Optimal Parametric Estimation of Biased Sinusoidal Signals Using DREM.
IEEE Signal Process. Lett.(2024)
摘要
This brief presents a novel optimal parametric estimation method of improving the reconstructing accuracy for biased sinusoidal signals. First, a second-order generalized integrator (SOGI) is used to construct a linear regression equation, whose unknown coefficient vector is a combination with the bias and frequency of the input signal. Next, the dynamic regression extension and mixing technique is employed to estimate the unknown parameters by solving this equation. Then, the particle swarm optimization algorithm simultaneously optimizes the parameters of SOGI and adaptive control gains. Finally, a comparison of the accuracy of frequency estimation and reconstruction ability illustrates the superiority of the proposed strategy.
更多查看译文
关键词
Frequency estimation,dynamic regressor extension and mixing,adaptive control,parameter optimization
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要