时变系统辨识的多新息方法
Multi-Innovation Identification Method for Time-Varying Systems
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摘要: 推广了估计时不变参数的单新息修正技术,提出了多新息辨识方法.该方法可以抑制坏 数据对参数估计的影响,具有较强的鲁棒性.分析表明多新息方法可以跟踪时变参数,计算 量也较遗忘因子最小二乘法和卡尔曼(Kalman)滤波算法要小.仿真结果说明多新息算法估 计系统参数是有效的.Abstract: In this paper, the single innovation modification technique of estimating time-invariant parameters is extended, and the multi-innovation identification method is presented. This method may overcome the effect of bad data on the parameter estimation. It has stronger robustness and may track time-varying parameters. Its computational burden is less than forgetting factor least squares algorithm and Kalman filter algorithm. The simulation results indicate that the multi-innovation algorithm works quite well.
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Key words:
- Parameter estimation /
- time-varying system /
- convergence /
- multi-innovation technique
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