Abstract
A basic analysis is carried out on identification, prediction, and control of a single degree of freedom system. First, the responses of the system excited by an active control device installed on the system are effectively utilized to identify the dynamic properties of the system which is modeled by a multi-variate ARMA model. Then, general modes of aninstantaneous optimal prediction control rule are formulated in terms of the identified components of the coefficient matrix of the ARMA model and the weights included in the control objective function. Based on the formulation, a neural network is derived whose links have physically meaningful weights.
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© 1994 Springer-Verlag, Berlin Heidelberg
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Hoshiya, M., Saito, Y. (1994). Prediction Control of Structures by ARMA Modeling. In: Spanos, P.D., Wu, YT. (eds) Probabilistic Structural Mechanics: Advances in Structural Reliability Methods. International Union of Theoretical and Applied Mechanics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-85092-9_16
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DOI: https://doi.org/10.1007/978-3-642-85092-9_16
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