The present invention relates to a method of determining the magnetic flux φ of an electric machine, based on measurements (MES) of currents and voltages in the phases of the electric machine, on a dynamic model (MOD) of the magnetic flux and on an adaptive Kalman filter (KAL).

There is proposed a method of estimating a navigation state with several variables of a mobile carrier according to the extended Kalman filter method, comprising the steps of:—acquisition of measurements of at least one of the variables,—extended Kalman filtering (400) producing a current estimated state and a covariance matrix delimiting in the space of the navigation state a region of errors, with the help of a previous estimated state, of an observation matrix, of a transition matrix and of the measurements acquired, the method being characterized in that it comprises a step (310, 330) of adjustment of the transition matrix and of the observation matrix before their use in the extended Kalman filtering in such a way that the adjusted matrices satisfy an observability condition which depends on at least one of the variables of the state of the carrier, the observability condition being adjusted so as to prevent the Kalman filter from reducing the dimension of the region along at least one non-observable axis of the state space, in which the observability condition to be satisfied by the adjusted transition and observation matrices is the nullity of the kernel of an observability matrix associated therewith and in which the adjustment comprises the steps of:—calculation (301) of at least one primary basis of non-observable vectors with the help of the previous estimated state—for each matrix to be adjusted, calculation (306, 308) of at least one matrix deviation associated with the matrix with the help of the primary basis of vectors, shifting (330) of each matrix to be adjusted according to the matrix deviation associated therewith so as to satisfy the observability condition.

The invention relates to a device and to a method for controlling a test stand arrangement having a specimen and having a loading machine, which is connected to the specimen by a connecting shaft. An estimated value (T.sub.E,est) for for the internal torque (T.sub.E) of the specimen is determined and, from the estimated value (T.sub.E,est), while taking into account a natural frequency (f.sub.0) and a delay, a damping signal (T.sub.Damp) is determined and fed back into the control loop.

The present invention relates to a method of determining the magnetic flux φ of an electric machine, based on measurements (MES) of currents and voltages in the phases of the electric machine, on a dynamic model (MOD) of the magnetic flux and on an adaptive Kalman filter (KAL).

The present invention is directed to energy-efficient hibernation in indoor wireless localization systems. A tag passively associates with a detection point (DP) and establishes a reveille time. The tag will awaken at the reveille time and send or receive a beacon to or from its associated DP. If the tag is receiving a beacon, it will awaken, receive, phase-lock its clock based on when the beacon was expected and when it was actually received, and return to hibernation. The DP transmits a scattershot of beacons, one for every tag in the system. If the tag is sending a beacon, it will awaken, send its beacon, and return to hibernation. The DP will receive the beacon and adjust its own clock based on the delay between when the beacon was expected and when it was actually received. The tag will broadcast its location to the DP on a set interval.

New measurement inputs for Kalman Filter or similar estimation approaches (at each sample) may include: DSRC messages from roadside transmitters (RSTs), such as: how long it takes for a DSRC signal from one or more fixed RSTs to reach the vehicle and comparison of that information with vehicle position estimates from a signal propagation model, which is based on how long it takes a DSRC signal to reach the vehicle GPS location from a fixed known RST location. From such measurements, it can be determined how much longer (or shorter) it takes to receive the RST message compared to the previous sample, which, in turn, gives an idea how far the vehicle has moved over a sample relative to a fixed RST location.

The invention relates to a device and to a method for controlling a test stand arrangement having a specimen and having a loading machine, which is connected to the specimen by a connecting shaft. An estimated value (T.sub.E,est) for for the internal torque (T.sub.E) of the specimen is determined and, from the estimated value (T.sub.E,est), while taking into account a natural frequency (f.sub.0) and a delay, a damping signal (T.sub.Damp) is determined and fed back into the control loop.

There is proposed a method of estimating a navigation state with several variables of a mobile carrier according to the extended Kalman filter method, comprising the steps of:acquisition of measurements of at least one of the variables,extended Kalman filtering (400) producing a current estimated state and a covariance matrix delimiting in the space of the navigation state a region of errors, with the help of a previous estimated state, of an observation matrix, of a transition matrix and of the measurements acquired, the method being characterized in that it comprises a step (310, 330) of adjustment of the transition matrix and of the observation matrix before their use in the extended Kalman filtering in such a way that the adjusted matrices satisfy an observability condition which depends on at least one of the variables of the state of the carrier, the observability condition being adjusted so as to prevent the Kalman filter from reducing the dimension of the region along at least one non-observable axis of the state space, in which the observability condition to be satisfied by the adjusted transition and observation matrices is the nullity of the kernel of an observability matrix associated therewith and in which the adjustment comprises the steps of:calculation (301) of at least one primary basis of non-observable vectors with the help of the previous estimated statefor each matrix to be adjusted, calculation (306, 308) of at least one matrix deviation associated with the matrix with the help of the primary basis of vectors, shifting (330) of each matrix to be adjusted according to the matrix deviation associated therewith so as to satisfy the observability condition.

New measurement inputs for Kalman Filter or similar estimation approaches (at each sample) may include: DSRC messages from roadside transmitters (RSTs), such as: how long it takes for a DSRC signal from one or more fixed RSTs to reach the vehicle and comparison of that information with vehicle position estimates from a signal propagation model, which is based on how long it takes a DSRC signal to reach the vehicle GPS location from a fixed known RST location. From such measurements, it can be determined how much longer (or shorter) it takes to receive the RST message compared to the previous sample, which, in turn, gives an idea how far the vehicle has moved over a sample relative to a fixed RST location.

An adaptive robust estimation method and system for parameters of an unmanned surface vessel belongs to the field of automatic control. First, an augmented state estimation problem considering an external disturbance for the unmanned surface vessel is constructed; augmented state vectors include a state vector of the unmanned surface vessel, a parameter vector, and an unknown input vector; and then, depending on a real-time input vector and a measurement vector of a system, a designed adaptive robust unscented Kalman filtering method is employed to obtain model parameters of the unmanned surface vessel.