クロスエントロピー深層学習によるPIDチューニング：リアプノフ安定性解析
PID Tuning using Cross-Entropy Deep Learning: a Lyapunov Stability Analysis
水中無人機の適応制御において、クロスエントロピー深層学習で適応パラメータを決定する学習ベース制御系の安定性を、実験と指標により実証的に解析した。
著者: Hector Kohler, Benoit Clement, Thomas Chaffre, Gilles Le Chenadec
分類: eess.SY, cs.LG, cs.RO, cs.SY
原文アブストラクト
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.
関連論文
- マルチコプター向け適応型PIDオートチューナーと実験結果制御・適応制御
