. "[21996E606280]" . . . "2" . "2"^^ . . . "SK - Slovensk\u00E1 republika" . "1"^^ . "Application of noise filter with multivariable GPC"@en . . . "RIV/00216275:25530/07:00005213!RIV08-MSM-25530___" . "\u010Cl\u00E1nek je v\u011Bnov\u00E1n prediktivn\u00EDmu \u0159\u00EDzen\u00ED Generalized Predictive Control, kter\u00E9 je zalo\u017Eeno na CARIMA modelu procesu. Jsou uvedeny regula\u010Dn\u00ED experimenty na laboratorn\u00EDm za\u0159\u00EDzen\u00ED. Polynom \u0161umu je uva\u017Eov\u00E1n jako laditeln\u00FD parametr regul\u00E1toru. Je uk\u00E1z\u00E1no jak tento polynom (filtr dat) zvy\u0161uje robustnost regul\u00E1toru proti vysokofrekven\u010Dn\u00EDm poruch\u00E1m - nap\u0159. proti \u0161umu m\u011B\u0159en\u00ED."@cs . "Aplikace filtru \u0161umu s v\u00EDcerozm\u011Brov\u00FDm prediktivn\u00EDm regul\u00E1torem"@cs . . . "AT&P journal PLUS 2" . . . "RIV/00216275:25530/07:00005213" . . . "Application of noise filter with multivariable GPC" . "Z(MSM0021627505)" . . . "2" . "410495" . "25530" . . "Aplikace filtru \u0161umu s v\u00EDcerozm\u011Brov\u00FDm prediktivn\u00EDm regul\u00E1torem"@cs . . "Haber, Robert" . "TITO control; generalized predictive control; CARIMA model; noise model; noise filtering"@en . "6"^^ . "Popularity of Model Predictive Control techniques is growing in recent years. It is an intuitive and general design method convenient for controlling of multivariable plants, systems with dead-times and it enables simple constraints handling and future references. Authors deal with Generalized Predictive Control based on CARIMA process model. Control experiments with pilot plant are presented by considering the noise polynomial as a tuneable controller parameter. It is shown how the noise polynomial (data filter) improves the controller insensitivity against the high frequency uncertainties ? i.e. the measurement noise." . "112-117" . "Application of noise filter with multivariable GPC" . "Popularity of Model Predictive Control techniques is growing in recent years. It is an intuitive and general design method convenient for controlling of multivariable plants, systems with dead-times and it enables simple constraints handling and future references. Authors deal with Generalized Predictive Control based on CARIMA process model. Control experiments with pilot plant are presented by considering the noise polynomial as a tuneable controller parameter. It is shown how the noise polynomial (data filter) improves the controller insensitivity against the high frequency uncertainties ? i.e. the measurement noise."@en . "Application of noise filter with multivariable GPC"@en . "Honc, Daniel" . "1336-5010" .