強正実性条件に基づくフィードバック誤差学習制御とセンシング障害への応用

抄録

Feedback error learning (FEL) control attains accurate response to a target signal by tuning parameters in feedforward (FF) controller, provided that feedback (FB) control stabilizes the closed-loop in two-degree-of-freedom structure. It has been shown under a certain strictly positive real (SPR) condition that the output error converges to zero for any target signals. In this paper we propose a somewhat different parameter tuning law from a conventional one and give a proof for convergence. We also apply the proposed method to temporal sensing failure. It is known that in networked control the sensing signal may be lost from time to time due to congestion in communication channels. Such temporal sensing failure also happens due to occlusion of non-contact sensors. In this paper, we show that our FEL control scheme is effective for such sensing failure through numerical simulation.