Search results for "Control Engineering"

showing 10 items of 435 documents

An algebraic approach for human posture estimation in the sagittal plane using accelerometer noisy signal

2012

International audience; Our aim is to develop an algebraic approach to estimate human posture in the sagittal plane using Inertial Measurement Unit (IMU) providing accelerations and angular velocities. To do it so, we address the issue of the estimation of the amplitude, frequency and phase of a biased and noisy sum of three sinusoidal waveform signals on a moving time horizon. Since the length of the time window is small, the estimation must be done within a fraction of the signal's period. The problem is solved via algebraic techniques (see [38] for the theoretical part concerning this problem). The efficiency of our approach is illustrated by computer simulations.

0209 industrial biotechnologySignal processingComputer sciencePhase (waves)02 engineering and technologyMotion controlAccelerometerSignalSagittal plane03 medical and health sciences020901 industrial engineering & automation0302 clinical medicineAmplitudemedicine.anatomical_structureInertial measurement unitControl theory[INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering[ INFO.INFO-AU ] Computer Science [cs]/Automatic Control Engineeringmedicine030217 neurology & neurosurgery
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Crowd-Averse Robust Mean-Field Games: Approximation via State Space Extension

2016

We consider a population of dynamic agents, also referred to as players. The state of each player evolves according to a linear stochastic differential equation driven by a Brownian motion and under the influence of a control and an adversarial disturbance. Every player minimizes a cost functional which involves quadratic terms on state and control plus a cross-coupling mean-field term measuring the congestion resulting from the collective behavior, which motivates the term “crowd-averse.” Motivations for this model are analyzed and discussed in three main contexts: a stock market application, a production engineering example, and a dynamic demand management problem in power systems. For th…

0209 industrial biotechnologyStochastic stabilityMathematical optimizationCollective behaviorTechnologyComputer sciencePopulationcontrol designcrowd-averse robust mean-field games state space extension dynamic agents linear stochastic differential equation Brownian motion adversarial disturbance cost functional cross-coupling mean-field term collective behavior stock market application production engineering example dynamic demand management problem robust mean-field game approximation error stochastic stability microscopic dynamics macroscopic dynamicscontrol engineering02 engineering and technology01 natural sciencesStochastic differential equationoptimal control020901 industrial engineering & automationQuadratic equationAutomation & Control SystemsEngineeringClosed loop systemsSettore ING-INF/04 - AutomaticaApproximation errorRobustness (computer science)Control theory0102 Applied MathematicsState space0101 mathematicsElectrical and Electronic EngineeringeducationBrownian motioneducation.field_of_studyScience & TechnologyStochastic process010102 general mathematicsRelaxation (iterative method)Engineering Electrical & ElectronicOptimal controlComputer Science Applications0906 Electrical and Electronic EngineeringIndustrial Engineering & AutomationMean field theoryControl and Systems EngineeringSettore MAT/09 - Ricerca Operativa0913 Mechanical Engineering
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Algebraic parameter estimation of a multi-sinusoidal waveform signal from noisy data

2013

International audience; In this paper, we apply an algebraic method to estimate the amplitudes, phases and frequencies of a biased and noisy sum of complex exponential sinusoidal signals. Let us stress that the obtained estimates are integrals of the noisy measured signal: these integrals act as time-varying filters. Compared to usual approaches, our algebraic method provides a more robust estimation of these parameters within a fraction of the signal's period. We provide some computer simulations to demonstrate the efficiency of our method.

0209 industrial biotechnology[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingSignalsymbols.namesake020901 industrial engineering & automation[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingControl theory[INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering[ INFO.INFO-AU ] Computer Science [cs]/Automatic Control Engineering0202 electrical engineering electronic engineering information engineeringFraction (mathematics)Algebraic numberNoisy data[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingMathematicsEstimation theory020206 networking & telecommunicationsAmplitudeSinusoidal waveformEuler's formulasymbols[INFO.INFO-AU] Computer Science [cs]/Automatic Control EngineeringAlgorithm[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Algebraic parameter estimation of a biased sinusoidal waveform signal from noisy data

2012

International audience; The amplitude, frequency and phase of a biased and noisy sum of two complex exponential sinusoidal signals are estimated via new algebraic techniques providing a robust estimation within a fraction of the signal period. The methods that are popular today do not seem able to achieve such performances. The efficiency of our approach is illustrated by several computer simulations.

