Underwater Unmanned Vehicles (UUVs) have to constantly compensate for the
external disturbing forces acting on their body. Adaptive Control theory is
commonly used there to grant the control law some flexibility in its response
to process variation. Today, learning-based (LB) adaptive methods are leading
the field where model-based control structures are combined with deep
model-free learning algorithms. This work proposes experiments and metrics to
empirically study the stability of such a controller. We perform this stability
analysis on a LB adaptive control system whose adaptive parameters are
determined using a Cross-Entropy Deep Learning method.

研究论文提出了一种基于学习的自适应控制系统，使用交叉熵深度学习方法确定自适应参数，并通过实验和指标对其稳定性进行了研究。

基于交叉熵深度学习的 PID 调参：一种李雅普诺夫稳定性分析

PID Tuning using Cross-Entropy Deep Learning: a Lyapunov Stability  Analysis

The structural response under the earthquake excitations can be simulated by
scaled-down model shake table tests or full-scale model shake table tests. In
this paper, adaptive control theory is used as a nonlinear shake table control
algorithm which considers the inherent nonlinearity of the shake table system
and the Control-Structural Interaction (CSI) effect that the linear controller
cannot consider, such as the Proportional-Integral-Derivative (PID) controller.
The mass of the specimen can be assumed as an unknown variation and the unknown
parameter will be replaced by an estimated value in the proposed control
framework. The signal generated by the control law of the adaptive control
method will be implemented by a loop-shaping controller. To verify the
stability and feasibility of the proposed control framework, a simulation of a
bare shake table and experiments with a bare shake table with a two-story frame
were carried out. This study randomly selects Earthquake recordings from the
Pacific Earthquake Engineering Research Center (PEER) database. The simulation
and experimental results show that the proposed control framework can be
effectively used in shake table control.

该研究利用自适应控制理论作为非线性振动台控制算法，考虑振动台系统的固有非线性和线性控制器无法考虑的控制 - 结构相互作用效应，通过估计未知参数替代材料质量的变动，然后使用环形控制器实现的自适应控制方法的控制律，使用太平洋地震工程研究中心（PEER）数据库的地震记录进行模拟与实验，并表明该控制框架能够有效用于振动台控制。