Search results for " State estimation"

showing 5 items of 5 documents

New Measurement Procedure for Load Flow Evaluation in Medium Voltage Smart Grids

2013

The aim of this paper is to present a new approach for the medium voltage (MV) distribution network load flow analysis, mainly based on power measurement at the low voltage (LV) level of MV/LV distribution substations. This allows to use measurement instruments, usually already installed in the secondary substations, thus achieving an equally reliable measurement system with a lower cost compared to measurements at the MV side. The new approach can be applied using a proper communication system to collect the nodal measurements and an iterative algorithm based on ladder iterative technique (LIT) to compute the load flow. The validity of this method is presented and discussed on the basis of…

EngineeringIterative methodbusiness.industrypower system measurementSystem of measurementSmart grid (SG) power system measurements load flow power quality analyzer (PQA) state estimation (SE) advanced metering infrastructure (AMI)substations.Communications systemautomatic meter readingpower distribution reliabilityPower (physics)Settore ING-IND/33 - Sistemi Elettrici Per L'Energiasmart power gridsSmart gridElectronic engineeringload flowiterative methodsPower-flow studybusinessLow voltageSettore ING-INF/07 - Misure Elettriche E ElettronicheVoltagepower system state estimation
researchProduct

Robust control of stochastic systems against bounded disturbances with application to flight control

2014

This paper investigates the problems of state observer design and observer-based integral sliding-mode control (SMC) for a class of Itô stochastic systems subject to simultaneous input and output disturbances. A new type of sliding-mode-based descriptor observer method is developed to approximate the system state and disturbance vectors. An integral-type SMC scheme is proposed based on the state estimation to stabilize the overall system. The main contributions of this approach are as follows: 1) The desired estimations of state and disturbance vectors can be obtained simultaneously, and 2) in the designed sliding-mode observer, the integral term of the Itô stochastic noise is eliminated …

EngineeringMathematical optimizationObserver (quantum physics)business.industryInput disturbanceintegral sliding-mode control (SMC)Computer Science Applications1707 Computer Vision and Pattern Recognitionoutput disturbanceNonlinear systemMatrix (mathematics)NoiseInput disturbance; integral sliding-mode control (SMC); output disturbance; sliding-mode observer (SMO); state estimation; Control and Systems Engineering; Computer Science Applications1707 Computer Vision and Pattern Recognition; Electrical and Electronic EngineeringReachabilityControl theoryControl and Systems EngineeringBounded functionsliding-mode observer (SMO)State observerstate estimationRobust controlElectrical and Electronic Engineeringbusiness
researchProduct

Predictive Intelligent Fuzzy Control for Cooperative Motion of Two Nonholonomic Wheeled Cars

2007

In this paper a problem of intelligent cooperative motion control of two wheeled nonholonomic cars (target and follower) is considered. Once a target car converges to a fixed state (position and orientation), a follower car coming from different position and orientation, converges to the state above, without excessive delay between the known arrival time of the target car and the arrival time of the follower. In this sense we present a new predictive fuzzy control system. A Kalman's filter and an odometric model are used to predict the future position and orientation of the target car. The prediction above is employed to plane a circular nonholonomic reference motion for the follower car. A…

Nonholonomic systemEngineeringbusiness.industryControl engineeringFuzzy control systemKalman filterMotion controlFuzzy logicModel predictive controlSettore ING-INF/04 - AutomaticaControl theoryPosition (vector)Intelligent control Fuzzy control Motion control Kinematics Velocity control Intelligent transportation systems Delay effects Vehicle dynamics State estimation Error correctionbusinessIntelligent control2007 IEEE Intelligent Transportation Systems Conference
researchProduct

Exploring Training Options for RF Sensing Using CSI

2018

This work analyzes human behavior recognition approaches using WiFi channel state information from the perhaps less usual point of view of training and calibration needs. With the help of selected literature examples, as well as with more detailed experimental insights on our own Doppler spectrum-based approach for physical motion/presence/cardinality detection, we first classify the diverse forms of training so far employed into three main categories (trained, trained-once, and training-free). We further discuss under which conditions it is possible to move toward lighter forms of calibration or even succeed in devising fully untrained model-based solutions. Our take home messages are main…

Point (typography)Settore ING-INF/03 - TelecomunicazioniComputer Networks and CommunicationsCalibration (statistics)Computer sciencebusiness.industry010401 analytical chemistryBehavioural sciences020206 networking & telecommunications02 engineering and technologyMachine learningcomputer.software_genreTraining Wireless fidelity Calibration Doppler effect Behavioral sciences Radio frequency Sensors Channel state estimation01 natural sciencesTraining (civil)Motion (physics)0104 chemical sciencesComputer Science ApplicationsPersonalization0202 electrical engineering electronic engineering information engineeringArtificial intelligenceElectrical and Electronic EngineeringbusinesscomputerIEEE Communications Magazine
researchProduct

Extended Kalman Filter for sensorless control of induction motors

2010

This paper deals with speed and rotor flux estimation of induction motors via Extended Kalman Filter (EKF). The filter is designed starting from a discrete time model obtained by means of a first order discretization of the original nonlinear model of the induction motor (IM). In order to obtain accurate estimation of the above mentioned variables, the load torque is included into the state variables and then estimated, thus constructing a sixth order EKF. Experimental results are shown with reference to a closed loop sensorless control system, consisting of a 750 W induction motor supplied by a voltage source inverter, a cascade controller consisting of four PI control loops and the design…

State variableEngineeringbusiness.industryControl engineeringKalman filterInvariant extended Kalman filterExtended Kalman filterSettore ING-INF/04 - AutomaticaComputer Science::Systems and ControlControl theoryFilter (video)Control systemFull state estimation sensorless control experimental validation.TorquebusinessInduction motor2010 First Symposium on Sensorless Control for Electrical Drives
researchProduct