Title :
Point-to-point iterative learning control with mixed constraints
Author :
Freeman, C. ; Ying Tan
Author_Institution :
Sch. of Electron. & Comput. Sci., Univ. of Southampton, Southampton, UK
fDate :
June 29 2011-July 1 2011
Abstract :
Iterative learning control is concerned with tracking a reference trajectory defined over a finite time duration, and is applied to systems which perform this action repeatedly. In this paper iterative learning schemes are developed to address the case in which the output is only critical at certain time instants. This freedom makes it possible to incorporate both hard and soft constraints into the control scheme. Experimental results confirm practically and performance.
Keywords :
control system synthesis; iterative methods; learning (artificial intelligence); finite time duration; iterative learning scheme; mixed constraint; point-to-point iterative learning control; reference trajectory; Approximation methods; Convergence; Minimization; Newton method; Optimization; Robots; Robustness;
Conference_Titel :
American Control Conference (ACC), 2011
Conference_Location :
San Francisco, CA
Print_ISBN :
978-1-4577-0080-4
DOI :
10.1109/ACC.2011.5991198
