Simple Effective Control for Robot Manipulators with Friction

Friction accounts for more than 60% of the motor torque, and hard nonlinearities due to Coulomb friction and stiction severely degrade control performances as they account for nearly 30% of the industrial robot motor torque. Although many friction compensation methods are available (Armstrong-Helouvry et al., 1994; Lischinsky et al., 1999; Bona & Indri, 2005;), here we only introduce relatively recent research works. Model-based friction compensation techniques (Mei et al., 2006; Bona et al., 2006; Liu et al., 2006) require prior experimental identification, and the drawback of these off-line friction estimation methods is that they can’t adapt when the friction effects vary during the robot operations (Visioli et al., 2001). The adaptive compensation methods (Marton & Lantos, 2007; Xie, 2006) take the modelling error of Lugre friction model into account, but they still require the complex prior experimental identification. Consequently, implementation of these schemes is highly complicated and computationally demanding due to the identification of many parameters and the calculation of the nonlinear friction model. Joint-torque sensory feedback (JTF) (Aghili & Namvar, 2006) compensates friction without the dynamic models, but high price torque sensors are needed for the implementation of JTF. To give satisfactory solution to robot control, in general, we should continue our research in modelling the robot dynamics and nonlinear friction so that they become applicable to wider problem domain. In the mean time, when the parameters of robot dynamics are poorly understood, and for the ease of practical implementation, simple and efficient techniques may represent a viable alternative. Accordingly, the authors developed a non-model based control technique for robot manipulators with nonlinear friction (Jin et al., 2006; Jin et al., 2008). The nonlinear terms in robot dynamics are classified into two categories from the time-delay estimation (TDE) viewpoint: soft nonlinearities (gravity, viscous friction, and Coriolis and centrifugal torques, disturbances, and interaction torques) and hard nonlinearities (due to Coulomb friction, stiction, and inertia force uncertainties). TDE is used to cancel soft nonlinearities, and ideal velocity feedback (IVF) is used to suppress the effect of hard nonlinearities. We refer the control technique as time-delay control with ideal velocity feedback (TDCIVF). Calculation of complex robot model and nonlinear friction model is not required in the TDCIVF. The TDCIVF control structure is transparent to designers; it consists of three elements that have clear meaning: a soft nonlinearity cancelling element, a hard nonlinearity suppressing