Title :
δ-model Adaptive Algorithm Based on Plant-Parameterization
Author :
Feng, Zhao ; Weiguo, Liu
Author_Institution :
Autom. Dept., Northwestern Polytech. Univ., Xi´´an
Abstract :
Focusing on some adaptive control problems of nonlinear industrial processes under given conditions. This paper proposes a modified iterative scheme of the closed-loop identification and designs delta-model adaptive controller based on plant-parameterization. The modification enables to identify the whole plant using only one coefficient and without the necessity of reducing the order of a new plant model. Moreover, instead of using a least squares algorithm, only a simple formula for identification is used. In addition, introduction of delta-models helps to cope with numerical instabilities of discrete models occurring when a sampling interval is being shortened. Digital simulation demonstrates that the proposed algorithm brings about good control results
Keywords :
adaptive control; closed loop systems; control system analysis; discrete systems; iterative methods; least squares approximations; nonlinear control systems; process control; closed-loop identification; delta-model adaptive controller; discrete models; least squares algorithm; modified iterative scheme; nonlinear industrial process; numerical instability; plant-parameterization; sampling interval; Adaptive algorithm; Adaptive control; Automatic control; Control systems; Design automation; Iterative algorithms; Least squares methods; Robust control; Sampling methods; Transfer functions; Youla-Kucera parameter; adaptive algorithm; iterative methods; least squares algorithm; parameter identification;
Conference_Titel :
Power Electronics and Motion Control Conference, 2006. IPEMC 2006. CES/IEEE 5th International
Conference_Location :
Shanghai
Print_ISBN :
1-4244-0448-7
DOI :
10.1109/IPEMC.2006.4778069