Search results for "Control"

showing 10 items of 13168 documents

Fuzzy control of pH using NAL

1991

Abstract A fuzzy controller for a neutralization process is described. The controller was set up for a laboratory pilot plant. The approach is shown to be effective and can be extended to highly nonlinear and nonstationary processes. The “operator” knowledge encoded in the rules was obtained by several experimental runs of the system using manual control. Rules are composed using the max-min compositional rule of inference. The use of metarules, which depends on controller performance and on active disturbances, makes the controller behave like an adaptive controller. The control program is encoded in NAL, a new experimental logic programming language that was first used in this work in a r…

Adaptive neuro fuzzy inference systemAdaptive controlAutomatic controlComputer scienceApplied Mathematicsfuzzy logicpH controlexpert systemsFuzzy control systemprocess controladaptive controlDefuzzificationFuzzy logicTheoretical Computer Sciencelogic programmingArtificial IntelligenceControl theoryFuzzy numberSoftwareInternational Journal of Approximate Reasoning
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Fuzzy modeling and control for a class of inverted pendulum system

2014

Published version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2014/936868 Open Access Focusing on the issue of nonlinear stability control system about the single-stage inverted pendulum, the T-S fuzzy model is employed. Firstly, linear approximation method would be applied into fuzzy model for the single-stage inverted pendulum. At the same time, for some nonlinear terms which could not be dealt with via linear approximation method, this paper will adopt fan range method into fuzzy model. After the T-S fuzzy model, the PDC technology is utilized to design the fuzzy controller secondly. Numerical simulation res…

Adaptive neuro fuzzy inference systemArticle SubjectMathematics::General Mathematicslcsh:MathematicsApplied MathematicsFuzzy control systemAnalysis; Applied Mathematicslcsh:QA1-939VDP::Mathematics and natural science: 400::Mathematics: 410::Analysis: 411Fuzzy logicInverted pendulumNonlinear systemControl theoryControl systemLinear approximationAnalysisMathematics
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Improved Performance of a PV Solar Panel with Adaptive Neuro Fuzzy Inference System ANFIS based MPPT

2018

This article presents the development of an intelligent technique of Adaptive-Neuro-Fuzzy Inference System (ANFIS) based on Maximum Power Point Tracking (ANFIS-MPPT) algorithm with PI controller in order to increase the performances of the photovoltaic panel system below change atmospheric circumstances. In this work, the mathematical principles of the ANFIS method were presented and developed using the software Matlab/Simulink. Moreover, the effectiveness of this ANFIS-MPPT technique is demonstrated by a comparison of the obtained results with others obtained from a classical (Perturb & Observe) P & O-MPPT method.From the analysis of the obtained results, the ANFIS-MPPT command provide bet…

Adaptive neuro fuzzy inference systemComputer sciencebusiness.industry020209 energyPhotovoltaic systemPID controller02 engineering and technologyMaximum power point trackingSoftwareControl theoryConvergence (routing)0202 electrical engineering electronic engineering information engineeringPoint (geometry)businessMATLABcomputercomputer.programming_language2018 7th International Conference on Renewable Energy Research and Applications (ICRERA)
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Data-based modeling of vehicle crash using adaptive neural-fuzzy inference system

2014

Vehicle crashes are considered to be events that are extremely complex to be analyzed from the mathematical point of view. In order to establish a mathematical model of a vehicle crash, one needs to consider various areas of research. For this reason, to simplify the analysis and improve the modeling process, in this paper, a novel adaptive neurofuzzy inference system (ANFIS-based) approach to reconstruct kinematics of colliding vehicles is presented. A typical five-layered ANFIS structure is trained to reproduce kinematics (acceleration, velocity, and displacement) of a vehicle involved in an oblique barrier collision. Subsequently, the same ANFIS structure is applied to simulate different…

Adaptive neuro fuzzy inference systemEngineeringVehicle crash reconstructionAdaptive neural-fuzzy inference system (ANFIS)-based prediction; Time-series analysis; Vehicle crash reconstruction; Vehicle dynamics modeling; Control and Systems Engineering; Computer Science Applications1707 Computer Vision and Pattern Recognition; Electrical and Electronic Engineeringbusiness.industryControl engineeringComputer Science Applications1707 Computer Vision and Pattern RecognitionKinematicsCollisionDisplacement (vector)Computer Science ApplicationsVehicle dynamicsAccelerationAdaptive neural-fuzzy inference system (ANFIS)-based predictionControl and Systems EngineeringTime-series analysisTime seriesElectrical and Electronic EngineeringbusinessReliability (statistics)Vehicle dynamics modeling
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Determining the Parameters of a Sugeno Fuzzy Controller Using a Parallel Genetic Algorithm

2013

Developed in the mid 1970s, the technique based on genetic algorithms proved its usefulness in finding optimal or near optimal solutions to problems for which accurate solving strategies are either non-existent or require excessively long running time. We implemented a genetic algorithm to determine the parameters of a Sugeno fuzzy controller for the Truck Backer-Upper problem (This problem is considered an acknowledged benchmark in nonlinear system identification.). Less known at first than Mamdami fuzzy controllers, Sugeno fuzzy controllers became popular once they were included into the ANFIS neuro-fuzzy Matlab library. By their nature, Sugeno controllers can be regarded as interpolation…

