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    Analog Neural Network for Multivariable Algebraic Loops in Constrained Control

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    Poster (1.724Mb)
    Date
    2015
    Author
    Levenson, Richard
    Adegbege, Ambrose A.
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    Abstract
    Abstract
    An analog neural network is designed to efficiently solve the proposed dynamic multivariable algebraic loop representation of a constrained control problem. The neural network is formulated by introducing dynamics into the static algebraic loop representation of the problem which allows it to be applied to a larger class of control problems. The proposed circuit implementation is practical and can be realized directly with passive components and operational amplifiers or with a field programmable analog array (FPAA). An example with various MATLAB simulations is included to demonstrate the effectiveness of the solution.
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    Department of Electrical and Computer Engineering
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    File access restricted due to FERPA regulations
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    • MUSE (Mentored Undergraduate Summer Experience)

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