Adaptive control method of rbf network for micro gyroscope based on global approximation of model

Abstract

The invention discloses a micro-gyroscope RBF (Radial Basis Function) network self-adapting control method based on model global approximation. According to the control method, based on a tracking error deign after filtering, a controller comprises a proportion differential item and an RBF neural network item. The RBF neural network item is approximated to an unknown function of a micro-gyroscope system and an updating algorithm based on a weight guarantees the global stability of the system based on a Lyapunov stability theory design. A robust item is added into the updating algorithm to guarantee the boundedness of control input; and the proportion differential item finally maintains a tracking error in any small range. The control method disclosed by the invention can realize high-precision tracking control on the micro-gyroscope system under the condition of no need of knowing about the structure or non-structure parameters of a micro-gyroscope, and in the presence of external interferences; and meanwhile, the robustness and the reliability of the system are improved.

Description

technical field [0001] The invention relates to a control method of a micro gyroscope, in particular to an adaptive control method of a micro gyroscope RBF network based on model integral approximation. Background technique [0002] Micromachined gyroscope (MEMS Gyroscope) is an inertial sensor processed by microelectronics and micromachining technology to sense angular velocity. It detects angular velocity through a vibrating micromechanical component made of silicon, so the micromechanical gyroscope is very easy to miniaturize and mass-produce, and has the characteristics of low cost and small size. In recent years, micromachined gyroscopes have been paid close attention to in many applications, for example, gyroscopes combined with micromachined acceleration sensors for inertial navigation, image stabilization in digital cameras, wireless inertial mice for computers, and so on. However, due to the inevitable processing errors in the manufacturing process and the influenc...

AI Technical Summary

Problems solved by technology

However, the robustness of adaptive control to external disturbances is very low, and it is easy to make the system unstable.

[0005] This shows that above-mentioned existing gyroscope obviously still has inconvenience and defect in use, and urgently needs to be further improved

In order to solve the problems existing in the use of existing gyroscopes, relevant manufacturers have tried their best to find a solution, but no suitable design has been developed for a long time

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