基于改进集员滤波的港口自动跨运车状态估计方法

针对自动跨运车状态估计问题,设计改进的集员滤波算法,在未知有界噪声环境下,获取自动跨运车实时运动状态的估计信息.首先,将自动跨运车运动学模型进行线性化处理,同时考虑其转向因素和侧倾因素,得到车辆的动力学线性模型;其次,将可能存在的内外部扰动建模为未知有界噪声,进而设计改进的集员滤波器,通过获取状态椭球域实现对自动跨运车运动参数的状态估计,同时给出改进的集员滤波算法;最后,通过仿真实验验证所提出算法的可行性和有效性.实验结果表明,所提出的改进集员滤波算法具有良好的状态估计性能.

State estimation of automated straddle carriers via improved set- membership filtering approach

This paper is concerned with the state estimation problem for an automated straddle carrier. An improved set-membership filtering scheme is proposed to solve the state estimation problem of the automated straddle carrier under unknown-but-bounded(UBB) process and measurement noises. First, the kinematic model of the automated straddle carrier is linearized to obtain the vehicle linear dynamic model. Then, an improved filtering method is designed to realize the state estimation of vehicle motion parameters by obtaining the state estimation ellipsoids. Finally, the simulations verify the feasibility and effectiveness of the proposed method. The experimental results show that the proposed algorithm has good state estimation performance.