Title :
Norm-Optimal Iterative Learning Control With Intermediate Point Weighting: Theory, Algorithms, and Experimental Evaluation
Author :
Owens, David H. ; Freeman, C.T. ; Thanh Van Dinh
Author_Institution :
Dept. of Autom. Control & Syst. Eng., Univ. of Sheffield, Sheffield, UK
Abstract :
This brief considers the iterative learning control (ILC) problem when tracking is only required at a subset of isolated time points along the trial duration. It presents a norm-optimal ILC solution to the problem with well-defined convergence properties, design guidelines, and supporting experimental results using an electromechanical test facility.
Keywords :
control system synthesis; convergence; iterative methods; learning systems; optimal control; tracking; ILC problem; convergence properties; design guideline; electromechanical test facility; intermediate point weighting; isolated time point; norm-optimal ILC solution; norm-optimal iterative learning control; tracking; Convergence; Eigenvalues and eigenfunctions; Equations; Feedforward neural networks; Frequency modulation; Hilbert space; State feedback; Iterative learning control (ILC); iterative methods; learning control systems; linear systems; motion control; non-minimum phase systems; optimization methods; test facilities;
Journal_Title :
Control Systems Technology, IEEE Transactions on
DOI :
10.1109/TCST.2012.2196281
