Adaptive control using multiple models

TLDR

Intelligent control requires rapid adaptation to unknown but constant environments, a concept first introduced by Narendra et al. (1992) to improve transient response. The paper proposes a general methodology and novel switching and tuning schemes that combine fixed and adaptive models for adaptive control. The methodology employs multiple models, switching, and tuning schemes that integrate fixed and adaptive models.

Abstract

Intelligent control may be viewed as the ability of a controller to operate in multiple environments by recognizing which environment is currently in existence and servicing it appropriately. An important prerequisite for an intelligent controller is the ability to adapt rapidly to any unknown but constant operating environment. This paper presents a general methodology for such adaptive control using multiple models, switching, and tuning. The approach was first introduced by Narendra et al. (1992) for improving the transient response of adaptive systems in a stable fashion. This paper proposes different switching and tuning schemes for adaptive control which combine fixed and adaptive models in novel ways. The principal mathematical results are the proofs of stability when these different schemes are used in the context of model reference control of an unknown linear time-invariant system. A variety of simulation results are presented to demonstrate the efficacy of the proposed methods.