Search results for "Sensorless Control"

showing 10 items of 14 documents

A unified observer for robust sensorless control of DC–DC converters

2017

Abstract Due to the large variety of converters' configurations, many different sensorless controllers are available in the literature, each one suited for a particular converter. The need for different configurations, especially on the same power supply, make it clear the advantage of having a shared control algorithm. This paper presents a unified nonlinear robust current observer for buck, boost and buck–boost converters in synchronous and asynchronous configurations. The unified observer speeds up the design, tuning and the implementation, and requires a memory cheaper code, easier to certify. Simulation and experimental results are presented to validate the approach in different scenar…

0209 industrial biotechnologyEngineeringObserver (quantum physics)Control (management)Robust control02 engineering and technologySettore ING-IND/32 - Convertitori Macchine E Azionamenti ElettriciAsynchronous converters020901 industrial engineering & automationControl theory0202 electrical engineering electronic engineering information engineeringCode (cryptography)Electrical and Electronic Engineeringbusiness.industryApplied Mathematics020208 electrical & electronic engineeringSynchronous convertersControl engineeringConvertersSensorless controlComputer Science ApplicationsPower (physics)Current mode controlNonlinear systemNonlinear observerControl and Systems EngineeringAsynchronous communicationRobust controlbusinessDC–DC converters
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Neural based MRAS sensorless techniques for high performance linear induction motor drives.

2010

This paper proposes a neural based MRAS (Model reference Adaptive System) speed observer suited for linear induction motors (LIM). Starting from the dynamical equation of the LIM in the synchronous reference frame in literature, the so-called voltage and current models of the LIM in the stationary reference frame, taking into consideration the end effects, have been deduced. Then, while the inductor equations have been used as reference model of the MRAS observer, the induced part equations have been discretized and rearranged so to be represented by a linear neural network (ADALINE). On this basis, the so called TLS EXIN neuron has been used to compute on-line, in recursive form, the machi…

EngineeringArtificial neural networkObserver (quantum physics)business.industrySettore ING-INF/04 - AutomaticaControl theoryLinear induction motorAdaptive systembusinessMRASReference modelStationary Reference FrameLinear Induction Motor (LIM) Sensorless control Model Reference Adaptive Systems (MRAS) Neural Networks (NN) Field Oriented Control (FOC)Reference frame
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Speed and rotor flux estimation of induction motors via on-line adjusted extended kalman filter

2006

This paper deals with the estimation of speed and rotor flux of induction motors via Extended Kalman Filter (EKF) with on-line adjusting of the system noise covariance matrix. The predictor of EKF consists of a discrete time model obtained by means of a second order discretization of the original nonlinear model of the induction motor. In order to obtain accurate estimation of the above mentioned variables, the load torque is included in the state variables and then estimated. Three different system noise models are also illustrated and compared each other by simulations carried out in Matlab/Simulink environment. For one of these models, EKF is adjusted on-line by means of an additional PI…

EngineeringDiscretizationStatorbusiness.industryCovariance matrixCovariance matrixKalman filterSensorless controlInvariant extended Kalman filterlaw.inventionExtended Kalman filterExtended Kalman filterNoiseSettore ING-INF/04 - AutomaticalawControl theoryInduction motorbusinessEstimationInduction motor
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Velocity sensorless control of a PMSM actuator directly driven an uncertain two-mass system using RKF tuned with an evolutionary algorithm

2010

This paper proposes a solution to tune an observer keeping robust closed loop performances for the sensorless motion control of an uncertain mechanical load directly driven by a PMSM through a flexible axis. An evolutionary algorithm optimizes the observers degrees of freedom. Experiments show that performances are effectively maintained.

EngineeringMechanical loadObserver (quantum physics)business.industryControl (management)Evolutionary algorithmControl engineeringDegrees of freedom (mechanics)Motion controlEvolutionary computationSensorless control PMSM motor two-mass system robust Kalman filterSettore ING-INF/04 - AutomaticaComputer Science::Systems and ControlControl theoryActuatorbusinessProceedings of 14th International Power Electronics and Motion Control Conference EPE-PEMC 2010
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PMSM Drives Sensorless Position Control with Signal Injection and Neural Filtering

2009

Vector Field Oriented Control (FOC) is one of the best control methods for high-dynamic electrical drives. To avoid the adoption of the speed/position sensor (resolver/encoder), a sensorless technique should be used. Among the various sensorless methods in literature, those based on machine saliency detection by signal injection seem to be most useful for thier giving the possibility of closing the position control loop. This paper proposes a method for enhancing both rotating and pulsating voltage carrier injection methods by a neural adaptive band filter. Results show the goodness of the proposed solution.

