Method for tracking and controlling locus of unmanned bicycle

Abstract

The invention belongs to the technical field of movement controlling of unmanned vehicles, and especially relates to a method for tracking and controlling a locus of an unmanned bicycle. The method comprises the steps of: firstly, establishing a balance dynamic model of the bicycle, and establishing discrete state equations of a bicycle self-balance control system into which a self-balance controller is added; secondly, establishing a discrete kinetic model of the bicycle, and carrying out linearization; then combining the kinetic model with the self-balance control system, carrying out corresponding simplification processing, and establishing a seven-dimension state predicting model of the bicycle; and finally, using the seven-dimension state predicting model as a prediction model of a bicycle locus tracking algorithm, carrying out locus tracking and controlling on the bicycle, and solving optimal control input of each sampling moment on line. The bicycle locus tracking and controlling method based on the seven-dimension state predicting model is capable of accurately predicting the state of the bicycle in the future time, the calculation amount is small, and a good control effect is ensured by the on-line real-time performance.

Description

technical field [0001] The invention belongs to the technical field of motion control of unmanned bicycles, and in particular relates to a method for track tracking control of unmanned bicycles. Background technique [0002] Compared with cars, unmanned bicycles have the advantages of low price, light and portable, flexible mobility, environmental protection and energy saving. However, compared to the four-wheel structure of a car, the two-wheel structure of a bicycle is unstable, and the bicycle cannot maintain balance without human control. Therefore, for a bicycle, in order to realize the function of unmanned driving, it must first be able to control its own balance. It can be seen that the realization of unmanned bicycles is much more difficult than that of unmanned cars. [0003] On the basis of realizing the self-balancing control of the bicycle, it is necessary to carry out motion control on it, cooperate with the functions of upper-level machine vision and trajecto...

AI Technical Summary

Problems solved by technology

However, for a bicycle, the balance dynamic model of the bicycle will cause a more complicated dynamic process when the handlebar of the bicycle turns to the target corner, which will have a greater impact on the trajectory of the bicycle.

Therefore, in the problem of bicycle trajectory tracking, it is unreasonable to use only the kinematics model for prediction, so it is impossible to achieve the best tracking effect

[0005] For bicycles, only using the kinematics model as the predictive model of the model predictive control algorithm to perform trajectory tracking control cannot achieve the best results

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