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Point to Point ILC with Receding Horizon Optimization Approach
Author(s) -
Haris Anwaar,
Yin Yi-xin,
Muhammad Ammar,
Salman Ijaz
Publication year - 2017
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2017914074
Subject(s) - computer science , point (geometry) , horizon , mathematical optimization , control theory (sociology) , artificial intelligence , mathematics , control (management) , geometry
Iterative learning control is a control technique used for the tracking of a finite duration trajectory. Iterative learning control (ILC) with focus on speed of tracking specific points and tracking error on these points is analyzed in this paper. A technique is introduced which employs the receding horizon optimization to track the points along with the iterative learning control is introduced. In order to increase the efficiency of optimization, use of Laguerre functions is introduced which gives more freedom in parameterizing the optimization trajectory and in tuning the optimization parameters. Hence the technique can be efficiently used to track points within the trajectory with good performance.

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