Indirect adaptive neural network sliding-mode control method for micro-gyroscope system

Abstract

The invention discloses an indirect adaptive neural network sliding-mode control method for a micro-gyroscope system. On the one hand, a neural network approximates an unknown terms in the micro-gyroscope system, and the advantage is that an accurate model of the system is not required to be known; and on the other hand, the neural network approximates an upper-bound value with external interference and parameter uncertainty in an on-line manner, switch terms in a sliding-mode controller can be serialized through on-line approximation to the upper-bound value, and buffeting can be greatly reduced. According to the sliding-mode control method, an integral term is added into the design of a sliding-mode surface to overcome a problem of a large steady-state error of the traditional sliding mode, and the robustness of the system is enhanced; and meanwhile, and the weight of the neural network is designed on the basis of a Lyapunov stability theorem, so that the overall stability of the system is ensured.

Description

technical field [0001] The invention belongs to the technical field of micro-gyroscope system control, and in particular relates to an indirect self-adaptive neural network sliding mode control method of the micro-gyroscope system. Background technique [0002] Micromachined gyroscope (MEMS Gyroscope) is an inertial sensor processed by microelectronics technology 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 th...

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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.

[0005] 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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