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Two Wheel Electric Bicycle Self-balance Control Algorithm Research

Author: WangGuangLin
Tutor: LanFengChong;YeZhiGang
School: South China University of Technology
Course: Vehicle Engineering
Keywords: Two self-balancing electric vehicle PID Kalman filter Gyroscope
CLC: TP273
Type: Master's thesis
Year: 2011
Downloads: 228
Quote: 0
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Abstract


The two self-balancing electric vehicle is a new type of transport, it is different from the electric bicycle and motorcycle wheel tandem, instead of using two fixed side by side, like a two parallel robot. The system is arranged in parallel, a two about the like traditional inverted pendulum itself is a natural instability body, must be applied to the the powerful control means in order to make it stable. Its small size, simple structure, flexible movement, suitable for working in cramped and dangerous space, have a wide range of civilian and military applications prospects. The purpose of this project is to self-balance control system developed a two-wheel electric vehicles, its working principle is the the system attitude sensors (gyroscopes, accelerometers) to monitor the status and state of the body in which the pitch rate of change, through high-speed microcontroller After the appropriate data and instructions, and the drive motor to generate a forward or backward acceleration to achieve the effect of the vehicle body front-back balance. Review and summarize the domestic and international two Self-Balancing Robot Research, the choice AtmeDgal16 microcontroller, Germany von Hubble Faulhaber gear motor with encoder hollow cup 2342L012 the MMA226D accelerometer sensor and EWTS82 of gyroscopes, drive wheels, designed production the motherboard and motor driver board assembly of two self-balancing electric vehicle model; prepared by the C language chosen to self-balance control program, the burning process, verify the real vehicle control algorithm feasibility. In the course of the study, the first through the establishment of a dynamic model, the use of Lagrange equations to verify the three degrees of freedom in the system the possibility of controllability, and four K values ??obtained control algorithm, based on the presence of gyro drift and accelerometer slow dynamic response testing, a gyroscope or accelerometer used alone, for the attitude of the system can not provide efficient and reliable information to reflect the real-time status of the vehicle body. Kalman filter optimization processing on the data collected by the sensor both the dynamic error compensation gyroscope drift errors and accelerometer to give a better approximation the inclination. Based in process control, PID controller has been the most widely used an automatic controller, PID control has been the most common control algorithm in many control methods, it solves the automatic control theory to solve the most fundamental problems both system stability, speed and accuracy, adjust the PID parameters can be achieved under the premise of stable system, taking into account the system with the capacity to immunity, at the same time, introduce integral term in the PID regulator, the system increases the a zero plot points, so that became the first-order or order over the system, so the system step response of the steady-state error is zero. This article PID algorithm derived using Kalman filtering better inclination approximation obtained the duty ratio of PWM-driven motor to achieve the two self-balancing electric vehicle posture balance control, Kalman filter is used to optimize the body posture, improve the accuracy of two self-balancing electric vehicle control.

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CLC: > Industrial Technology > Automation technology,computer technology > Automation technology and equipment > Automation systems > Automatic control,automatic control system
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