Wongsura, Sirisak (Sirindhorn International Inst. of Tech.), Kongprawechnon, Waree (Sirindhorn International Inst. of Tech.)

Discrete-Time Feedback Error Learning Control without Recourse to Positive Realness

Scheduled for presentation during the Regular Session "Adaptive and Learning Control" (TuP11), Tuesday, July 25, 2006, 17:00−17:25, Room 104a

17th International Symposium on Mathematical Theory of Networks and Systems, July 24-28, 2006, Kyoto, Japan

This information is tentative and subject to change. Compiled on April 25, 2024

Abstract

In this study, a new theoretical foundation on the Discrete-Time Feedback Error Learning (DTFEL) method is established. This is analogous to the original continuous-time version Feedback Error Learning (FEL) method which is proposed as a control model of cerebellum in the field of computational neuroscience. DTFEL method is developed because digital controller is now replacing the analog one and FEL method can not be applied to this type of controller directly. However, the validity of the DTFEL is proved its stability based on the strictly positive realness. In the viewpoint of adaptive control, this is very restricted because some required assumptions can not be satisfied by real systems. Additionally, it is stated that the stability of the system is guaranteed by selecting a sufficiently large positive constant feedback gain. However, from the viewpoint of control system design, it is not clear that how large the feedback gain should be, since such largeness depends on the unknown parameters. This study propose another scheme for the DTFEL method which does not require any positive real conditions. This can be done by utilizing the error signal more effectively.