Fractional-order adaptive inverse fuzzy sliding mode control method for microgyroscope

Abstract

The invention discloses a fractional-order adaptive inverse fuzzy sliding mode control method for a microgyroscope. The method comprises a step of establishing a dimensionless dynamic equation mathematical model and a reference trajectory model of a microgyroscope system, and a step of constructing an inversion adaption fuzzy sliding mode controller based on a fractional order. According to the method, the real-time tracing of a target by the microgyroscope can be achieved, the robustness of the system is increased, and good performance still can be maintained under the condition of external interference. A fractional order adaptive law is designed based on a fractional order sliding mode surface, a self-adaptive identification method is designed based on a Lyapunov stability criterion, various unknown system parameters of the microgyroscope is estimated in an online way in real time, compared with an integer order, adjustable items are added, and a control effect and a parameter estimation effect are improved. A fuzzy system approaches upper bound values of a parameter uncertainty and an external disturbance total number, through the fuzzy approximation of the upper bound values,switching terms in the sliding mode controller can be continuous, and buffeting can be greatly reduced.

Description

technical field [0001] The invention relates to the technical field of micro gyroscope control, in particular to a fractional-order self-adaptive inversion fuzzy sliding mode control method of a micro gyroscope. Background technique [0002] The micro-gyroscope is a sensor for measuring the angular velocity of inertial navigation and inertial guidance systems. Because it can navigate autonomously in any environment, it has received widespread attention since its appearance, and has been widely used in aerospace, navigation, aviation and military fields. Applications. However, there are errors in the production and manufacturing process and are susceptible to temperature effects, resulting in differences between the characteristics of the components and the design, resulting in a decrease in the performance of the micro gyroscope. In addition, the micro gyroscope is a multi-input multi-output system and the system parameters are uncertain and easily affected by the external ...

AI Technical Summary

Problems solved by technology

However, there are errors in the production and manufacturing process and are susceptible to temperature, resulting in differences between the characteristics of the components and the design, resulting in a decrease in the performance of the micro gyroscope

In addition, the micro gyroscope is a multi-input multi-output system and the system parameters are uncertain and easily affected by the external environment, which makes the tracking effect of the gyroscope unsatisfactory.

In the traditional sliding mode control method, the design of the sliding mode surface is a combination of error ratio, differential or integral, where the order of differential or integral is an integer, the tracking effect of the micro gyroscope is relatively poor, and the system parameters and angular velocity estimation The effect is also relatively poor, and it is easy to cause chattering

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