Iterative Learning Controller for Trajectory Tracking Tasks Based on Experience Database

  • Xuesong Wang
  • Yuhu Cheng
  • Wei Sun
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3930)


An iterative learning controller based on experience database is proposed for a class of robotic trajectory tracking tasks. It is very general for supporting all types of iterative learning control schemes. The experience database consists of previously tracked trajectories and their corresponding control inputs. The initial control input of an iterative learning controller can be selected properly using a dynamic RBF neural network by properly considering the past experience of tracking various trajectories. Moreover, the RBF network can be created dynamically to ensure the network size is economical. Simulation results of trajectory tracking of a planar two-link manipulator indicate that the convergence speed of the iterative learning controller can be improved by using this method.


Hide Unit Trajectory Tracking Query Point Experience Database Trajectory Tracking Control 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Xuesong Wang
    • 1
  • Yuhu Cheng
    • 1
  • Wei Sun
    • 1
  1. 1.School of Information and Electrical EngineeringChina University of Mining and TechnologyXuzhouChina

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