TY - Generic T1 - Transparency extension in haptic interfaces via adaptive dynamics cancellation T2 - American Society of Mechanical Engineers, Dynamic Systems and Control Division (Publication) DSC Y1 - 2005 A1 - McJunkin, Samuel A1 - Speich, John E. A1 - O'Malley, M.K. KW - Adaptive control systems KW - Computer simulation KW - Linear systems KW - Manipulators KW - Mathematical models KW - Transfer functions AB -

Haptic interfaces are a class of robotic manipulators that display force feedback to enhance the realism of virtual environment displays. However, these manipulators often fail to effectively replicate the real world environment due to dynamic limitations of the manipulator itself. The ratio of the simulated to transmitted environment impedance is defined as the transparency transfer function (TTF), and can be used to quantify the effectiveness of a haptic device in displaying the simulated environment. The TTF is ideally equal to one for the bandwidth of human proprioception. In this work, a method is presented that increases TTF bandwidth via cancellation of dynamics with an adaptive model. This adaptive model is based on the kinematics and dynamics of a PHANToM haptic interface with assumed joint stiffness and damping added. The Lagrangian of the PHANToM is reformulated into a regressor matrix containing the state variables multiplied by a parameter vector. A least-squares approach is used to estimate the parameter vector by assuming that errors in force output are due to the manipulator dynamics. The parameter estimate is then used in the original model to provide a feed-forward cancellation of the manipulator dynamics. Software simulation using data from passive user interactions shows that the model cancellation technique improves bandwidth up to 35 Hz versus 7 Hz without compensation. Finally, this method has a distinct advantage when compared with other compensation methodsfor haptic interactions because it does not rely on linear assumptions near a particular operating point and will adapt to capture unmodeled features. Copyright © 2005 by ASME.

JF - American Society of Mechanical Engineers, Dynamic Systems and Control Division (Publication) DSC CY - Orlando, FL, United States VL - 74 DSC N1 -

Transparency extension;Robotic manipulators;Transparency transfer function (TTF);Model cancellation techniques;

ER - TY - Generic T1 - Virtual lab for system identification of an electromechanical system T2 - American Society of Mechanical Engineers, Dynamic Systems and Control Division (Publication) DSC Y1 - 2005 A1 - O'Malley, M.K. A1 - David M. McStravick KW - Computer software KW - Data acquisition KW - Mathematical models KW - Mechanical engineering KW - Real time systems KW - Students AB -

A stand-alone virtual instrument (vi) has been developed to augment an experimental system identification laboratory exercise in a required mechanical engineering course on system dynamics. The Virtual Lab (VL) was used productively as a post-lab exercise in conjunction with an existing laboratory experiment for system identification. The VL can be formatted as a standalone file, which the students can download and access at their convenience, without the need for LabVIEW software. The virtual lab presented in this paper used the experimental identification of a transfer function for an xy recorder developed at Rose-Hulman Institute of Technology. In the original Rose-Hulman experiment, students view a video of the acquisition of frequency response data for an X-Y recorder. Then, students complete a detailed optimization procedure using Microsoft Excel in order to determine system parameters for two transfer function models. This paper describes using the Virtual Lab to extend the original lab exercise into an interactive mode. The students complete the Microsoft Excel part of the exercise, but then repeat the optimization using brute force via the LabVIEW based VL developed by the authors, rather than using the optimization toolbox in Excel. With the VL, students can see in real-time the effects of each unknown parameter on the frequency response plot, thus providing additional insight into the relationships between these parameters and the behavior of the electromechanical system. This feature is notably absent in the Microsoft Excel portion of the exercise. Although this exercise uses simple dynamic models, the combination of Excel and LabVIEW approaches provide an insightful introduction to experimental system identification. In this paper, details of the VL are presented, including the functionality of the VL and methodologies for disseminating the VL as a stand-alone piece of software. Finally some assessment results for the original (Excel version) and VL methods of presenting the laboratory exercise are discussed. Copyright © 2005 by ASME.

JF - American Society of Mechanical Engineers, Dynamic Systems and Control Division (Publication) DSC CY - Orlando, FL, United States VL - 74 DSC N1 -

Virtual instrument (vi);Identification laboratory;Virtual Lab (VL);

ER -