基于输入估计方法的振动主动控制试验研究

针对一种基于随机游走和输入估计策略的振动主动控制方法进行了试验研究。该方法涉及的动力学模型既依赖于受控系统的基本物理参数，又与未知的外扰激励密切相关。首先采用模态识别方法离线辨识系统的物理参数，以获得系统状态方程，再利用随机游走模型将未知外扰视为辅助状态量来构造新的状态方程，并借助Kalman滤波原理对新状态方程中的未知状态进行估计，进而得到未知状态和外扰的估计值。根据系统已知的测量输出、未知状态及外扰的估计值构造目标函数，应用LQG方法求解控制器增益，得到考虑未知外扰的最优控制输入。以柔性悬臂梁模型作为受控对象，对其实施振动主动控制，试验结果表明，该控制方法能有效抑制模型的前四阶模态振动，特别是对低阶模态的控制，其效果远优于经典LQG控制方法。

Experimental study of an active vibration control method based on input estimation

The aim of this study is to investigate a method of active vibration control based on input estimation by experimental method. The control method depends on parameters and external disturbance of the controlled system. In order to establish a dynamic equation of the system with parameters unknown, an algorithm of model identification is introduced to identify the parameters firstly. And then, system disturbance is described as discrete recursive expression by random walk model and introduced to a new state equation as an auxiliary state variable. According to the methods of Kalman filter and linear quadratic Gaussian (LQG), the control algorithm based on the new state equation is constructed. Therefore, the system objective function can be created according to the new state vectors including disturbance, state variables and control inputs. Finally, we could obtain the values of current control input by optimal algorithm. The method has been validated in a cantilever beam model and proved good effects. The results reveal the new method proposed were much better than the conventional LQG method.