Experience-Based Iterative Learning Controllers for Robotic Systems
作者： M. Arif , T. Ishihara , H. Inooka
关键词: Trajectory 、 Control theory 、 Control (management) 、 Input/output 、 Iterative learning control 、 Control engineering 、 Class (computer programming) 、 Robotic systems 、 Control theory 、 Computer science 、 User defined
摘要: An experience based iterative learning controller is proposed for a general class of robotic systems. Experience the stored in memory terms input output data and later used prediction initial control new desired trajectory. It proved this paper that using approach we can reduce number iterations to achieve certain user defined tracking accuracy. This very applicable all kinds existing schemes. Numerical illustrations showed effectiveness method.
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