Abstract: The present invention is a method of controlling a wind turbine by determining the wind speed in the plane of a rotor (PR) of a wind turbine (1), by measuring the rotational speed of the rotor, the angle of the blades and the generated power. The method according to the invention implements a dynamic wind turbine model, a dynamic wind model and an unscented Kalman filter.

Abstract: The present invention is a method of determining the average wind speed in a vertical plane by use of a LiDAR sensor (2), comprising performing measurements (MES), constructing a measurement model (MOD M) and a wind model (MOD V). Then an adaptive Kalman filter (KAL) is used to determine the wind speed (v), and determining the average wind speed in the vertical plane under consideration (RAWS).

Abstract: A method for quantizing data representative of a radio signal received by a radio antenna of a mobile network. The method includes: demodulating the radio signal received by the antenna, providing a demodulated signal; scalar quantizing each value of the demodulated signal using a quantization table selected according to a channel coding level used to transmit the radio signal, providing a quantized demodulated signal; and transmitting the quantized demodulated signal to a channel decoding module.

Abstract: The invention is a method of determining wind speed components using a ground-based LiDAR sensor (1) comprising determining the wind direction (Dir) and the average wind speed (v) in a measurement plane (PM), then constructing a projection line perpendicular to wind direction (Dir) in measurement plane (PM), and subsequently determining a time shift (?t) between the measurement points (b1, b2, b3, b4) and the projection line, to determine corrected measurement signals.

Abstract: The invention is a method for determining wind speed components by using a placed LiDAR sensor (1). For this method, the wind speed components are first approximated by using the signals from the LiDAR sensor (1). These approximations are used in a wind signal model, and then used in a non-stationary Kalman filter (KAL), to construct filtered measurement signals. The filtered measurement signals are then used to reconstruct (REC) the wind speed components.

Abstract: A method and a device for matching a quantization table of data representative of a radio signal received by a radio antenna of a mobile network. The method includes: obtaining an item of information representative of a channel decoding error rate of a decoded quantized demodulated signal from a demodulation of the radio signal received by the antenna, the demodulated radio signal having been quantized by the quantization table, and the quantized demodulated radio signal having undergone a channel decoding; matching the quantization table when the channel decoding error rate is higher than a determined threshold; and transmitting an item of information representative of the matching of the quantization table to a channel decoding device or to a demodulation device.

Abstract: The present invention is a method of determining an induction factor of the wind for a wind turbine (1) equipped with a LiDAR sensor (2). For this method, wind speed measurements are performed in measurement planes (PM) by use of LiDAR sensor (2), then induction factors between measurement planes (PM) are determined by use of the measurements and of a first linear Kalman filter, and the induction factor between a measurement plane (PM) and the rotor plane (PR) of wind turbine (1) is determined by a second linear Kalman filter.

Abstract: The present invention relates to a method of determining an induction factor between the rotor plane (PR) and a measurement plane (PM), involving measuring the wind speed in at least two measurement planes (PM), determining the wind speed in rotor plane (PR) by use of a Kalman filter from the measurements, and measuring the induction factor by use of an adaptive Kalman filter from the measurements and the wind speed in rotor plane (PR).

Abstract: The invention is a method for detecting aberrant values of an incident wind field in a space located upstream of a lidar sensor. The method comprises acquiring and modelling a measurement rws(k) with the lidar sensor of an incident wind field, by estimating a median mr(k) and a mean absolute deviation dr(k) in real time of measurements of the incident wind field and detecting aberrant values in real time using the estimated median mr(k) and the mean absolute deviation dr(k).

Abstract: The invention relates to a method of determining the vertical profile of the wind speed upstream from a wind turbine (1), wherein wind speed measurements are performed by a LiDAR sensor (2), then the exponent ? of the power law is determined by an unscented Kalman filter and measurements, and the exponent ? is applied to the power law in order to determine the vertical wind speed profile.

Abstract: The present invention relates to a method of determining the direction of the wind by a LiDAR sensor (2). This method comprises performing measurements by the LiDAR sensor (2), deducing a Gaussian distribution of the longitudinal (u) and transverse (v) components of the wind speed, and determining wind direction (?) by a spherical cubature approximation method and of the Gaussian distribution of the longitudinal and transverse components of the wind speed.

Abstract: The present invention relates to a method of determining an induction factor between the rotor plane (PR) and a measurement plane (PM), involving measuring the wind speed in at least two measurement planes (PM), determining the wind speed in rotor plane (PR) by use of a Kalman filter from the measurements, and a step of measuring the induction factor by use of an adaptive Kalman filter from the measurements and the wind speed in rotor plane (PR).

Abstract: The present invention relates to a method of determining the average wind speed in a vertical plane by use of a LiDAR sensor (2), comprising performing measurements (MES), constructing a measurement model (MOD M) and a wind model (MOD V), then using an adaptive Kalman filter (KAL) to determine the wind speed (v), and determining the average wind speed in the vertical plane being considered (RAWS).

Abstract: The invention relates to a method for acquisition and modelling of an incident wind field by a LiDAR sensor. Acquisition and modelling include a step of estimating the wind amplitudes and directions for a set of discretized points, and a step of incident wind field reconstruction in three dimensions and in real time. The invention also relates to a method of controlling and/or monitoring a wind turbine equipped with such a LiDAR sensor from the incident wind field reconstructed in three dimensions and in real time.

Abstract: The present invention is a method of determining the wind speed in the plane of a rotor (PR) of a wind turbine (1), by measuring the rotational speed of the rotor, the angle of the blades and the generated power. The method according to the invention implements a dynamic wind turbine model, a dynamic wind model and an unscented Kalman filter.

Abstract: The present invention relates to a method of determining the direction of the wind by a LiDAR sensor (2). This method comprises performing measurements by the LiDAR sensor (2), deducing a Gaussian distribution of the longitudinal (u) and transverse (v) components of the wind speed, and determining wind direction (?) by a spherical cubature approximation method and of the Gaussian distribution of the longitudinal and transverse components of the wind speed.

Abstract: The present invention is a method for predicting the wind speed in the rotor plane (PR) of a wind turbine (1), by accounting for an induction factor used in a wind evolution model implemented by a Kalman filter. The invention also is a method for controlling a wind turbine (1), a computer program product, a LiDAR sensor (2) and a wind turbine (1), which uses the wind prediction determined with the method according to the invention.

Abstract: The invention relates to a method of determining the vertical profile of the wind speed upstream from a wind turbine (1), wherein wind speed measurements are performed by means of a LiDAR sensor (2), then the exponent ? of the power law is determined by means of an unscented Kalman filter and measurements, and this exponent ? is applied to the power law in order to determine the vertical wind speed profile.

Abstract: A method is proposed for processing of data packets received by an upstream node and intended for transmission to a terminal by a downstream node. The upstream node includes a queue of non-priority data packets intended for the terminal. The method includes: obtaining a first piece of information representing a filling state of the above-mentioned queue over a predetermined period of observation; when the first piece of information obtained has a value indicating a filling level of the queue that is lower than or equal to a first predetermined non-zero low threshold, reducing a rate of departure from the queue; when the first piece of obtained information has a value indicating a filling level of the queue that is higher than a first predetermined high threshold higher than or equal to the first low threshold, increasing the rate of departure from the queue.

Abstract: The present invention is a method for predicting the wind speed in the rotor plane (PR) of a wind turbine (1), by accounting for an induction factor used in a wind evolution model implemented by a Kalman filter. The invention also is a method for controlling a wind turbine (1), a computer program product, a LiDAR sensor (2) and a wind turbine (1), which uses the wind prediction determined with the method according to the invention.