Title :
Data-driven predictive terminal iterative learning control for a class of discrete-time nonlinear systems
Author :
Jin Shangtai ; Hou Zhongsheng ; Chi Ronghu
Author_Institution :
Adv. Control Syst. Lab., Beijing Jiaotong Univ., Beijing, China
Abstract :
In this paper, a novel data-driven predictive terminal iterative learning control (DDPTILC) scheme is proposed for a class of unknown discrete-time nonlinear systems by combining the advantages of predictive control and terminal iterative learning control. The design and analysis of the proposed DDPTILC merely depends on the real-time measured I/O data without requiring any model information. Rigorous mathematical analysis shows the efficiency of the proposed DDPTILC scheme.
Keywords :
discrete time systems; nonlinear systems; predictive control; DDPTILC scheme; data driven predictive terminal iterative learning control; real time measured I/O data; rigorous mathematical analysis; unknown discrete time nonlinear systems; Control systems; Convergence; Equations; Mathematical model; Nonlinear systems; Prediction algorithms; Predictive control; Data-driven control; Discrete-time nonlinear systems; Predictive control; Terminal ILC;
Conference_Titel :
Control Conference (CCC), 2013 32nd Chinese
