"1790-5117" . . . . . "Adaptive Continuous-Time Decoupling Control" . . "6"^^ . "1586" . . "multivariable control, control algorithms, adaptive control, polynomial methods, pole assignment, recursive identification"@en . "Latest Trends on Systems. Volume II" . . "2"^^ . "Adaptive Continuous-Time Decoupling Control"@en . . "Bob\u00E1l, Vladim\u00EDr" . "V" . "The paper is focused on a design and implementation of a decoupling multivariable controller. The controller was designed in continuous-time version. The control algorithm is based on polynomial theory and pole \u2013 placement. A decoupling compensator is used to suppress interactions between control loops. The controller integrates an on \u2013 line identification of an ARX model of a controlled system and a control synthesis on the basis of the identified parameters. The model parameters are recursively estimated using the recursive least squares method. It is not possible to measure directly input and output derivatives of a system in case of continuous \u2013 time control loop. One of the possible approaches to this problem is establishing of filters and filtered variables to substitute the primary variables. The filtered variables are then used in the recursive identification procedure."@en . . "2014-07-17+02:00"^^ . "RIV/70883521:28140/14:43872328" . . "Europment" . "Adaptive Continuous-Time Decoupling Control" . "2"^^ . "28140" . . "Adaptive Continuous-Time Decoupling Control"@en . . . . "RIV/70883521:28140/14:43872328!RIV15-MSM-28140___" . "[2F23F9990DBA]" . . "978-1-61804-244-6" . "The paper is focused on a design and implementation of a decoupling multivariable controller. The controller was designed in continuous-time version. The control algorithm is based on polynomial theory and pole \u2013 placement. A decoupling compensator is used to suppress interactions between control loops. The controller integrates an on \u2013 line identification of an ARX model of a controlled system and a control synthesis on the basis of the identified parameters. The model parameters are recursively estimated using the recursive least squares method. It is not possible to measure directly input and output derivatives of a system in case of continuous \u2013 time control loop. One of the possible approaches to this problem is establishing of filters and filtered variables to substitute the primary variables. The filtered variables are then used in the recursive identification procedure." . "Santorini" . "Rhodes" . . "Kubal\u010D\u00EDk, Marek" . . . .