The problem of adaptive semi-active control of transient structural vibration induced by unknown harmonic excitation is studied. The controller adaptation is attained by using a specially designed reinforcement learning algorithm that adjusts the parameters of a switching control policy to guarantee efficient dissipation of the structural energy. This algorithm relies on an efficient gradient-based sequence that accelerates the learning protocol and results in suboptimal control. The performance of this method is examined through numerical experiments for a span structure that is equipped with a semi-active device of controlled stiffness and damping parameters. The experiments cover a selection of control learning scenarios and comparisons to optimal open-loop and heuristic state-feedback control strategies. This study has confirmed that the developed method has high stabilizing performance, and the relatively low computational burden of the incorporated iterative learning algorithm facilitates its application to multi–degree-of-freedom structures.

中文翻译：

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基于强化学习的控制抑制未知谐波激励下半主动结构的瞬态振动

研究了未知谐波激励引起的瞬态结构振动的自适应半主动控制问题。控制器自适应是通过使用专门设计的强化学习算法来实现的，该算法调整切换控制策略的参数以保证结构能量的有效耗散。该算法依赖于有效的基于梯度的序列，该序列加速学习协议并导致次优控制。通过对配备有受控刚度和阻尼参数的半主动装置的跨结构进行数值实验来检验该方法的性能。实验涵盖了控制学习场景的选择以及与最佳开环和启发式状态反馈控制策略的比较。