Abstract This chapter presents a series of intelligent control schemes for robot manipulator control. A controller using fuzzy logic to infer the learning parameters is developed to improve the performance of the dual-adaptive controller. A new task space/joint space hybrid control scheme for bimanual robot with impedance and force control is also introduced. The task space controller adapts end-point impedance, to compensate for interactive dynamics, and the joint space controller adapts the impedance to improve robustness against external disturbances. An adaptive model reference control is designed for robots to track desired trajectories and for the closed-loop dynamics to follow a reference model, which is derived using the LQR optimization technique to minimize both the motion tracking error and the transient acceleration for a smooth trajectory. A new discrete-time adaptive controller for robot manipulator with uncertainties from the unknown or varying payload is introduced, based on the idea of one-step guess. The history information is used to estimate the unknown fixed or time-varying payload on the end effector.


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    Title :

    Intelligent Control of Robot Manipulator


    Contributors:
    Yang, Chenguang (author) / Ma, Hongbin (author) / Fu, Mengyin (author)


    Publication date :

    2016-01-01


    Size :

    48 pages




    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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