Rotational inertia identification method of recursive least square method with forgetting factor

Abstract

The invention discloses a rotational inertia identification method based on a recursive least square method with a forgetting factor. The method comprises the following steps: writing an asynchronous motor motion equation into a recursive least square form, and determining an output variable, a to-be-identified parameter and an observation matrix; defining an observed quantity length, a forgetting factor, an initialization covariance matrix and an identification parameter; calculating a gain matrix at the current moment; calculating the covariance at the current moment; updating the parameter estimation value; updating the target function value; and comparing the calculated target function value with a preset target function value, continuously updating, and finally calculating to obtain rotational inertia information of the motor. The rotational inertia identification method of the recursive least square method with the forgetting factor is introduced, and the system control performance of the motor under the conditions that the load rotational inertia changes and the like is improved.

Description

technical field [0001] The invention relates to the technical field of motor moment of inertia identification, in particular to a method for identifying moment of inertia of a recursive least square method with a forgetting factor. Background technique [0002] In the modern high-performance AC motor speed control system, the vector control technology has been widely used in the high-performance control of various AC motors because of its excellent performance, simple and reliable method, etc. The key to the realization of vector control technology is decoupling. The premise of decoupling is accurate flux linkage estimation, and the accuracy of flux linkage estimation greatly depends on the motor parameters. Therefore, the identification of motor parameters occupies an important foundation in vector control technology. sexual status. In addition to being limited by the identification accuracy of the motor parameters, it is also affected by the load characteristics. Among t...

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Problems solved by technology

However, when the recursive least squares method is applied to time-varying parameter identification, it will encounter the problem of parameter saturation

Because the time-varying parameter identification is carried out online, new observation data are continuously obtained, and the old and new data have the same weight in the identification process, so as the identification proceeds, the identification result of the new data will be affected by the old data, resulting in a relatively large big deviation

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