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Non-linear on-line identifiers and adaptive control systems.

It is assumed that processes to be identified or controlled can be described by linear or non-linear differential equations with unknown coefficients aᵢ. For on-line identifications a model is constructed to have the same form of differential equation as the process, but with adjustable parameters αᵢ replacing the aᵢ. The parameters αᵢ are adjusted in a steepest descent fashion; they are shown to converge to the aᵢ as long as an adjustment gain K(t) is non-negative, and not identically zero.
An approximate analysis is carried out to determine the best constant K which gives the fastest identification. Optimal control theory is introduced to find the best piecewise continuous K(t) in the interval 0 ≤ K(t) ≤ Kmax . From the exact solution in a special case, a switched suboptimal K which always gives fast identification is determined.
Identification schemes are developed for processes which include an unknown non-linearity that, can be assumed to be piecewise linear.
An adaptive control, system is developed to control processes with unknown time-varying coefficients. The system is shown to be stable as long as the process inverse is stable; the process need not be stable. Systems to control linear and non-linear unstable processes are designed and simulated. The limitations of the adaptive system are determined, and compared with the limitations of conventional feedback systems. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

Identiferoai:union.ndltd.org:UBC/oai:circle.library.ubc.ca:2429/36689
Date January 1966
CreatorsButler, Robert Ewart
PublisherUniversity of British Columbia
Source SetsUniversity of British Columbia
LanguageEnglish
Detected LanguageEnglish
TypeText, Thesis/Dissertation
RightsFor non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.

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