Adaptive neuro fuzzy inference systemMathematical optimizationFunction approximationControl theoryComputer scienceGenetic algorithmFuzzy setFuzzy control systemFuzzy logicInterpolation2013 19th International Conference on Control Systems and Computer Science
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Inverse kinematics of a 7 DOF manipulator using Adaptive Neuro-Fuzzy Inference Systems

2012

This paper was carried out objectively to explore and describe the inverse kinematics solutions of an anthropomorphic redundant robotic structure with seven degrees of freedom and human like workspace. Traditional inverse kinematics methods can have an unacceptably slow pace for the today's extremely redundant systems. The presented method uses the Adaptive Neuro-Fuzzy Inference Systems (ANFIS) editor and the Fuzzy Logic toolbox from MATLAB® which allow the investigation of various kinematical suitable solutions. ANFIS supports the determination of one degree of freedom, remaining therefore only six undetermined degrees. For better understanding of the simulations a CAD model that mimics th…

Adaptive neuro fuzzy inference systemNeuro-fuzzyInverse kinematicsControl theoryComputer scienceDegrees of freedom (statistics)Control engineeringCADWorkspaceFuzzy logicRobotic arm2012 12th International Conference on Control Automation Robotics & Vision (ICARCV)
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Adaptive neuro-fuzzy inference system for kinematics solutions of redundant robots

2016

This written paper presents aspects concerning the implementation of the Adaptive Neuro-Fuzzy Inference System (ANFIS) in the resolution of a redundant serial robot kinematics. The kinematics solutions are divided into two categories: direct kinematics solutions and inverse kinematics solutions. To be able to control a robot the most important solutions are the ones for the inverse kinematics since one knows the position and the final orientation of the end effector and needs to determine the relative displacement or movements into the robot couplings. To obtain the optimal solutions for the inverse kinematics of a redundant robot the mathematical equations were based onto the redundancy ci…

Adaptive neuro fuzzy inference systemRobot kinematicsEngineeringInverse kinematicsbusiness.industryKinematicsRobot end effectorlaw.inventionRobot controlComputer Science::RoboticslawKinematics equationsControl theoryRobotbusinessComputingMethodologies_COMPUTERGRAPHICS2016 6th International Conference on Computers Communications and Control (ICCCC)
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Type-2 Fuzzy Control of a Bioreactor

2009

Abstract—In this paper the control of a bioprocess using an adaptive type-2 fuzzy logic controller is proposed. The process is concerned with the aerobic alcoholic fermentation for the growth of Saccharomyces Cerevisiae a n d i s characterized by nonlinearity and parameter uncertainty. Three type-2 fuzzy controllers heve been developed and tested by simulation: a simple type-2 fuzzy logic controller with 49 rules; a type-2 fuzzyneuro- predictive controller (T2FNPC); a t y p e -2 selftuning fuzzy controller ( T2STFC). The T2FNPC combines the capability of the type-2 fuzzy logic to handle uncertainties, with the ability of predictive control to predict future plant performance making use of a…

Adaptive neuro fuzzy inference systemSettore ING-IND/26 - Teoria Dello Sviluppo Dei Processi ChimiciAdaptive controlArtificial neural networkNeuro-fuzzyComputer scienceFuzzy setFuzzy control systemEthanol fermentationFuzzy logicDefuzzificationNonlinear systemModel predictive controlControl theoryAdaptive systemAdaptive control Type-2 fuzzy control Non-linear systems UncertaintyProcess controlRobust control
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An FPGA-Based Adaptive Fuzzy Coprocessor

2005

The architecture of a general purpose fuzzy logic coprocessor and its implementation on an FPGA based System on Chip is described. Thanks to its ability to support a fast dynamic reconfiguration of all its parameters, it is suitable for implementing adaptive fuzzy logic algorithms, or for the execution of different fuzzy algorithms in a time sharing fashion. The high throughput obtained using a pipelined structure and the efficient data organization allows significant increase of the computational capabilities strongly desired in applications with hard real-time constraints.

Adaptive neuro fuzzy inference systemfuzzy inferenceCoprocessorAdaptive algorithmbusiness.industryComputer scienceMembership functionsControl reconfigurationSettore ING-INF/01 - ElettronicaFuzzy logicFuzzy logicFuzzy electronicsComputer Science::Hardware ArchitectureEmbedded systembusinessThroughput (business)Membership function
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Optimization design process of a morphing winglet

2018

Aeronautic and aerospace engineering is recently moving in the direction of developing morphing wing devices, with the aim of making adaptable the aerodynamic shapes to different operational conditions. Those devices may be classified according to two different conceptual architectures: kinematic or compliant systems. Both of them embed within their body all the active components (actuators and sensors), necessary to their operations. In the first case, the geometry variation is achieved through an augmented classical mechanism, while in the second case the form modification is due to a special arrangement of the inner structure creating a distributed elastic hinges arrangement. Whatever is…

Adaptive winglet topology optimization morphing devices load alleviation and controlWingProcess (engineering)Computer scienceTopology optimizationControl engineering02 engineering and technologyAerodynamicsKinematics021001 nanoscience & nanotechnologyAeroelasticity01 natural sciences010309 opticsMorphingRobustness (computer science)Adaptive system0103 physical sciencesSystems architectureDesign processWingtip deviceSettore ING-IND/04 - Costruzioni E Strutture Aerospaziali0210 nano-technologyEngineering design processActuatorBioinspiration, Biomimetics, and Bioreplication VIII
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