Mems sensor array type high-precision output control method

Abstract

The invention relates to a MEMS sensor array type high-precision output control method with unknown interference effect, belonging to the field of micro-electromechanical systems. This method is an online dynamic system bias estimation algorithm driven by unknown input. It converts the measurement model of the target state into a system bias pseudo-measurement model by performing weighted linear combination of the measurement values ​​of multiple MEMS sensors. Construct a generalized dynamic system deviation model with random unknown input, which constitutes a dynamic system deviation model, and then judges whether the decoupling conditions are satisfied. If it is satisfied, the unknown disturbance is decoupled based on the dynamic system deviation model. Under the partial criterion, the gain matrix is ​​calculated, and finally the optimal linear minimum variance system deviation estimation is obtained, and the optimal estimation value of the array MEMS sensor is output. The present invention significantly improves the state estimation performance of the array MEMS sensor output with unknown environmental disturbance through the synchronous optimization processing of state estimation and disturbance identification.

Description

technical field [0001] The invention relates to a MEMS sensor array type high-precision output control method with unknown interference effect, belonging to the field of micro-electromechanical systems. Background technique [0002] MEMS technology has successfully achieved miniaturization and cost reduction of a variety of sensors. These sensors have been widely used in many fields, including artificial intelligence, Internet of Things, and Industry 4.0, etc. External extreme environmental factors, such as large temperature difference, pressure difference, strong radiation, high vacuum, microgravity, large impact, etc., widely act on MEMS sensors, resulting in sensor sensitivity and its linearity, zero deviation, repeatability, zero drift, etc. The parameters deteriorate significantly, greatly reducing the sensor accuracy. The characteristics of miniaturization and low cost of MEMS sensors promote the development of array control methods, which have received extensive att...

AI Technical Summary

Problems solved by technology

Although the above methods estimate the unknown input, they all model the unknown input parameters in the state model, or in the state model and the measurement model at the same time, and because the description of the system deviation is often regarded as a sensor quantity Therefore, some application conditions of these traditional array control methods (such as the statistical distribution of known system noise, etc.) are not sufficient, and the output accuracy of the array sensor cannot be improved well, and even a new system will be generated. error

Based on the above existing schemes and existing problems, the present invention proposes a MEMS sensor array type high-precision output control method with unknown environmental effects, and the system deviation of the sensor caused by the sudden failure of the sensor or the common interference of the external disturbance caused by the environment where the sensor is located is also reduced. There will be a sudden change, and an unknown input decoupling filter based on the system deviation pseudo-measurement model and the generalized dynamic system deviation model is designed to solve the traditional method of estimating the unknown input by modeling it in the state model and what is generally considered to be Part of the measurement model conflicts and these traditional methods cannot be directly used to deal with such problems. It can effectively achieve high-precision output of array sensors in actual engineering situations and significantly improve the anti-disturbance characteristics of sensors.

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