Dynamic Parameter Identification of Parallel Robots Considering Physical Feasibility and Nonlinear Friction Models
نویسندگان
چکیده
This paper deals with the identification problem of the inertial and frictional parameters of a parallel manipulator. Two important issue are considered; the physical feasibility of the identified inertial parameters and the use of linear and nonlinear friction models. The dynamic model, analyzed and reduced to a set of base parameters through the Singular Value Decomposition, is derived starting from the Gibbs-Appell equations of motion along with the Gauss principle of Least Action. The identification process is solved by using nonlinear constrained optimization techniques and it is verified, using exciting periodic trajectories, through a simulated parallel manipulator and applied over an actual 3-DOF RPS parallel manipulator. A comparison is made between the Least Square Method and the proposed optimization process in the case of linear friction models, and between the linear and nonlinear friction models in the optimization process.
منابع مشابه
Friction Compensation for Dynamic and Static Models Using Nonlinear Adaptive Optimal Technique
Friction is a nonlinear phenomenon which has destructive effects on performance of control systems. To obviate these effects, friction compensation is an effectual solution. In this paper, an adaptive technique is proposed in order to eliminate limit cycles as one of the undesired behaviors due to presence of friction in control systems which happen frequently. The proposed approach works for n...
متن کاملAdaptive Control of a 3-DOF Parallel Manipulator Considering Payload Handling and Relevant Parameter Identification
A model-based control system may produce a substantial increase in the overall performance of parallel robots, thus allowing less expensive manufacturing. Although dynamic parameter identification is an experimental technique that significantly improves data feeding dynamic models, some difficulties arise: the effect of the parallel robot's unmodeled dynamics, the variation of some dynamic para...
متن کاملIdentification of an Autonomous Underwater Vehicle Dynamic Using Extended Kalman Filter with ARMA Noise Model
In the procedure of designing an underwater vehicle or robot, its maneuverability and controllability must be simulated and tested, before the product is finalized for manufacturing. Since the hydrodynamic forces and moments highly affect the dynamic and maneuverability of the system, they must be estimated with a reasonable accuracy. In this study, hydrodynamic coefficients of an autonomous un...
متن کاملModelling and Identification of Robots with Both Joint and Drive Flexibilities
Modelling and identification of flexible-joint robots is required for dynamic simulation and model based control of industrial robots. A nonlinear finite element based method is used to derive the dynamic equations of motion in a form suitable for both simulation and identification. The latter requires that the equations of motion are linear in the dynamic parameters. For accurate simulations o...
متن کاملNonlinear Grey-box Identification of Industrial Robots Containing Flexibilities
Nonlinear grey-box identification of industrial robots is considered. A three-step identification procedure is proposed in which parameters for rigid body dynamics, friction, and flexibilities can be identified only using measurements on the motor. In the first two steps, good initial parameter estimates are derived which are used in the last step, where the parameters of a nonlinear physically...
متن کامل