"2"^^ . "Pardubice" . . "2"^^ . . "Kombinace diskr\u00E9tn\u00ED delta identifikace a spojit\u00E9 synt\u00E9zy regul\u00E1toru"@cs . "1"^^ . . . "This paper considers the application of continuous self-tuning PID controller. The process is identified by the regression (ARX) model using the recursive least squares method (RLSM). The basic RLSM algorithm has been modified for the discrete delta model structures. This is used delta models for identification. Delta operator approximates derivative and the approximation becomes better as the sampling period tends to zero. The delta operator converges with decreased sampling period to a continuous operator ( ). For small sampling period can be used delta parameters as continuous parameters. Than can be used any continuous controller synthesis.The proposed hybrid control which consists of continuous-time self-tuning controller and recursive least square delta identification of the system demonstrate very good dynamic behaviour. Figure 1 shows the example of control process with very small sampling period . The advantages of this method include simplicity in the recursive identification part (the"@en . "2004-06-08+02:00"^^ . "1" . "Univerzita Pardubice" . "P\u0159\u00EDsp\u011Bvek popisuje kombinaci spojit\u00E9ho samo\u010Dinn\u011B se nastavuj\u00EDc\u00EDho PID regul\u00E1toru a pr\u016Fb\u011B\u017En\u00E9 diskr\u00E9tn\u00ED Delta identifikace. Proces je identifikov\u00E1n rekurzivn\u00ED metodou nejmen\u0161\u00EDch \u010Dtverc\u016F, kter\u00E1 je modifikov\u00E1na pro diskr\u00E9tn\u00ED delta modely. Delta model aproximuje derivaci. Se zmen\u0161uj\u00EDc\u00ED se periodu vzorkov\u00E1n\u00ED dost\u00E1v\u00E1me kvalitn\u011Bj\u0161\u00ED aproximaci. Z toho je z\u0159ejm\u00E9, \u017Ee Delta oper\u00E1tor konverguje se sni\u017Euj\u00EDc\u00ED se periodou vzorkov\u00E1n\u00ED k spojit\u00E9mu oper\u00E1toru. Potom pro velmi mal\u00E9 periody vzorkov\u00E1n\u00ED lze prohl\u00E1sit, \u017Ee delta parametry soustavy velmi p\u0159esn\u011B aproximuj\u00ED spojit\u00E9 parametry. S vyu\u017Eit\u00EDm tohoto p\u0159edpokladu m\u016F\u017Eeme po Delta identifikaci pou\u017E\u00EDt libovolnou spojitou synt\u00E9zu regul\u00E1toru.Navr\u017Een\u00E9 Hybridn\u00ED \u0159\u00EDzen\u00ED, kter\u00E9 se skl\u00E1d\u00E1 ze spojit\u00E9ho samo\u010Dinn\u011B se nastavuj\u00EDc\u00EDho regul\u00E1toru a rekurzivn\u00ED Delta identifikace zalo\u017Een\u00E9 na metod\u011B nejmen\u0161\u00EDch \u010Dtverc\u016F vykazuje velmi dobr\u00E9 dynamick\u00E9 vlastnosti. p\u0159\u00EDsp\u011Bvek ukazuje p\u0159\u00EDklad \u0159\u00EDzen\u00ED s velmi malou periodou vzorkov\u00E1n\u00ED. V\u00FDhody t\u00E9to nov\u00E9 metody zahrnuj\u00ED jednoduchost v rekurzivn\u00ED identifi"@cs . "Proceedings the 6th International Scientific - Technical Conference Proces Control 2004" . "558073" . "[2D4996B122D8]" . "Combination of Discrete Delta Identification and Continuous Controller Synthesis"@en . . "28110" . "Kombinace diskr\u00E9tn\u00ED delta identifikace a spojit\u00E9 synt\u00E9zy regul\u00E1toru"@cs . . . "RIV/70883521:28110/04:63502370" . "80-7194-662-1" . "Combination of Discrete Delta Identification and Continuous Controller Synthesis" . . "P(GP102/02/P042), Z(MSM 281100001)" . "Combination of Discrete Delta Identification and Continuous Controller Synthesis" . . "This paper considers the application of continuous self-tuning PID controller. The process is identified by the regression (ARX) model using the recursive least squares method (RLSM). The basic RLSM algorithm has been modified for the discrete delta model structures. This is used delta models for identification. Delta operator approximates derivative and the approximation becomes better as the sampling period tends to zero. The delta operator converges with decreased sampling period to a continuous operator ( ). For small sampling period can be used delta parameters as continuous parameters. Than can be used any continuous controller synthesis.The proposed hybrid control which consists of continuous-time self-tuning controller and recursive least square delta identification of the system demonstrate very good dynamic behaviour. Figure 1 shows the example of control process with very small sampling period . The advantages of this method include simplicity in the recursive identification part (the" . . "Bob\u00E1l, Vladim\u00EDr" . . . . . "Sysel, Martin" . "Combination of Discrete Delta Identification and Continuous Controller Synthesis"@en . . . "Kouty nad Desnou" . "RIV/70883521:28110/04:63502370!RIV/2005/GA0/281105/N" . . . . . "Delta; identification; adaptive control; continuous controller"@en .