摘要
倾斜角度的测量精度直接决定了状态控制系统的工作效果。在单一传感器测量倾斜角度的研究基础上,探讨了传感器数据融合技术用于倾斜角度测量的方法。首先分析基于加速度计和陀螺仪测量倾斜角度的原理,并研究加速度计和陀螺仪测量结果的频率特性;然后根据加速度计和陀螺仪测量结果的频率特性选定互补滤波器作为数据融合的方法;最后选定量子粒子优化群(QPSO)算法作为互补滤波器的参数寻优方法,并对比量子粒子优化群算法和粒子群优化算法的参数寻优效果。实验结果表明,互补滤波器可以在广泛频域范围内准确测量倾斜角度值,并且量子粒子群优化算法相对于粒子群优化算法具有更好的参数寻优效果。
The measurement accuracy of tilt angle directly detemines the effect of the state control system. On the basis of studying single sensor tilt angle mensurement, this paper discusses the method using sensor data fusion technology in tilt angle measuresment. Firstly, the tilt angle measurement principle based on accelerometer and gyroscope is analyzed, and the frequency characteristics of accelerometer and gyroscope measurement results are studied. Secondly, the complementary filter is selected as the data fusion method according to the frequency characteristics of accelerometer and gyroscope measurement results. Finally, the quantum-behaved particle swarm optimization （QPSO） a/gorithm is introduced as the parameter optimization method of the complementary filter, and the parameter optimization effects of QPSO and particle swarm optimization （PSO） algorithms are conpared in this paper. The experiment results show that the complementary filter can accurately measure the tilt angle in a wide frequency range, and QPSO algorithm has better parameter optimization effect than PSO algorithm.
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2017年第7期1683-1689,共7页
Chinese Journal of Scientific Instrument
基金
国家自然科学基金(51577046)
国家自然科学基金重点项目(51637004)
国家重点研发计划"重大科学仪器设备开发"(2016YFF0102200)
合肥工业大学博士专项科研基金(JZ2016HGBZ1030)项目资助
关键词
倾斜角度
数据融合
互补滤波器
量子粒子群优化算法
tilt angle
data fusion
complementary filter
quantum-behaved particle swarm optimization （QPSO） algorithm
