PDF control of robotic systems with non-Gaussian disturbances

Haiyong Chen, Hong Wang, De Xu

    Research output: Contribution to conferenceOther


    In this study, the probability density function (PDF) control method has been developed to deal with the random tracking error for a class of robotic manipulator that are subjected to non-Gaussian noises. The control aim is that the shape of the PDF of the tracking error is made as close as possible to the desired PDF. The ILC frame about PDF control approach of manipulators system with non-Gaussian noises has been proposed and a recursive optimization solution batch-by-batch has been developed. In each batch, nonlinear closed-loop error dynamics is considered. In addition, the convergence condition of the tracking control algorithm has been analyzed. Finally, a simulation is given to illustrate the efficiency of the proposed approach. © 2008 Copyright SPIE - The International Society for Optical Engineering.


    Conference7th International Symposium on Instrumentation and Control Technology: Optoelectronic Technology and Instruments, Control Theory and Automation, and Space Exploration
    Period1/07/08 → …


    • Iterative learning control
    • Manipulator control
    • Non-Gaussian noises
    • Probability density function control


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