Identification of Dynamic Parameters of A 3-DOF RPS Parallel Manipulator

edkadik's picture
Journal Title, Volume, Page: 
Mechanism and Machine Theory Volume 43, Issue 1, January 2008, Pages 1–17
Year of Publication: 
2008
Authors: 
Nidal Farhat
Departamento de Ingeniería Mecánica y de Materiales, Universidad Politécnica de Valencia, C/Camino de Vera s/n, 46022 Valencia, Spain
Current Affiliation: 
Department of Mechanical Engineering, Faculty of Engineering, An-Najah National University, Nablus, P.O. Box 7, Palestine
Vicente Mata
Departamento de Ingeniería Mecánica y de Materiales, Universidad Politécnica de Valencia, C/Camino de Vera s/n, 46022 Valencia, Spain
Alvaro Page
Departamento de Física Aplicada, Universidad Politécnica de Valencia, C/Camino de Vera s/n, 46022 Valencia, Spain
Francisco Valero
Departamento de Ingeniería Mecánica y de Materiales, Universidad Politécnica de Valencia, C/Camino de Vera s/n, 46022 Valencia, Spain
Preferred Abstract (Original): 

In this paper, the dynamic parameters, both inertial and frictional, of a 3-DOF RPS parallel manipulator are identified considering two important issues: the physical feasibility of the identified inertial parameters and the use of nonlinear friction models in the identification process in order to model the friction phenomenon at robot joints. The dynamic model of the parallel manipulator is obtained starting from the Gibbs–Appell equations of motion along with the Gauss principle of Least Action, and these equations of motion are rewritten in a/their linear form with respect to the inertial parameters of the mechanical system. At this point, in accordance with the friction model considered, either linear or nonlinear, two types of dynamic models are dealt with: the totally and the partially linear with respect to the parameters to be identified. In order to solve the identification problem when nonlinear friction models are included, a nonlinear constrained optimization problem will be formulated and solved, instead of the Least Square Method, which is valid only for linear identification problems. It must be mentioned that the above-mentioned optimization problem will include the physical feasibility of the identified parameters in its formulation. The proposed procedure will be verified against a virtual parallel manipulator and finally, experimental identification processes are carried out over an actual parallel manipulator and a comparison is made between the LSM and the optimization process in the case of linear friction models, and between the linear and nonlinear friction models in the optimization process.