EngineeringSignal processingVector controlArtificial neural networkbusiness.industryFilter (signal processing)neural networksCurrent transformerControl theoryResolverElectronic engineeringPMSMsensorless controlbusinesssignal processingEncoderPosition sensor
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Sensorless small wind turbine with a sliding-mode observer for water heating applications

2015

Water heating applications consume a considerable portion of electricity demand in most of countries. Small wind turbines are one of attractive alternatives for grid electricity based water heating systems. Wind energy can be converted to heat energy in a high efficient manner. However it is essential that wind turbine based water heating systems should be economical and reliable. Maximum power point tracking algorithm of most of available wind turbines requires information from a wind speed sensor and a rotor speed sensor which reduces the reliability of the system. In this paper, the proposed 5 kW wind turbine does not require external wind speed sensors and rotor speed sensors. The syste…

EngineeringWind powerSmall wind turbineWind turbine controlWater heating systembusiness.industrySensorless controlTurbineWind speedMaximum power point trackingIndustrial and Manufacturing EngineeringPower (physics)Power optimizerStand-alone power systemControl theorySensorless control; Sliding-mode observer; Water heating system; Wind turbine control; Electrical and Electronic Engineering; Industrial and Manufacturing EngineeringElectrical and Electronic EngineeringbusinessSliding-mode observer
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Robustness Analysis of an Extended Kalman Filter for Sensorless Control of Induction Motors

2010

This paper deals with robustness analysis of Extended Kalman Filters (EKFs) for sensorless motion control of induction motors. Analysis is carried out by means of simulation experiments considering a conventional EKF, in which system and measurement noise covariance matrices are constant, and an adaptive EKF in which the system noise covariance matrix is updated on-line using a PID-type algorithm driven by the stator current estimation errors.

Engineeringbusiness.industryStatorCovariance matrixControl engineeringKalman filterCovarianceInvariant extended Kalman filterlaw.inventionComputer Science::RoboticsExtended Kalman filterSensorless ControlSettore ING-INF/04 - AutomaticaComputer Science::Systems and ControlControl theorylawRobustness (computer science)Kalman filterInduction motorbusinessInduction motor
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Sensorless Control of Induction-Motor Drive Based on Robust Kalman Filter and Adaptive Speed Estimation

2014

This paper deals with robust estimation of rotor flux and speed for sensorless control of motion control systems with an induction motor. Instead of using sixth-order extended Kalman filters (EKFs), rotor flux is estimated by means of a fourth-order descriptor-type robust KF, which explicitly takes into account motor parameter uncertainties, whereas the speed is estimated using a recursive least squares algorithm starting from the knowledge of the rotor flux itself. It is shown that the descriptor-type structure allows for a direct translation of parameter uncertainties into variations of the coefficients appearing in the model, and this improves the degree of robustness of the estimates. E…

Recursive least squares filterRobust kalman filterEstimatorKalman filterMotion controlSettore ING-INF/04 - AutomaticaControl and Systems EngineeringRobustness (computer science)Control theoryControl systemInduction motor robust Kalman filter adaptive speed estimation sensorless controlElectrical and Electronic EngineeringInduction motorMathematicsIEEE Transactions on Industrial Electronics
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MRAS Sensorless Techniques for High Performance Linear Induction Motor Drives.

2010

This paper proposes an MRAS (Model reference Adaptive System) speed observer suited for linear induction motors (LIM). Starting from the dynamical equation of the LIM in the synchronous reference frame in literature, the so-called voltage and current models of the LIM in the stationary reference frame, taking into consideration the end effects, have been deduced. These equations have been used respectively as reference and adaptive model of an MRAS observer. As machine under test, a complete dynamic model, based on the constructive elements of the LIM and taking into consideration the end effects by the definition of a proper air-gap function, has been adopted. This model has been previousl…

Settore ING-INF/04 - AutomaticaLinear Induction Motor (LIM) Sensorless control Model Reference Adaptive Systems (MRAS) Field Oriented Control (FOC).
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Sensorless interaction robot control

2010

Settore ING-INF/04 - AutomaticaRobotics Interaction Sensorless Control
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