0209 industrial biotechnology[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingPhase (waves)02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingSignalsymbols.namesake020901 industrial engineering & automation[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering[ INFO.INFO-AU ] Computer Science [cs]/Automatic Control Engineering0202 electrical engineering electronic engineering information engineeringElectronic engineeringFraction (mathematics)Differential algebraAlgebraic numberMathematics[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingEstimation theory020206 networking & telecommunicationsAmplitudeEuler's formulasymbols[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingAlgorithm[INFO.INFO-AU] Computer Science [cs]/Automatic Control Engineering
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A Hybrid Control Strategy for Quadratic Boost Converters with Inductor Currents Estimation

2020

International audience; This paper deals with a control strategy for a DC-DC quadratic boost converter. In particular, a hybrid control scheme is proposed to encompass a control law and an observer for the estimation of the system states, based only on the measurements of the input and output voltages. Differently from classical control methods, where the controller is designed from a small-signal model, here the real model of the system is examined without considering the average values of the discrete variables. Using hybrid dynamical system theory, asymptotic stability of a neighborhood of the equilibrium point is established, ensuring practical stability of the origin, which contains es…

0209 industrial biotechnologyhybrid dynamical systemsObserver (quantum physics)Computer science02 engineering and technologyDynamical systemStability (probability)020901 industrial engineering & automationQuadratic equationExponential stabilitySettore ING-INF/04 - AutomaticaControl theoryswitching systems[INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering0202 electrical engineering electronic engineering information engineeringElectrical and Electronic Engineeringlinear matrix inequalitiesEquilibrium pointApplied Mathematics020208 electrical & electronic engineeringobserverConvertersComputer Science ApplicationsHybrid dynamical systems Linear matrix inequalities Observer Quadratic boost converter Switching systemsControl and Systems EngineeringQuadratic boost converter
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EMERGENCE: WHAT DOES IT MEAN AND HOW IS IT RELEVANT TO COMPUTER ENGINEERING?

2018

05 social sciences050109 social psychology0501 psychology and cognitive sciencesControl engineeringSociologyNon linear dynamical systems050105 experimental psychology
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Another Approach for Redundancy Resolution of a 7 DOF Robotic Arm

2015

In this paper we have presented a method to solve the inverse kinematics problem of a redundant robotic arm with seven degrees of freedom and a human like workspace based on mathematical equations, Fuzzy Logic implementation and Simulink models. For better visualization of the kinematics simulation a CAD model that mimics the real robotic arm was created into SolidWorks® and then the CAD parts were converted into SimMechanics model.

321 kinematic structureEngineeringInverse kinematicsbusiness.industryControl engineeringCADGeneral MedicineWorkspaceKinematicsFuzzy logicComputer Science::RoboticsRedundancy (engineering)businessRobotic armAstrophysics::Galaxy AstrophysicsSimulationApplied Mechanics and Materials
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The inverse kinematics solutions of a 7 DOF robotic arm using Fuzzy Logic

2012

This paper focuses on modeling resolving and simulations of the inverse kinematics of an anthropomorphic redundant robotic structure with seven degrees of freedom and a workspace similar to human arm. Also the kinematical model and the kinematics equations of the robotic arm are presented. A method of resolving the redundancy of seven degrees of freedom robotic arm is presented using Fuzzy Logic toolbox from MATLAB®.

321 kinematic structureRobot kinematicsInverse kinematicsComputer scienceControl engineeringKinematicsFuzzy control systemWorkspaceFuzzy logicComputer Science::RoboticsControl theoryKinematics equationsRobotic armAstrophysics::Galaxy Astrophysics2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA)
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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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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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