title: Generalized minimum variance control under long-range prediction horizon setups.
abstract: This paper presents the design and evaluation of a minimal order Generalized Minimum Variance controller with long-range prediction horizon and how it affects the controller and plant output variances. This study investigates how the increased prediction horizon can contribute to mitigate stochastic disturbances and attenuate oscillations. In order to design high order prediction minimum variance filters, a design procedure independent of the Diophantine Equation solution is used. The evaluation is conducted through simulations and practical essays with two different plants: a first order water flow rate problem and a second order under-damped electronic circuit. Both problems are assessed under an incremental control scheme and based on identified stochastic models. Also, two optimal tuning procedures for the algorithm are proposed.
authors.affiliation: Federal University of Pará, Belém, Brazil. Electronic address: asilveira@ufpa.br.
authors.forename: Antonio
authors.initials: A
authors.lastname: Silveira
authors.affiliation: University of Applied Sciences and Arts Hannover, Hannover, Germany. Electronic address: rodrigo.trentini@hs-hannover.de.
authors.forename: Rodrigo
authors.initials: R
authors.lastname: Trentini
authors.affiliation: Federal University of Santa Catarina, Florianópolis, Brazil. Electronic address: antonio.arc@ufsc.br.
authors.forename: Antonio
authors.initials: A
authors.lastname: Coelho
authors.affiliation: University of Applied Sciences and Arts Hannover, Hannover, Germany. Electronic address: ruediger.kutzner@hs-hannover.de.
authors.forename: Rüdiger
authors.initials: R
authors.lastname: Kutzner
authors.affiliation: Leibniz Universität Hannover, Hannover, Germany. Electronic address: hofmann@iee.uni-hannover.de.
authors.forename: Lutz
authors.initials: L
authors.lastname: Hofmann
keywords: Kalman filter; Long-range predictive control; Minimum variance control; Stochastic control