An Adaptive Sliding Mode Control Method for Reaction Wheel Balancing Bicycle Robot

Abstract

The invention discloses an adaptive sliding mode control method for a reaction wheel balancing bicycle robot, comprising the following steps: collecting motion parameters of a self-balancing bicycle robot through a sensor measurement module; The sliding mode controller drives the reaction motor system motion according to the bicycle inclination angle parameter of real-time input and the front wheel steering angular velocity output voltage U; the output equation of the adaptive sliding mode controller is: adopt the technical scheme of the present invention, the method used It can adapt to the external environment while minimizing the impact of various disturbances in the external environment on the balance bicycle robot without losing robustness.

Description

technical field [0001] The invention relates to the field of bicycle robot balance control, in particular to an adaptive sliding mode control method for a reaction wheel balance bicycle robot. Background technique [0002] The balance bicycle robot is a self-balancing robot that uses sensors to perceive its own state, and then controls it through a control algorithm to achieve unmanned self-balancing. In recent years, unmanned navigation systems are being extensively studied. As a category of unmanned systems, bicycle robots have also been studied by many scholars and engineers. Due to its narrower structure, the bicycle robot can adapt to special environments where four-wheeled vehicles cannot work, such as narrow passages or pipes. The first step toward self-driving bicycles is autonomous balancing. [0003] There are various types of balancing bicycle robots, the most commonly studied is to use front wheel steering to keep the bicycle balanced. This approach minimizes...

AI Technical Summary

Problems solved by technology

This method is simple in design, so it is widely used, but 1) the robustness of the PID control algorithm is not ideal when disturbed, and the balance will fluctuate greatly when disturbed, or even lose balance, and it is not suitable for uncertain The adaptability of system parameters and changing system parameters is weak, and it is difficult to adapt to the bicycle robot whose parameters are not determined

As a linear control method, PID control does not control the specific system model, so it cannot control the nonlinear system with both robustness and stability.

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