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http://dx.doi.org/10.5302/J.ICROS.2004.10.5.395

An Adaptive Iterative Learning Control and Identification for Uncertain Robotic Systems  

최준영 (한국전자통신연구원)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.10, no.5, 2004 , pp. 395-401 More about this Journal
Abstract
We present an AILC(Adaptive Iterative Learning Control) scheme and a sufficient condition for system parameter identification for uncertain robotic systems that perform the same tasks repetitively. It is guaranteed that the joint velocity and position asymptotically converge to the reference joint velocity and position, respectively. In addition, it is proved that a sufficient condition for parameter identification is the PE(Persistent Excitation) condition on the regressor matrix evaluated at the reference trajectory during the operation period. Since the regressor matrix on the reference trajectory can be easily computed prior to the real robot operation, the proposed algorithm provides a useful method to verify whether the parameter error converges to zero or not.
Keywords
ILC; AILC; robotic systems; PE condition;
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