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Adaptive control using multiple models

Narendra, K.S., Balakrishnan, J.·1997·IEEE Transactions on Automatic Control

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.

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Metadata

Authors
Narendra, K. S., & Balakrishnan, J.
Venue
IEEE Transactions on Automatic Control
Published
1997
Volume
42
Issue
2
Pages
171-187
ISSN
0018-9286 (ISSN-L)
OpenAlex
W2111367974
Cited by
1,276
References
0
FWCI
52.72
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Adaptive control using multiple models. https://app.cochat.ai/papers/10.1109/9.554398
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Narendra, K. S., & Balakrishnan, J. (1997). Adaptive control using multiple models. IEEE Transactions on Automatic Control. https://doi.org/10.1109/9.554398

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.