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Adaptive predictive controllers based on orthonormal series representation

✍ Scribed by D. Sbarbaro; N. M. Filatov; H. Unbehauen

Publisher
John Wiley and Sons
Year
1999
Tongue
English
Weight
116 KB
Volume
13
Category
Article
ISSN
0890-6327

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✦ Synopsis

This work presents and compares a set of active and passive adaptive predictive controllers based on orthonormal series representations. The controllers are designed according to the receding thorizon principle, where the parameters of the predictive model are considered as random variables. This general framework allows the design of active and passive adaptive controllers, according to the assumptions made over the prediction of the posterior densities of the random variables. Several simulated examples illustrate the characteristics for each algorithm and the performance improvement obtained by active adaptive controllers.

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## Abstract Laguerre Functional Model has many advantages such as good approximation capability for the variances of system time‐delay, order and other structural parameters, low computational complexity, and the facility of online parameter identification, etc., so this model is suitable for compl