Micro-gyroscope control system based on neural network

Abstract

The invention discloses a micro-gyroscope control system based on a neural network. The micro-gyroscope control system comprises a control system which is in connection communication with a micro-gyroscope, wherein the control system comprises a nominal controller and a neural network compensator. The control scheme of a feedback controller based on a micro-gyroscope nominal model and the neural network compensator is applicable to control of the micro-gyroscope, so that the tracking effect and robustness of the micro-gyroscope control system are improved. The adaptive law of a weight value of the neural network is designed based on a Lyapunov stability theory, so that the stability of the whole control system can be guaranteed under the condition of presence of a modeling error of the neural network.

Description

Technical field: [0001] The invention relates to a control system of a micro gyroscope, in particular to a robust tracking control system of a micro gyroscope based on a neural network. Background technique: [0002] Micro gyroscopes are inertial sensors that measure angular rates. Compared with traditional gyroscopes, micro gyroscopes have unparalleled advantages in size and cost, so they have broad markets, such as navigation and guidance, consumer electronics, navigation and national defense apply. However, due to the inevitable processing errors in the manufacturing process and the influence of ambient temperature, there will be differences between the characteristics of the original and the design, resulting in parameter uncertainty in the micro gyroscope, it is difficult to establish an accurate mathematical model, and usually only The nominal value of each parameter. In addition, the external disturbance in the working environment cannot be ignored, which makes the ...

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