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Recursive identification of time-varying non-linear cascade systems with static input and dynamic output non-linearities

机译:具有静态输入和动态输出非线性的时变非线性级联系统的递归识别

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摘要

The paper deals with the recursive identification of time-varying non-linear dynamic systems using three-block cascade models with non-linear static, linear dynamic and non-linear dynamic blocks. These models are appropriate for systems with both actuator and sensor non-linearities. Multiple application of a decomposition technique provides special expressions for the corresponding non-linear model description that are linear in parameters. A modified recursive least-squares-based algorithm is used for estimation of the time-varying input polynomial and output backlash parameters. Simulation studies show the feasibility of proposed approach to estimate the model parameters and track their changes.
机译:本文研究了时变非线性动态系统的递推辨识问题,采用了三个具有非线性静态块、线性动态块和非线性动态块的块级联模型。这些模型适用于具有执行器和传感器非线性的系统。分解技术的多次应用为相应的非线性模型描述提供了特殊的表达式,这些描述在参数上是线性的。采用改进的递推最小二乘法估计时变输入多项式和输出齿隙参数。仿真研究表明了该方法估计模型参数并跟踪其变化的可行性。

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