4results about How to "Improve State Estimation Accuracy" patented technology

This invention belongs to the field of power system technology and provides a method and system for state estimation of distribution systems that considers measurement communication reliability. First, a stochastic state estimation model for distribution systems considering measurement loss is established, introducing a series of random 0-1 variables to represent the random loss of measurements. To calculate the values ​​of each random variable, a method for calculating measurement communication reliability considering the operating state of communication equipment is proposed. A depth-first search is used to find the communication path between the measurement and the estimator, and the reliability of each path is calculated based on the current operating time of the equipment. Then, all paths are orthogonalized, and the reliability of all orthogonal paths is summed to obtain the measurement communication reliability. Finally, an extended Kalman filter algorithm for the established stochastic state estimation model is derived based on projective theory. By incorporating the communication reliability of each measurement into the estimation process, the reasonable allocation of measurement weights is achieved, improving the accuracy of state estimation.

The invention discloses a dexterous hand force-position coordination control method based on multi-sensor fusion, and relates to the technical field of robot intelligent control, and the method comprises the steps: mapping uncertainty entries in a unified interaction state estimation package into boundary contraction amounts, writing the boundary contraction amounts into a plurality of types of boundaries, executing look-ahead feasibility cutting, and generating a contraction constraint control configuration package; combining a contraction constraint control configuration packet with a unified interaction state estimation packet, constructing a plugging force displacement curve monitoring record, registering an energy suppression mark, executing slow amplitude limiting and compensation recalculation at the same time, and generating a force-position coordination instruction packet; and driving the dexterous hand according to the force-position coordination instruction packet, collecting a multi-modal driving receipt, and binding by combining the channel weight descending mark and the registered energy suppression mark to generate a force-position coordination execution result set. According to the method, credible weighted fusion of the multi-source sensing data is realized, and the state estimation precision is improved.

The application discloses a traffic state estimator design method and device for a multi-agent system, comprising: dividing a highway network into a plurality of cells according to preset positions, taking traffic flow density as a traffic state variable, establishing a traffic flow model of the highway network, and determining an output matrix of a traffic sensor; according to observability or detectability of the highway network system composed of a highway network system matrix and an output matrix of each type of traffic sensor, at least one state observer and at least one Kalman filter are constructed; all vehicle density estimation values obtained based on the state observer and the Kalman filter are respectively subjected to weighted summation fusion calculation to obtain first and second total vehicle density estimation values; and the first and second total vehicle density estimation values are subjected to weighted summation fusion calculation to obtain a final vehicle density estimation value. The application improves the state estimation precision of mixed traffic flow and improves the utilization efficiency of different types of sensors.

This invention relates to the field of airborne geophysical exploration, and more particularly to an intelligent monitoring and predictive guidance method for helicopter-towed pods. This method involves arranging multiple GPS arrays on the flexible structure of the pod, fusing airborne GPS, radar altimeter, attitude sensor, video, and meteorological data to construct a pod oscillation model incorporating structural modes and identifying deformation parameters online. A multi-model adaptive fusion framework is established, employing extended Kalman filtering and a Bayesian weight update mechanism to achieve state estimation. The spatial wind field gradient is inverted and injected into the forced pendulum dynamics equation to predict the trajectory, calculating the ground contact risk index to trigger graded alarms. Pilot cognitive load is assessed based on eye-tracking and joystick spectral analysis, dynamically simplifying the guidance interface. Lateral / longitudinal oscillation patterns are identified in the body coordinate system, generating differentiated control commands. This invention achieves intelligent monitoring and predictive guidance of the pod's state, improving flight safety and data quality.