STOCHASTIC AUGMENTATION BY GENERALIZED MINIMUM VARIANCE CONTROL WITH RST LOOP-SHAPING

Tarcisio Carlos Farias Pinheiro¹; Anderson de França Silva¹; Antonio da Silva Silveira¹; Maryson Da silva Araújo¹

¹ Universidade Federal do Pará

Baixar PDF

Resumo

In this work we use the RST structure to shape the GMV optimization problem. The RST controller is tuned by pole assignment based on a second order plant model and a second order desired closed-loop model. The derived RST controller is then passed to the GMV generalized output weighting polynomials in order to produce a stochastic equivalent controller. The result is the equivalence of the RST and the GMV produced closed-loop dynamics whilst in ideal conditions (without noise or uncertainties), but a more economic and efficient GMV closed-loop dynamics under an adverse stochastic scenario.

Palavras-chave: STOCHASTIC AUGMENTATION; RST CONTROLLER; GENERALIZED MINIMUM VARIANCE CONTROL