首页> 外文会议>IEEE International Conference on Acoustics, Speech, and Signal Processing >APPLICATION OF KALMAN AND RLS ADAPTIVE ALGORITHMS TO NON-LINEAR LOUDSPEAKER CONTROLER PARAMETER ESTIMATION: A CASE STUDY
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APPLICATION OF KALMAN AND RLS ADAPTIVE ALGORITHMS TO NON-LINEAR LOUDSPEAKER CONTROLER PARAMETER ESTIMATION: A CASE STUDY

机译:Kalman和RLS自适应算法在非线性扬声器控制器参数估计中的应用:一种案例研究

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The loudspeaker is a nonlinear transducer that produces harmonic distortion and nonlinear controllers, requiring parameters well tuned to the loudspeaker, are used to reduce it. Unfortunately loudspeaker parameters are not well known and vary during normal operation. Based on a simplified nonlinear model of the loudspeaker, and a modification to the adaptive filters, nonlinear systems for the estimation of parameter for the mechanical part and for the electrical part of the loudspeaker where developed. The parameters estimated are directly usable by the controllers, not requiring additional conversion calculations. The Kalman and RLS adaptive algorithms where applied to this systems and simulation results show that they converge, although the electrical part estimation system was about 15 times slower than the mechanical.
机译:扬声器是一个非线性换能器,它产生谐波失真和非线性控制器,需要良好调整到扬声器的参数,用于减少它。遗憾的是,扬声器参数在正常操作期间扬声器参数并不众所周知。基于扬声器的简化非线性模型,以及对机械部件的参数估计的自适应滤波器,非线性系统的修改以及扬声器的电气部分。估计的参数可由控制器直接可用,而不需要额外的转换计算。卡尔曼和RLS自适应算法,其中应用于该系统和仿真结果表明它们会聚,但电气部件估计系统比机械慢的约15倍。

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