International Journal of Control, Automation and Systems 2019; 17(7): 1856-1865
Published online July 3, 2019
https://doi.org/10.1007/s12555-018-0657-x
© The International Journal of Control, Automation, and Systems
In this paper, a parameter identification method by randomly excited trajectories for decentralized joints of robot manipulators is presented. Each joint of a robot manipulator is decoupled and identified as a second order linear equation by a recursive least square method. Although robot manipulators are a nonlinear and coupled system, decentralized models are required for either the independent joint control such as model-based linear control methods, a time-delayed control (TDC) method or the input torque estimation. The random walk-based parameter identification scheme of using a recursive least square (RLS) method is applied to a mobile manipulator, KOBOKER as a test-bed. Then the identified models are used for designing a state observer to estimate the states of KOBOKER more accurately when the robot follows the sinusoidal trajectory. The accuracies of the identified model and the estimated state are verified experimentally by comparing with the torque of a linearized motion equation.
Keywords Decentralized control, model identification, random walk, robot manipulators, state observer.
International Journal of Control, Automation and Systems 2019; 17(7): 1856-1865
Published online July 1, 2019 https://doi.org/10.1007/s12555-018-0657-x
Copyright © The International Journal of Control, Automation, and Systems.
Sang-Deok Lee, Yeong-Geol Bae, and Seul Jung*
Chungnam National University
In this paper, a parameter identification method by randomly excited trajectories for decentralized joints of robot manipulators is presented. Each joint of a robot manipulator is decoupled and identified as a second order linear equation by a recursive least square method. Although robot manipulators are a nonlinear and coupled system, decentralized models are required for either the independent joint control such as model-based linear control methods, a time-delayed control (TDC) method or the input torque estimation. The random walk-based parameter identification scheme of using a recursive least square (RLS) method is applied to a mobile manipulator, KOBOKER as a test-bed. Then the identified models are used for designing a state observer to estimate the states of KOBOKER more accurately when the robot follows the sinusoidal trajectory. The accuracies of the identified model and the estimated state are verified experimentally by comparing with the torque of a linearized motion equation.
Keywords: Decentralized control, model identification, random walk, robot manipulators, state observer.
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