データ駆動設計のための散逸的iFIRフィルタ
Dissipative iFIR filters for data-driven design
仮想参照フィードバックチューニングと散逸性制約を組み合わせ、周波数領域の線形不等式として定式化することで、データ長と制御器複雑度に対してスケーラブルな閉ループ安定性保証付きデータ駆動制御設計を提案し、ソフトグリッパのインピーダンス制御で実証した。
著者: Zixing Wang, Yi Zhang, Fulvio Forni
分類: eess.SY, cs.RO, cs.SY, math.OC
原文アブストラクト
We tackle the problem of providing closed-loop stability guarantees with a scalable data-driven design. We combine virtual reference feedback tuning with dissipativity constraints on the controller for closed-loop stability. The constraints are formulated as a set of linear inequalities in the frequency domain. This leads to a convex problem that is scalable with respect to the length of the data and the complexity of the controller. An extension of virtual reference feedback tuning to include disturbance dynamics is also discussed. The proposed data-driven control design is illustrated by a soft gripper impedance control example.
