Abraham Castellanos Silva, I. Landau, Petros A. Ioannou
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引用次数: 2
摘要
在主动振动控制(AVC)和主动噪声控制(ANC)中,自适应反馈方法被广泛用于抑制未知时变频率的多窄带干扰。该方法直接或间接地基于内部模型原理和youla - ku era参数化与自适应律的结合。与该方法相关的所有算法都假设植物零点与扰动模型的极点不同,以实现扰动补偿。然而,在实践中,问题更加复杂,因为不清楚如果对象具有非常低的阻尼复零(经常在机械结构中遇到)并且干扰的频率接近反共振频率(对象零的共振频率)会发生什么。最近一项关于存在未知时变扰动的自适应调节的国际研究[16]已经将这种情况作为基准示例。已经提出了几种解决方案,最成功的解决方案是基于youla - ku时代中央控制器[5]使用具有最小参数数量的Q FIR滤波器来实现所需闭环极点的适当选择。最近在[12]中提出,Q (FIR)滤波器的过参数化可以增强线性和自适应方案在植物复零附近的鲁棒性。本文使用[16]中相同的基准示例比较了这两种方法。给出了两种方法的仿真和实时实验结果。
Direct adaptive regulation in the vicinity of low damped complex zeros — Application to active vibration control
The adaptive feedback approach is now widely used for the rejection of multiple narrow band disturbances with unknown and time varying frequencies in Active Vibration Control (AVC) and Active Noise Control (ANC). The approach is based directly or indirectly on the use of the Internal Model Principle and the Youla-Kučera parametrization combined with an adaptive law. All the algorithms associated with the approach make the assumption that the plant zeros are different from the poles of the disturbance model in order to achieve disturbance compensation. However in practice the problem is more intricate since it is not clear what happens if the plant have very low damped complex zeros (often encountered in mechanical structures) and the frequency of the disturbance is close to the anti-resonance frequency (the resonance frequency of the plant zeros). A recent international investigation on adaptive regulation in the presence of unknown time varying disturbances [16] has considered such a situation for a benchmark example. Several solutions have been proposed and the most successful has been based on the appropriate choice of the desired closed loop poles to be achieved by the Youla-Kučera central controller [5] using a Q FIR filter with the minimum number of parameters. Recently in [12] it was suggested that over parametrization of the Q (FIR) filter can enhance the robustness of the linear and adaptive scheme in the vicinity of plant complex zeros. The present paper compares these two approaches using the same benchmark example as in [16]. The results from simulations and real time experiments used to evaluate the two approaches are presented.