Adaptive Control Architectures for Uncertain Systems With Unmodeled Dynamics

Adaptive Control Architectures for Uncertain Systems With Unmodeled Dynamics

K. Merve Dogan

Abstract

Model reference adaptive control is a powerful tool that has a capability to suppress the effect of system uncertainties for achieving a desired level of closed-loop system performance. Yet, for a wide array of applications including unmodeled dynamics such as coupled rigid body systems with flexible interconnection links, airplanes with high aspect ratio wings, and high speed vehicles with strong rigid body and flexible dynamics coupling, the closed-loop system stability with model reference adaptive control laws can be challenged. In this seminar, we will focus on the stability interplay between a class of unmodeled dynamics and system uncertainties for model reference adaptive control laws, and proposed a robustifying term to relax the resulting interplay. The presented system-theoretical findings will be also supported by experimental results in order to bridge the theory-practice gap, where we use a benchmark mechanical system setup involving an inverted pendulum on a cart coupled with another cart through a spring in the presence of unknown frictions.


Presenter

K. Merve Dogan

Graduate Teaching Assistant
University of South Florida
United States
Region 3 Southeastern U.S.

Video

Chair

Organizer

Date & Time

Wed, April 1, 2020