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Generalized Quadratic Linearization of Machine Models
Author(s) -
Parvathy Ayalur Krishnamoorthy,
V. Kamaraj,
R. Devanathan
Publication year - 2011
Publication title -
journal of control science and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.208
H-Index - 18
eISSN - 1687-5257
pISSN - 1687-5249
DOI - 10.1155/2011/926712
Subject(s) - linearization , feedback linearization , taylor series , quadratic equation , mathematics , affine transformation , nonlinear system , singularity , control theory (sociology) , computer science , mathematical analysis , control (management) , pure mathematics , physics , artificial intelligence , geometry , quantum mechanics
In the exact linearization of involutive nonlinear system models, the issue of singularity needs to be addressedin practical applications. The approximate linearization technique due to Krener, based on Taylor series expansion, apart from being applicable to noninvolutive systems, allows the singularity issue to be circumvented. But approximate linearization, while removing terms up to certain order, also introduces terms of higher order than those removed into the system. To overcome this problem, in the case of quadratic linearization, a new concept called“generalized quadratic linearization” is introduced in this paper, which seeks to remove quadratic terms without introducing third- and higher-order terms into the system. Also, solution of generalized quadratic linearization of a class of control affine systems is derived. Two machine models are shown to belong to this class and are reduced to only linear terms through coordinate and state feedback. The result is applicable to other machine models aswell

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