A decomposition based recursive least squares identification algorithm for input nonlinear systems

Author(s):  
Huibo Chen ◽  
Yongsong Xiao
2020 ◽  
Vol 2020 ◽  
pp. 1-17 ◽  
Author(s):  
Zhiyu Ni ◽  
Shunan Wu ◽  
Yewei Zhang ◽  
Zhigang Wu

Manipulator systems are widely used in payload capture and movement in the ground/space operation due to their dexterous manipulation capability. In this study, a method for identifying the payload parameters of a flexible space manipulator using the estimated system of complex eigenvalue matrix is proposed. The original nonlinear dynamic model of the manipulator is linearized at a selected working point. Subsequently, the system state-space model and corresponding complex eigenvalue parameters are determined by the observer/Kalman filter identification algorithm using the torque input signal of the motor and the vibration output signals of the link. Therefore, the inertia parameters of the payload, that is, the mass and the moment of inertia, can be derived from the identified complex eigenvalue system and mode shapes by solving a least-squares problem. In numerical simulations, the proposed parameter identification method is implemented and compared with the classical recursive least-squares and affine projection sign algorithms. Numerical results demonstrate that the proposed method can effectively estimate the payload parameters with satisfactory accuracy.


2018 ◽  
Vol 355 (8) ◽  
pp. 3737-3752 ◽  
Author(s):  
Feng Ding ◽  
Huibo Chen ◽  
Ling Xu ◽  
Jiyang Dai ◽  
Qishen Li ◽  
...  

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