风洞悬臂杆结构主动减振系统的研究

风洞测试时悬臂杆振动会影响测试数据的准确性，为了抑制悬臂杆振动，设计了基于压电驱动器的主动减振系统，提出了将人工神经网络与传统比例积分微分(proportion integration differentiation, 简称PID)相结合的智能控制算法，实现了控制参数在线实时调整。对该控制系统的减振性能分别进行了地面试验和风洞试验，并与采用传统PID控制的试验结果进行对比。结果表明，神经网络PID控制下的振动收敛时间比传统PID缩短了50%，而且在不同风速和攻角下，悬臂杆系统的1阶模态振动均得到了有效衰减（衰减幅度>19 dB），表现出良好的鲁棒性。

Study of Active Damping System for the Cantilever Sting in Wind Tunnel Based on Piezoelectric Actuators

In order to decrease the influence of sting vibration on wind tunnel testing data, an active vibration reduction system using piezoelectric actuators is developed. The variation and complicated nature of the sting system make it challenging to model and determine the control parameter for a conventional PID. To solve this problem, a new control method combining a neural network and conventional PID is proposed. The performance of the control system is then validated through both ground tests and wind tunnel tests using balance signal feedback. Results show that decay time can be shortened by 50% compared to using a conventional PID, and the first mode amplitude is damped at least 19 dB under various wind speeds and attack angles.