Title :
Comments on "An iterative learning controller with initial state learning"
Author :
Lucibello, Pasquale
Author_Institution :
Sogin-Societa Gestione Impianti Nucleari, Rome, Italy
fDate :
4/1/2002 12:00:00 AM
Abstract :
In the original paper of Chen, Wen, Gong and Sun (ibid., vol.44 , p.371-6, 1999), initial state learning was considered for a class of nonlinear control systems. This paper treats of the linear setting. Its purpose is threefold. (1) It draws the readers´ attention to some papers addressing initial state learning not cited in the aforementioned paper. (2) It points out that the class of control systems addressed in the aforementioned paper is restricted to that of systems with state-space dimension equal to output space dimension, but that this hypothesis can be removed. (3) It analyzes the point of convergence of the algorithm proposed in the aforementioned paper when applied to systems with internal dynamics.
Keywords :
convergence; iterative methods; learning (artificial intelligence); convergence; initial state learning; internal dynamics; iterative learning controller; linear systems; output space dimension; state-space dimension; Algorithm design and analysis; Control systems; Control theory; Convergence; Error correction; Linear systems; Manipulators; Motion control; Robots; Robust control;
Journal_Title :
Automatic Control, IEEE Transactions on