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Abstract

An apparatus for identifying the structure and estimating the parameters in the structure of a controlled system is described. The apparatus uses a structure identifier, in a preferred embodiment, employing a neural network, to match the relationship of the system inputs and outputs to a mathematical relation. This identified structure is communicated to a parameter estimator. The parameter estimator may employ a neural network to give an initial parameter vector which can be used to generate, iteratively, better parameter estimates. This increases the efficacy of the parameter estimator. The apparatus can be inserted into controllers for various systems to improve performance. Using a neural network for parameter estimation as shown can be generalized to any nonlinear optimization problem.

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