A program of active vibration control with unknown excitations was studied here. According to the knowledge of Kalman filtering and linear quadratic Gaussian(LQG) method, the control algorithm based on random walk and input estimation was proposed. First, the excitations were described as discrete recursive forms by using random walk model and they were introduced into state functions of the control system as auxiliary state variables. And then, the Kal- man filtering principle was used to estimate the unknown excitations combining the auxiliary state functions. So, the sys- tem target functions could be created according to the estimation values of the unknown excitations, state variables and the known measured outputs. Finally, using the LQG algorithm to get the optimal values of current control inputs. Good con- trol effects were proved by numeric simulation with sdof and 2dof models. The results were better than those based on the conventional LQG method.%为研究未知外扰作用下动力学系统的振动主动控制问题,结合Kalman滤波和LQG(linear quadratic Gaussian)控制方法,提出了基于随机游走和输入估计的振动主动控制方法.为尽量获取未知外扰信息,首先采用随机游走模型构建未知外扰信号的离散递推形式,并将其作为辅助状态引进受控系统的状态方程.然后,借助具有信号识别和跟踪能力的Kalman滤波原理,对含有辅助状态的系统进行状态估计,从而得到未知外扰的估计值.根据系统已知测量输出、未知状态及外扰的估计值构造系统目标函数,采用LQG方法求解系统最优控制输入.最后针对sdof和2dof模型进行数值仿真,结果表明受控系统在非随机和随机外扰激励下都具有良好的控制效果,且控制精度优于传统LQG方法.
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