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机构地区:[1]清华大学电机工程及应用电子技术系电力系统及大型发电设备安全控制和仿真国家重点实验室,北京100084
出 处:《清华大学学报(自然科学版)》2006年第1期21-24,共4页Journal of Tsinghua University(Science and Technology)
摘 要:为了解决混频激励下含有非线性特征的电阻与电感(RL)串联电路参数的在线辨识问题,提出通过提取伏安曲线和广义磁链轨迹几何特征的参数辨识新方法。该方法采用最小二乘法定义伏安曲线和广义磁链轨迹复杂图形的倾斜度,由直线拟合直接辨识参数。从端口能量与功率的角度,讨论了算法的物理本质。实验结果表明:该算法具有辨识精度高、运算量小、便于递推等优点,适合于动态实时在线辨识,克服了基于Fourier变换的传统方法计算量大、结果依赖于信号频谱分布等问题。An online identification method was developed to measure the parameters of a series connected nonlinear resistance and inductance (RL) circuit excited by a mixing frequencies supply. The parameters are found by calculating the geometric features, namely the equivalent slopes, using the least square muhiple method on the characteristics of the voltage-current and generalized flux-current curves for the circuit. The physical meaning of the method is derived from the electric power and magnetic energy, The algorithm is especially suitable for recurrence computation and it avoids the shortcomings of conventional algorithms based on fast Fourier transforms (FFT) which require a large number of computations and dependence on the frequency spectrum in the measured signals. Measured results are given for an inductance and a transformer.
分 类 号:TM934.42[电气工程—电力电子与电力传动]
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