Multiple-model adaptive control with set-valued observers

— This paper proposes a multiple-model adaptive control methodology, using set-valued observers (MMAC-SVO) for the identification subsystem, that is able to provide robust stability and performance guarantees for the closed-loop, when the plant, which can be open-loop stable or unstable, has significant parametric uncertainty. We illustrate, with an example, how set-valued observers (SVOs) can be used to select regions of uncertainty for the parameters of the plant. We also discuss some of the most problematic computational shortcomings and numerical issues that arise from the use of this kind of robust estimation methods. The behavior of the proposed control algorithm is demonstrated in simulation.

• Type: Conference
• Year: 2009
• Where: CDC
• Authors: Paulo Andre Nobre Rosa, Carlos Silvestre, Jeff S. Shamma, Michael Athans
• Keywords: Adaptive Control Methodology, CDC 2009, Control Systems, Set-valued Observers, Significant Parametric Uncertainty