摘要
以在某水下平台导轨上运行的水下小车为研究对象,针对在非理想情况下由于车轮打滑所引起的速度测量误差,提出了一种基于车身加速度和车轮速度信息的小车速度估算方法。以卡尔曼滤波为基本算法,提出了基于模糊控制思想的参数调节方法,根据测量值和估算值之间的差值,在线调节观测噪声的方差值,以改变卡尔曼滤波器的参数。经Matlab仿真表明,模糊卡尔曼滤波算法融合了速度和加速度的测量值,具有较好的抗冲击能力和跟踪能力,测量精度较高。
This work presents a method of underwater-vehicle speed estimation based on acceleration and wheel speed informa- tion. To address the problem of measurement error caused by wheel-slip, a fuzzy logic based adaption turning algorithm, which can on-line adjust the observation noise covariance by monitoring the difference between speed information and speed estimation, is presented. Simulation results demonstrate that the traceability and stability of the algorithm is improved, and accuracy of estimation of vehicle speed is thus improved.
出处
《仪表技术与传感器》
CSCD
北大核心
2012年第12期80-83,共4页
Instrument Technique and Sensor
基金
国家自然科学基金项目(51079061)
关键词
水下小车
车速估计
模糊控制
卡尔曼滤波
underwater-vehicle
speed estimation
fuzzy control
kalman filter
