Title :
Projection algorithm based adaptive iterative learning control for a class of discrete-time systems
Author :
Baobin Liu ; Wei Zhou
Author_Institution :
Coll. of Eng., Jiangsu Inst. of Commerce, Nanjing, China
Abstract :
In this paper, adaptive iterative learning control scheme is designed for a class of discrete-time uncertain systems with random initial state and unknown control gain. The system uncertainty is generated by a stable high-order internal model. The proposed controller incorporates a projection algorithm. Through rigorous analysis, the asymptotical learning convergence along the iteration axis in a finite time interval can be guaranteed, provided the desired trajectory is iteration-varying.
Keywords :
adaptive control; control system synthesis; discrete time systems; iterative learning control; learning systems; stability; uncertain systems; asymptotical learning convergence; discrete-time uncertain systems; iteration-varying trajectory; projection algorithm based adaptive iterative learning control design; random initial state; stable high-order internal model; system uncertainty; unknown control gain; Adaptive systems; Convergence; Discrete-time systems; Projection algorithms; Trajectory; Uncertainty; Adaptive Iterative Learning Control; High-Order Internal Model and Random Initial Condition; Time-Iteration-Varying Parametric Uncertainty; Unknown Control Gain;
Conference_Titel :
Control and Decision Conference (CCDC), 2015 27th Chinese
Conference_Location :
Qingdao
Print_ISBN :
978-1-4799-7016-2
DOI :
10.1109/CCDC.2015.7162434
