Modeling and identification of an RRR-robot

Abstract

A dynamic model of a robot with 3 rotational degrees of freedom is derived in closed form. A systematic procedure for estimation of model dynamic parameters is suggested. It consists of the fallwing steps: (i) identification of friction model parameters for each joint; (ii) calculation of optimal exciting trajectories, required for estimation of the remaining dynamic model parameters; (iii) estimation of these parameters using a least-squares method. The estimated model satisfactory reconstructs experimental control signals, justifying its use in model-based nonlinear control.

Synchronization of Mechanical Systems

“…The torque f i (q i ) models the friction with B v,i the viscous friction coefficient and the other terms representing the Coulomb and Stribeck friction effects. The physical parameters of the dynamic model (2.33, 2.34) have been estimated using an extended Kalman filter in a similar way to the work presented in (Kostic et al 2001). The input torque τ i for collecting the data to run the Kalman filter was set as a P controller, with a desired trajectory q d (t) of frequency 0.4 Hz.…”

“…The parameters in the matrices M (q i ), C(q i ,q i ) and the gravity vector g(q i ) are listed in Table H.3 in Appendix H. The physical parameters of the robots in M (q i ), C(q i ,q i ), g(q i ) and f (q i ) have been estimated by using extended Kalman filters and least square methods in a similar way to the work presented in (Kostic et al 2001). …”

Discrete-time sliding mode control of a direct-drive robot manipulator

“…2, is an experimental facility for research in motion control [13][14][15][16]. Closed-form models of the robot kinematics and rigidbody dynamics are available in [14].…”

“…Their kinematic parameters, according to the well-known DenavitsHartenberg's notation [12], are presented in Table 1. The inertial and friction parameters are estimated with sufficient accuracy in [13]. During motion control, the nonlinearity and couplings in the robot dynamics are reduced using (2) q was the known reference motion, and 1 e was reconstructed according to (13).…”

“…The inertial and friction parameters are estimated with sufficient accuracy in [13]. During motion control, the nonlinearity and couplings in the robot dynamics are reduced using (2) q was the known reference motion, and 1 e was reconstructed according to (13). Practical procedures to identify an FRF as shown in Fig.…”