Design of a Database-Driven Kansei Feedback Control System with Determination Mechanism of Learning Rate

Abstract

In recent years, the visualization technology of Kansei has been studied, and the database-driven Kansei feedback control scheme has been proposed. It aims at improving Kansei, which is human sensitivity, when the equipment operation is conducted. It is necessary to appropriately determine the learning rate included in the database-driven control scheme to achieve better control performance. This paper proposes a database-driven Kansei feedback control scheme with a determination mechanism of learning rate, and the stability is proved based on the Lyapunov function. In addition, the effectiveness of the proposed scheme is numerically verified.