非线性时变随机系统状态及参数的实时联合估计

JOINT REAL TIME ESTIMATION OF STATES AND PARAMETERS FOR TIMEVARIANT NONLINEAR STOCHASTIC SYSTEMS

  • 摘要: 在文1中,我们给出了一种用于一类非线性时变随机系统的带次优渐消因子的扩展卡尔曼滤波器,可以估计出快速变化的系统状态.本文推广了文1的结果,使其可处理一般的非线性测量.同时,给出了一种状态及参数的联合估计方法.所做大量仿真研究表明,本文方法具有良好的实时性及动态跟踪性.

     

    Abstract: In this paper,Suboptimal fading extended Kalman filter for the state estimation of time variant nonliear stochastic systems is extended to deal with more general cases.An approach is presented for joint real time estimation of states and parameters for a class of general time-variant nonlinear stochastic systems.The effectiveness of the new approach is demonstrated by computer simulation.

     

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