In order to effectively attenuate the inherent hysteresis nonlinearity of magneto-rheological (MR) dampers, and achieve precise tracking control of damping force, a cascaded control strategy based on Hammerstein model is proposed in this paper. A BP neural network is utilized to construct the nonlinear module of Hammerstein model, which accurately captures the hysteresis behavior of MR dampers. The dynamic characteristics of the dampers are then described by a linear time-invariant model. For MR dampers, the cascaded control strategy enhances the robustness of the system compared to traditional open-loop control based on the inverse model schemes. The effectiveness of the proposed control algorithm has been verified through simulation experiments and hardware-in-the-loop experiments using a seat suspension testbed equipped with MR dampers.

中文翻译：

---

基于Hammerstein模型的磁流变阻尼器级联控制策略


为了有效衰减磁流变阻尼器固有的磁滞非线性，实现阻尼力的精确跟踪控制，提出了一种基于Hammerstein模型的级联控制策略。利用BP神经网络构建Hammerstein模型的非线性模块，准确地捕捉磁流变阻尼器的磁滞行为。然后通过线性时不变模型描述阻尼器的动态特性。对于磁流变阻尼器，与基于逆模型方案的传统开环控制相比，级联控制策略增强了系统的鲁棒性。使用配备磁流变阻尼器的座椅悬架试验台通过仿真实验和硬件在环实验验证了所提出控制算法的有效性。