Two-wheel self-balanced car based on Kalman filtering and PID algorithm

摘要：

Self-balanced car is a typical Incomplete control system. Self-balanced car`s body is a natural instability, so it has multivariable, nonlinear, strong coupling and other characteristics. The choice of inertial sensors has become one of the most important issues while designing a self-balanced car. But the sensor module is too expensive that is the reason of the high cost of the self-balanced car. A lower costed acceleration ADXL335 and angular velocity sensor ISZ-650 are chosen to make a sensor module much cheaper and the attitude is measured with Kalman filtering and PID algorithm.Finally a self-balanced car model is made to prove the feasibility of reducing costs.

作者: LIU Kun BAI Ming NI Yuhua

作者单位: College of Information Technology Beijing Normal University at Zhuhai Zhuhai, China

会议类型: 国际会议

会议名称: 2011 IEEE 18th International Conference on Industrial Engineering and Engineering Management(2011 IEEE 第十八届工业工程与工程管理国际会议 IEEM2011)

会议地点: 长春

会议语种:英文

页码: 281-285

在线出版日期: 2011-09-03（万方平台首次上网日期，不代表论文的发表时间）