Abstract:A new dynamic model to describe joint friction in a industrial robot is presented. This model is an extension of the popular LuGre dynamic friction model. However, the description of the Stribeck effect is modeled with a first order nonlinear differential equation. This yields a second order dynamic friction model that still preserves the intuitive base of previous models, reproduces the pseudo-steady state behavior and offers the same input-output properties. The advantage with respect to other dynamic fricti… Show more
“…Figure 20 shows typical responses when the NIASA compensator is combined with the standard PID controller. A plot for the NIASA compensator combined with the high performance PID controller is not shown because it is visually indistinguishable from figure 20. As compared to either PID controller, the NIASA compensator appears to significantly reduce the position error when tracking the gross motion of the step.…”
Section: Small Step Experimentsmentioning
confidence: 98%
“…Friction observers have been successfully implemented with most significant advanced friction models [2,5,11,13,14,15,16,17,18]. Several adaptive extensions have also been investigated [19,20,21,22,23]. In many previous efforts, friction observers are shown to improve servo tracking performance [2,5,14,15].…”
The aim of this work is to discuss methods of friction identification and provide experimental evaluation of a novel control algorithm that enhances settling after point-to-point motion. This algorithm is called the Nonlinear Integral Action Settling Algorithm or NIASA. As the name suggests, the integral gain is nonlinear, and is based upon a Dahl friction model. The settling resulting from PID+NIASA control is nearly exponential, and governed by a time constant that is specified in the control design. As the NIASA algorithm requires, friction parameters must be identified for the servo under test. Two methods of friction identification (Step Tests and Identification Profile) are contrasted and found to provide comparable results, although the latter can provide advantages. The identified friction parameters are in turn used to perform four sets of control experiments; Two PID controllers (standard factory tuning and high performance PID with acceleration feedforward) are tested both with and without NIASA compensation. In the case study with a factory tuned PID controller, servo settling times to within ± 3 to ± 100 nm, are reduced by between 80.5% and 87.4% when NIASA compensation is added. When the NIASA compensator is added to the high performance PID controller, servo settling time is still reduced by between 50.5% and 73.0%. Although the NIASA compensator was designed to increase settling performance for relatively large point-to-point motions, similar positive results are achieved when the method is applied to smaller step motions that do not leave the pre-rolling friction regime. Frequency domain analyses demonstrated the nonlinear loop-gain of the plant, with a clear distinction between the rolling and pre-rolling friction cases. As expected, the nonlinear loop gain was found to lower the bandwidth for smaller motions. Adding NIASA control was observed to increase the bandwidth for small motions by a factor of 3-6, while having little effect on for large motions.
“…Figure 20 shows typical responses when the NIASA compensator is combined with the standard PID controller. A plot for the NIASA compensator combined with the high performance PID controller is not shown because it is visually indistinguishable from figure 20. As compared to either PID controller, the NIASA compensator appears to significantly reduce the position error when tracking the gross motion of the step.…”
Section: Small Step Experimentsmentioning
confidence: 98%
“…Friction observers have been successfully implemented with most significant advanced friction models [2,5,11,13,14,15,16,17,18]. Several adaptive extensions have also been investigated [19,20,21,22,23]. In many previous efforts, friction observers are shown to improve servo tracking performance [2,5,14,15].…”
The aim of this work is to discuss methods of friction identification and provide experimental evaluation of a novel control algorithm that enhances settling after point-to-point motion. This algorithm is called the Nonlinear Integral Action Settling Algorithm or NIASA. As the name suggests, the integral gain is nonlinear, and is based upon a Dahl friction model. The settling resulting from PID+NIASA control is nearly exponential, and governed by a time constant that is specified in the control design. As the NIASA algorithm requires, friction parameters must be identified for the servo under test. Two methods of friction identification (Step Tests and Identification Profile) are contrasted and found to provide comparable results, although the latter can provide advantages. The identified friction parameters are in turn used to perform four sets of control experiments; Two PID controllers (standard factory tuning and high performance PID with acceleration feedforward) are tested both with and without NIASA compensation. In the case study with a factory tuned PID controller, servo settling times to within ± 3 to ± 100 nm, are reduced by between 80.5% and 87.4% when NIASA compensation is added. When the NIASA compensator is added to the high performance PID controller, servo settling time is still reduced by between 50.5% and 73.0%. Although the NIASA compensator was designed to increase settling performance for relatively large point-to-point motions, similar positive results are achieved when the method is applied to smaller step motions that do not leave the pre-rolling friction regime. Frequency domain analyses demonstrated the nonlinear loop-gain of the plant, with a clear distinction between the rolling and pre-rolling friction cases. As expected, the nonlinear loop gain was found to lower the bandwidth for smaller motions. Adding NIASA control was observed to increase the bandwidth for small motions by a factor of 3-6, while having little effect on for large motions.
