控制器的设计是直接基于称为伪偏导数的向量，伪偏导数是通过新型参数估计算法，根据给出的永磁直流直线电机非线性系统模型的输入输出信息在线导出的。
The design of controller is based directly on pseudo- partial-derivatives (PPD) derived on-line from the input and output information of the system using a novel parameter estimation algorithm.
本文提出一种基于神经网络的多维自回归模型(AR, NLAR)参数估计方法。
A method of parameter estimation for multi-dimension autoregressive models (ar, NLAR) via neural network is given in this paper.
为了克服随机噪声对河流水质模型参数估计的干扰，提出了一种水质模型参数的鲁棒估计方法，即基于M -估计的信赖域算法。
In order to overcome the disturbance of noises, a robust identification method of water quality model parameters namely trust region algorithm based on M-estimation is proposed.
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