5results about How to "Realize online estimation" patented technology

The invention discloses a self-adaptive event triggering cooperative tracking control method for an unmanned cluster system under resource limitation. The method comprises the following steps: establishing a dynamic model of a leader and a follower for a heterogeneous unmanned cluster system; constructing a distributed observer for the follower; determining a state measurement error and an internal dynamic variable of the follower, determining a dynamic event triggering condition of the follower, and constructing a self-adaptive event triggering controller of the follower; when the state measurement error meets or does not meet the dynamic event triggering condition, the adaptive event triggering controller adopts different means to obtain the system observation state of the neighbor node and updates the adaptive event triggering controller; and the follower realizes cooperative tracking control on the leader based on a system observation state. According to the method, the communication burden is effectively reduced, and an efficient and reliable solution is provided for cooperative control of the heterogeneous unmanned cluster system in a complex environment.

The application discloses a kind of vehicle-mounted integrated navigation system wheel speed meter error online estimation and compensation method, this method under the premise of not changing original integrated navigation algorithm architecture, wheel speed meter double-loop update mode is designed, wheel speed meter error is estimated online using low-dimensional filter in error estimation loop, compensate wheel speed meter output in filter loop in combination with error estimation result, improve the precision of integrated navigation of inertial navigation system / wheel speed meter.The method realizes wheel speed meter error online estimation based on wheel speed meter double-loop update mode and dimensionality reduction filter, does not affect the original integrated navigation algorithm architecture, small amount of calculation, high estimation accuracy, after error estimation and compensation, the integrated navigation positioning performance under the condition that GNSS signal is blocked can be improved, and higher engineering application value is shown.

The application discloses a high-rotation body angular rate online estimation method based on an improved sparrow search algorithm under a non-gyroscope condition. According to the working principle and output characteristics of a magnetic resistance sensor, the indirect and direct relationship between the magnetic resistance sensor and the high-rotation body angular rate is explored, a multi-objective fitness function with the angular rate as an optimization object is designed, and thus the construction of an angular rate online estimation model is completed. According to the advantages and disadvantages of the SSA, in order to make the sparrow search directional and fast, an adaptive dynamic step strategy and a dynamic compression search strategy are proposed to improve the traditional SSA, so as to improve the optimization ability and the ability to jump out of a local extreme value of the algorithm. The ISSA is used to optimize and solve the angular rate online estimation model, so as to realize the online estimation of the high-rotation body angular rate under the non-gyroscope condition.

This application discloses an inertial integral positioning and downhole constraint correction method and system based on a miniature downhole sensor. The method includes: acquiring triaxial angular velocity and triaxial acceleration data from the miniature downhole sensor; recursively obtaining predicted position, predicted velocity, and predicted attitude based on quaternion attitude calculation and inertial integral algorithm; constructing a wellbore spatial constraint model based on known wellbore trajectory and wellbore diameter parameters, and constructing a fluid property constraint model based on downhole fluid property parameters; generating the two types of constraint correction quantities independently and without coupling; employing an error state Kalman filter framework to filter and update the two types of correction quantities as observation information, and injecting the error state into the nominal state to output a three-dimensional motion trajectory estimate. This method continuously corrects inertial positioning drift by introducing wellbore and fluid constraint information, achieving usable positioning results for the sensor even without external positioning signals.

The application discloses a radio frequency chip test error compensation method and relates to the technical fields of electric parameter measurement and radio frequency measurement. The radio frequency chip test error compensation method is characterized in that a temperature collecting device is arranged at the proximal end of a test fixture, and the temperature is taken as an exogenous input. An extended Kalman filter is used, in which an equivalent contact network is taken as a state variable, and S parameters / impedance according to frequency points are taken as observation variables, so that the online estimation of contact characteristics is realized. Then, the transmission parameters and other cascade network parameters are taken as a working domain to complete inverse cascade de-embedding, so that the measurement results can be corrected in real time when the temperature changes and the contact is slightly disturbed. Unlike offline compensation depending on a fixed model, the application introduces residual error driven covariance self-adaptation and mutation triggered enhanced updating, so that the filtering weight can be dynamically adjusted according to the temperature change rate and the drift accumulation, and the timeliness and adaptability are significantly improved.