有限信息约束下的离散鲁棒滤波器设计

Discrete-time Robust Filtering with Limited Information

本文研究一类有限信息约束下的离散系统鲁棒滤波问题.滤波对象的测量输出经由多个量化器量化后发送给滤波器.在所考虑的滤波问题中,通过引入均匀分布的随机变量描述量化噪声,并采用随机系统的方法实现滤波误差系统的建模,从而将滤波误差系统建模成一个具有多个随机变量的不确定性系统.基于随机系统的分析方法,通过黎卡提方程给出了H;滤波器的设计方法,使得滤波误差系统均方稳定且符合给定的性能指标.最后,通过仿真算例验证了本文所提设计方法的有效性.

The robust filtering problem is considered for a class of discrete systems with limited information.The measurements of the filtering plant are quantized by multiple quantizers and sent to the filter.The quantization errors are described by introducing uniformly distributed random variables, and the filtering error system is thus modeled as an uncertain system with multiple random variables.Based on the stochastic system approach, the H;filter is obtained by the Riccati equation such that the filtering error system is mean square stable and meets the given performance level.Finally, the effectiveness of the proposed design method is verified by a simulation example.