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Closed-loop parameter identification of second-order non-linear systems: a distributional approach using delayed reference signals

机译:二阶非线性系统的闭环参数识别:使用延迟参考信号的分布方法

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摘要

This work presents a closed-loop parameter identification algorithm for a class of second-order non-linear systems affected by constant disturbances, quantisation, and state estimation errors. The proposed scheme permits obtaining a linear parameterisation of the non-linear system by developing a simplified procedure that allows using the distributional framework approach straightforwardly. The parametrisation stage requires signals with known delays. These delays are introduced to the system through the reference signal. Then, the linear parametrisation is used by a least-squares (LS) algorithm and a state estimator to generate the estimated values of the system parameters and the constant disturbance. The proposed algorithm is compared to a standard off-line LS algorithm in numerical simulations. Besides, the effectiveness and robustness of the proposed methodology are verified using a Monte Carlo simulation by considering that the system's output is corrupted by white noise. The results indicate that the proposed parameter identification scheme outperforms the LS algorithm, but without requiring any pre-processing stage.
机译:这项工作为一类受恒定干扰,量化和状态估计误差影响的二阶非线性系统提出了一种闭环参数识别算法。所提出的方案允许通过开发允许直接使用分布框架方法的简化程序来获得非线性系统的线性参数化。参数化阶段需要具有已知延迟的信号。这些延迟通过参考信号引入系统。然后,最小二乘(LS)算法和状态估计器使用线性参数化来生成系统参数和恒定干扰的估计值。在数值模拟中,将所提出的算法与标准离线LS算法进行了比较。此外,考虑到系统的输出受到白噪声的破坏,使用蒙特卡洛模拟验证了所提出方法的有效性和鲁棒性。结果表明,所提出的参数识别方案优于LS算法,但不需要任何预处理阶段。

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