部分観測確率システムの階層制御
Layered Control of Partially Observed Stochastic Systems
部分観測と確率的ノイズ下での階層制御の理論基盤を確立し、各層の状態推定器間の出力距離を事前計算可能な範囲に保つ確率的シミュレーション関数を導入。線形システムとカルマンフィルタに対して構築法を示し、航空ロボットの例で実証した。
著者: Charis Stamouli, Anastasios Tsiamis, George J. Pappas
分類: eess.SY
原文アブストラクト
Layered control is essential for managing complexity in large-scale systems, employing progressively coarser models at higher layers. While significant advances have been made for fully observable systems, the theoretical foundations of layered control under partial observations and stochastic noise remain underexplored. To address this gap, we propose a principled layered control framework for such settings. Given a state estimator at each layer, our approach ensures that the expected output distance between systems at successive layers remains within a priori computable bounds. This is achieved by introducing a novel notion of stochastic simulation functions for partially observed systems. For the class of linear systems with Kalman estimators, we provide a systematic construction of these functions along with the corresponding control design. We demonstrate our framework on two aerial robotic scenarios: an unmanned aerial vehicle and a hexacopter with a camera payload.