Abstract
Two-wheeled self-balancing vehicle system is a kind of naturally unstable underactuated system with high-rank unstable multivariable strongly coupling complicated dynamic nonlinear property. Nonlinear dynamics modeling and simulation, as a basis of two-wheeled self-balancing vehicle dynamics research, has the guiding effect for system design of the project demonstration and design phase. Dynamics model of the two-wheeled self-balancing vehicle is established by importing a TSi ProPac package to the Mathematica software (version 8.0), which analyzes the stability and calculates the Lyapunov exponents of the system. The relationship between external force and stability of the system is analyzed by the phase trajectory. Proportional–integral–derivative control is added to the system in order to improve the stability of the two-wheeled self-balancing vehicle. From the research, Lyapunov exponent can be used to research the stability of hyperchaos system. The stability of the two-wheeled self-balancing vehicle is better by inputting the proportional–integral–derivative control. The Lyapunov exponent and phase trajectory can help us analyze the stability of a system better and lay the foundation for the analysis and control of the two-wheeled self-balancing vehicle system.
Highlights
In recent years, two-wheeled self-balancing vehicle is widely used for its advantages such as energy saving, environmental protection, simple structure, flexible operation, and so on
The control effectiveness is validated through the numerical simulation, and the results demonstrate that proportional– integral–derivative (PID) controller can effectively ensure stability and provide robust self-balancing control
Two-wheeled self-balancing vehicle system mainly consists of two parts, namely, the body and the pendulum bar, and the pendulum bar is mainly used to control the motion of the vehicle.[16]
Summary
Two-wheeled self-balancing vehicle is widely used for its advantages such as energy saving, environmental protection, simple structure, flexible operation, and so on. College used the fuzzy control algorithm,[8] the two-wheeled vehicle of Adelaide University used proportional-derivative (PD) control method, and ‘‘free mover’’ in China University of Science and Technology used proportional– integral–derivative (PID) control algorithm.[9] These algorithms can ensure dynamics stability of two-wheeled self-balancing vehicles and users can flexibly operate through a simple training. The research in this area is relatively few It has become a focus of how to understand its intrinsic characteristics by the simple external structure of the two-wheeled self-balancing vehicle. A dynamics modeling method with software package ProPac TSi is used and a PID controller is designed for its simple structure and other advantages.
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