The discrete-time passive performance index is established in this paper for the control design problem. By constructing a new type ofLyapunov-Krasovskii function (LKF) in delta domain, and utilizing some fuzzy weighing matrices, a new passive performance condition is proposed for the system under consideration. Based on the condition, a st…

EngineeringArticle Subjectbusiness.industrylcsh:MathematicsGeneral MathematicsGeneral EngineeringControl engineeringFuzzy control systemFunction (mathematics)Delta operatorType (model theory)lcsh:QA1-939Fuzzy logicDomain (software engineering)Discrete time and continuous timelcsh:TA1-2040Control theoryVDP::Matematikk og Naturvitenskap: 400::Matematikk: 410::Anvendt matematikk: 413lcsh:Engineering (General). Civil engineering (General)businessMathematical Problems in Engineering
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H∞ fuzzy control of DC-DC converters with input constraint

2012

Published version of an article in the journal: Mathematical Problems in Engineering. Also available from the publisher at: http://dx.doi.org/10.1155/2012/973082 Open access This paper proposes a method for designing H∞ fuzzy control of DC-DC converters under actuator saturation. Because linear control design methods do not take into account the nonlinearity of the system, a T-S fuzzy model and a controller design approach is used. The designed control not only handles the external disturbance but also the saturation of duty cycle. The input constraint is first transformed into a symmetric saturation which is represented by a polytopic model. Stabilization conditions for the H∞ state feedba…

EngineeringArticle Subjectinput constraintsstate feedback systemGeneral Mathematicssimulation examplePlantControl theoryactuator saturationspolytopic modelsexternal disturbancesbusiness.industrylcsh:MathematicsGeneral EngineeringFuzzy control systemConvertersLyapunov approachlcsh:QA1-939VDP::Mathematics and natural science: 400::Mathematics: 410Constraint (information theory)Nonlinear systemDuty cyclelcsh:TA1-2040T-S fuzzy modelscontroller designsState (computer science)businessSaturation (chemistry)lcsh:Engineering (General). Civil engineering (General)linear control design
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Time reduction for completion of a civil engineering construction using fuzzy clustering techniques

2017

In the civil engineering field, there are usually unexpected troubles that can cause delays during execution. This situation involves numerous variables (resource number, execution time, costs, working area availability, etc.), mutually dependent, that complicate the definition of the problem analytical model and the related resolution. Consequently, the decision-maker may avoid rational methods to define the activities that could be conveniently modified, relying only on his personal experience or experts’ advices. In order to improve this kind of decision from an objective point of view, the authors analysed the operation correction using a data mining technique, called Fuzzy Clustering. …

EngineeringFuzzy clusteringbusiness.industryMechanical EngineeringControl (management)Aerospace Engineering020101 civil engineeringproject management construction road scheduling decision making02 engineering and technologyFuzzy control systemCivil engineeringField (computer science)0201 civil engineeringScheduling (computing)Reduction (complexity)Resource (project management)Modeling and SimulationAutomotive EngineeringSettore ICAR/04 - Strade Ferrovie Ed AeroportiProject managementbusiness
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A Fuzzy Discrete Event Simulator for Fuzzy Production Environment Analysis

1998

Abstract Discrete Event Simulation is a powerful tool to help production managers in planning manufacturing systems. The necessity to rapid react to market conditions is pushing production planners to process requirements and information affected by vagueness. Vagueness is related with event definition, therefore it is not manageable through statistical tools, but more properly by using fuzzy mathematics. Production situations where uncertainty takes body in term of vagueness are referred as Fuzzy Production Environments. Classical Discrete Event simulators are not suitable to deal with fuzzy variables, therefore they cannot be used to model Fuzzy Production Environments. This paper aims to…

EngineeringNeuro-fuzzyEvent (computing)business.industryMechanical EngineeringVaguenessFuzzy control systemFuzzy logicIndustrial and Manufacturing EngineeringFuzzy mathematicsFuzzy set operationsDiscrete event simulationbusinessSimulationCIRP Annals
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