有源消声的混合自适应控制系统及试验研究
Hybrid Adaptive Control System for Active Noise Control and Experimental Investigation
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摘要: 为有效提高有源噪声控制的消声性能,针对线性控制和非线性控制方法的优缺点,基于模型参考神经网络直接自适应控制原理,提出了一种模型参考混合直接自适应控制策略,利用FLMs和非线性BP网络混合构建自适应控制系统,通过系统误差确定2种网络的加权系数,使控制器训练初期以FLMs为主提高收敛速度,后期以非线性BP网络为主提高系统控制精度.混合控制策略在保持原有非线性控制策略优点的同时,提高了系统的收敛速度.试验结果表明.该控制策略优于神经网络自适应控制.Abstract: In order to improve the performance of active noise control effectively, this paper presents a model reference hybrid direct adaptive control(MRHDAC) strategy. Based on the model reference direct adaptive control(MRDAC), this strategy makes use of advantages of FLMS algorithm and nonlinear BP networks to restructure a control system. Weights of FLMS and BP algorithm were modified according to the system error. When it begins to control nonlinear system, the system applies mainly FLMS algorithm to improving the convergent rate, then, BP to improve the control accuracy. The hybrid system keeps the advantages of the BP networks and at the same time improves convergence rate. The results of experiments have proved that the new strategy is more effective than MRDAC.