DocumentCode :
1377695
Title :
MIMO Closed Loop Identification of an Industrial Robot
Author :
Calanca, Andrea ; Capisani, Luca M. ; Ferrara, Antonella ; Magnani, Lorenza
Author_Institution :
Dept. of Comput. Eng. & Syst. Sci., Univ. of Pavia, Pavia, Italy
Volume :
19
Issue :
5
fYear :
2011
Firstpage :
1214
Lastpage :
1224
Abstract :
This paper proposes a practical multi-input multi-output (MIMO) closed loop parameters identification procedure for robot manipulators. It is based on the weighted least squares (WLS) method, coupled with particular solutions to facilitate the estimation, reducing the noise effect. More precisely, a two steps procedure to reduce the condition number of the input data matrix with optimal trajectory planning, and a method to estimate the variances matrix to be used as a weight matrix for the WLS method are illustrated. Moreover, the identification problem is solved with reference to an MIMO coupled system. A closed loop identification is needed because the system is open loop unstable, and because the robot has to track an optimal reference input so as to correctly execute the identification procedure. Some solutions are also presented to overtake common identification problems, such as the bias of the estimated parameters, the presence of outliers, the necessity of balancing the kinematics of the third link, and the reduction of the sensitivity to noise of the estimate. The presented procedure has been successfully experimentally tested on a COMAU SMART3-S2 industrial manipulator used in a planar configuration.
Keywords :
MIMO systems; closed loop systems; identification; industrial manipulators; least squares approximations; optimal systems; parameter estimation; path planning; position control; sensitivity analysis; COMAU SMART3-S2 industrial manipulator; MIMO closed loop identification; MIMO coupled system; closed loop identification; identification procedure; industrial robot; input data matrix; noise effect reduction; optimal reference; optimal trajectory planning; parameters identification; planar configuration; robot manipulators; sensitivity reduction; variances matrix estimation; weighted least squares method; Least squares methods; MIMO; Manipulators; Robots; System identification; Manipulators; robots; system identification;
fLanguage :
English
Journal_Title :
Control Systems Technology, IEEE Transactions on
Publisher :
ieee
ISSN :
1063-6536
Type :
jour
DOI :
10.1109/TCST.2010.2077294
Filename :
5634145
Link To Document :
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