“…The implementation of this control law requires an observer for z , because this variable cannot be measured. As shown in Martínez-Rosas and Alvarez-Icaza (2008) and Martínez-Rosas et al (2009), this observer can be implemented together with the control law. The proposed design is simple as it takes advantage of the fact that z is bounded.…”
Section: Ida-pbc Of a Civil Structurementioning
confidence: 99%
“…This double pendulum is a two-link robotic arm. The application of dynamic friction models to this double pendulum was inspired by Martínez-Rosas and Alvarez-Icaza (2008), which shows the successful applications of a dynamic friction model to describe friction at the links of a three-degree-of-freedom robot. Figure 12.Under-actuated double pendulum.…”
Passivity-based control of under-actuated mechanical systems with nonlinear friction effects in the generalized coordinates of motion is analyzed in this paper. Nonlinear friction is modeled with a modified LuGre dynamic friction model. The internal states of the dynamic friction model are incorporated as generalized coordinates in a port-controlled Hamiltonian formulation for the complete mechanical system in such a way that all passivity properties of this formulation are preserved for the extended generalized coordinates system. Interconnection and damping assignment passivity-based control laws are developed for the models of two case studies: a building with a magneto-rheological damper and a double pendulum. Simulation results are also presented.
“…Differences between the modeled friction process and the true friction process can lead to undesirable system characteristics, such as, system instability and extended servo settling times [6]. Adaptive extensions to friction observers have been developed [6,13,14]. However, these efforts are not particularly concerned with the rate at which the model of the frictional process converges to the true process and June 20, 2012 DRAFT it appears that the methods take at least several seconds to converge (much longer than the settling process).…”
A nonlinear control algorithm is proposed that greatly reduces settling time in precision instruments with rolling element bearings. Reductions of 80.5-87.4% in settling time were achieved when settling to within 3-100 nm of the commanded position. Final settling of such systems is typically impacted by the nonlinearity in the pre-rolling friction regime, which manifests as a hysteretic stiffness. Consequently, the integral term in the controller can take a long time to respond. In this work, the Nonlinear Integral Action Settling Algorithm (NIASA) is presented. The nonlinear integral gain takes the form of a Dahl friction model. Since the integral gain mimics hysteretic stiffness, the output of the integral control term is instantaneously set to a large value after each direction change, greatly improving settling response. A nearly first order error dynamic results, which has a user-definable time constant. Before the algorithm can be implemented, the Coulomb friction and initial contact stiffness in the Dahl model must be experimentally determined for the stage. A sensitivity study was performed on the initial contact stiffness, which was found in other works to dictate stability of the algorithm [1, 2]. I. INTRODUCTION Rapid point-to-point motion of a servo mechanism has obvious industrial applications. In these systems, the objective is to move as quickly as possible from one location to the next with no concern for the particular motion profile used. Many such mechanisms contain rolling element bearings, given their low cost and generally good performance. As industrial processes Manuscript
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