Robust-adaptive neural network H-infinity control method of MEMS gyroscope

Abstract

The present invention discloses a robust-adaptive neural network H-infinity control method of a MEMS gyroscope. A controller is designed based on a Riccati equation, and includes two parts of a basic neural network controller constructed by utilizing a strong online approximating capability of the neural network and a robust control item used for overcoming influences of external disturbance and parameter uncertainty on MEMS gyroscope system output tracking errors and ensuring system closed-loop stabilization. Parameters in a adaptive adjustment neural network system based on a Lyapunov stability theory are adopted, thus to ensure stability of the system. The controller is based on the Riccati equation, such that non-linear phenomena in the system are compensated, the precise tracking aim is achieved, stability of the system and robustness to external disturbance are raised, and industrial utility values are achieved.

Description

technical field [0001] The invention relates to a control method of a micro-gyroscope system, in particular to a robust self-adaptive neural network H infinite control method of a MEMS micro-gyroscope. Background technique [0002] 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 influence of ambient temperature, t...

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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.

[0004] This shows that above-mentioned existing gyroscope obviously still has inconvenience and defect in use, and 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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