.png){kind=icon}
Return
Stable robot manipulator parameter identification: A closed-loop input error approach
.png){kind=icon}
OA
AI
DOI：10.1016/j.automatica.2022.110294.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This paper presents an on-line parametric estimation method for robot manipulators. The identification algorithm estimates the parameters by using the input error between the robot and a parallel estimated model. Both, the robot and the estimated model are controlled by two Proportional-Derivative (PD) controller tuned with the same gain values, and a persistent excitation (PE) signal for ensuring parameters convergence is included. The exact model matching and the estimation error cases are analysed. Noisy state measurements and filters are avoided in the model parameterization by using only the states of the estimated model. A second parameter identification algorithm, which is based on a composite update law, is also proposed. It improves parameters convergence and robustness of the update rule in presence of estimation errors. The stability of the closed-loop dynamics related to the estimated model is assessed via Lyapunov stability theory. Simulations are carried out to validate the proposed approaches. (C) 2022 Elsevier Ltd. All rights reserved.
Keywords:
System identification
CLIE
Persistent exciting signal
Composite update rule
Estimation error
Parameter convergence
Gradient method
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
5.9
Papers:
1.2W
Citations:
5.2W
Organization
Cited Papers
ShareSavem5U-SVM: identification of RNA 5-methyluridine modification sites based on multi-view features of physicochemical features and distributed representation.png)
BMC Biology
OAAI
BMC BiologyIF0
OAAIShareSaveDC servomechanism parameter identification: A closed loop input error approachISA TRANSACTIONS
ISA TRANSACTIONSIF6.5
PREAI
ShareSaveShareSaveIdentification and optimal control of nonlinear systems using recurrent neural networks and reinforcement learning: An overviewNEUROCOMPUTING
NEUROCOMPUTINGIF6.5
PREAI
ShareSaveShareSaveBody size preferences and sociocultural influences on attitudes towards obesity among Moroccan Sahraoui womenBody Image
Body ImageIF0
PREAI
ShareSave
View more