A Decentralized Model Identification Scheme by Random-work RLS Process for Robot Manipulators: Experimental Studies

다국어 초록 (Multilingual Abstract)

In this paper, a parameter identification method by randomly excited trajectories for decentralized jointsof robot manipulators is presented. Each joint of a robot manipulator is decoupled and identified as a secondorder linear equation by a recursive least square method. Although robot manipulators are a nonlinear and coupledsystem, decentralized models are required for either the independent joint control such as model-based linear controlmethods, a time-delayed control (TDC) method or the input torque estimation. The random walk-based parameteridentification scheme of using a recursive least square (RLS) method is applied to a mobile manipulator, KOBOKERas a test-bed. Then the identified models are used for designing a state observer to estimate the states of KOBOKERmore accurately when the robot follows the sinusoidal trajectory. The accuracies of the identified model and theestimated state are verified experimentally by comparing with the torque of a linearized motion equation.

참고문헌 (Reference)

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