Z-axis gyroscope control method based on neural network identification parameters

Abstract

The application discloses a Z-axis gyroscope control method based on neural network identification parameters. According to the method, a micro-gyroscope tracking error and a designed sliding mode surface are obtained; a spring parameter matrix is estimated by using an RBF neural network based on the tracking error and the sliding mode surface; a micro-gyroscope control law is designed according to the sliding mode surface and the estimated spring parameters; and then accurate estimation of the spring parameters is realized. Therefore, the spring parameters can be estimated by using the neuralnetwork under the circumstances that the gyro system frame has an asymmetric structure and the spring parameters are unknown or a nominal value does not accord with an actual value; and the adaptiveadjustment of the weight is completed by designing an adaptive rule of the neural network weight, so that the stability of the system is ensured, and the measurement precision of the gyroscope is improved.

Description

technical field [0001] The invention relates to the field of automatic control systems, in particular to a Z-axis gyroscope control method based on neural network identification parameters. Background technique [0002] MEMS gyroscopes are commonly used sensors for measuring angular velocity. Mainly used in navigation, mobile phones, quadcopters and other occasions. The working principle of the gyroscope is based on the inertial effect of the proof mass induced by the Coriolis force. When there is an angular velocity input, a Coriolis force perpendicular to the angular velocity direction and the initial vibration direction will be generated on the micro gyroscope, and its magnitude is proportional to the input angular velocity. By detecting the vibration displacement caused by the Coriolis force, and after a series of processing such as demodulation, amplification, and filtering, the required angular velocity signal can be obtained. [0003] In fact, there are always smal...

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Problems solved by technology

[0003] In fact, there are always small manufacturing errors in the manufacturing process of micro gyroscopes, which lead to a certain deviation between the spring parameters of the gyroscope system and their nominal values. Problems such as the misalignment of the measuring device and the offset of the mass center of gravity will produce unnecessary cross-coupling effects, forming inherent system interference in the form of mechanical and electrostatic forces, and reducing the performance of the micro gyroscope

The traditional control method uses adaptive sliding mode to estimate the system spring parameters, and the tracking effect is relatively poor

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