Huang Zhicheng, Cheng Yang, Wang Xingguo, Wu Nanxing
College of Mechanical and Electronic Engineering, Jingdezhen Ceramic University, Jingdezhen 333001, China.
Biomimetics (Basel). 2024 Sep 25;9(10):584. doi: 10.3390/biomimetics9100584.
The paper partially covered Active Constrained Layer Damping (ACLD) cantilever beams' dynamic modeling, active vibration control, and parameter optimization techniques as the main topic of this research. The dynamic model of the viscoelastic sandwich beam is created by merging the finite element approach with the Golla Hughes McTavish (GHM) model. The governing equation is constructed based on Hamilton's principle. After the joint reduction of physical space and state space, the model is modified to comply with the demands of active control. The control parameters are optimized based on the Kalman filter and genetic algorithm. The effect of various ACLD coverage architectures and excitation signals on the system's vibration is investigated. According to the research, the genetic algorithm's optimization iteration can quickly find the best solution while achieving accurate model tracking, increasing the effectiveness and precision of active control. The Kalman filter can effectively suppress the impact of vibration and noise exposure to random excitation on the system.
本文部分涵盖了主动约束层阻尼（ACLD）悬臂梁的动态建模、主动振动控制和参数优化技术，作为本研究的主要主题。通过将有限元方法与戈拉·休斯·麦克塔维什（GHM）模型相结合，建立了粘弹性夹层梁的动态模型。基于哈密顿原理构建控制方程。在对物理空间和状态空间进行联合降阶后，对模型进行修改以符合主动控制的要求。基于卡尔曼滤波器和遗传算法对控制参数进行优化。研究了各种ACLD覆盖结构和激励信号对系统振动的影响。研究表明，遗传算法的优化迭代能够在实现精确模型跟踪的同时快速找到最优解，提高主动控制的有效性和精度。卡尔曼滤波器能够有效抑制随机激励对系统的振动和噪声影响。
