In this study the authors develop haptic systems for telerobotic surgery. In order to model the full range of tactile force exhibited from an MR damper a microstructural, kinetic theory-based model of Magnetorheological (MR) fluids has been developed. Microscale constitutive equations relating flow, stress, and particle orientation are produced. The model developed is fully vectorial and relationships between the stress tensor and the applied magnetic field vector are fully exploited. The higher accuracy of the model in this regard gives better force representations of highly compliant objects. This model is then applied in force feedback control of single degree of freedom (SDOF) and two degrees of freedom (2DOF) systems. Carbonyl iron powders with different particle sizes mixed with silicone oils with different viscosities are used to make several sample MR fluids. These MR fluid samples are then used in three different designed MR dampers. A State feedback control algorithm is employed to control a SDOF system and tracking a 2-D profile path using a special innovative MR force feedback joystick. The results indicate that the MR based force feedback dampers can be used as effective haptic devices. The systems designed and constructed in this paper can be extended to a three degree of freedom force feedback system appropriate for telerobotic surgery.
Characteristic phenomenological behavior of MR fluids is typically modeled by Bingham’s equation, which has no fundamental connection to the microstructure of MR fluid and the fully coupled mechanical-electrical-magnetic equations. In this paper microstructurally, kinetic theory-based model of MR fluids (consisting of micro-sized ferrous particles suspended in a Newtonian fluid) are developed. For modeling these composite systems, dumbbell models in which two beads joined by an elastic connector are investigated. In these models the distributed forces from the carrier fluid and from the magnetic field on the suspended particle are idealized as being localized on beads. Microscale constitutive equations relating flow, stress, and particle orientation are produced by integrating the coupled equations governing forces, flow, and orientation over a representative volume of particles and carrier fluid. Coefficients in the constitutive equations are specified not by a fit to macroscale experimental flow measurement but rather in terms of primitive measurements of particle microstructure, carrier fluid, viscosity and density, and temperature. These new models for MR fluids are three dimensional and applicable to any flow geometry, while the Bingham plastic model is in general applicable only to shear flow. The models in this paper reduce to forms similar to Bingham’s model in a simple shear flow, but with coefficients which arise from fundamental electromagnetic considerations and microstructural features such as geometrical, magnetic and mechanical characterization of the particles, quantities measured primitively from the carrier fluid, magnetic field and temperature.
In this study, the authors develop haptic systems for telerobotic surgery exploiting MR fluids for semiactive force feedback. To investigate the full range of tactile force exhibited by a particular MR damper design, a microstructural 3D kinetic theory-based model of MR fluids has been developed. In this model, microscale constitutive equations relate flow, stress, and particle orientation. The higher accuracy of the model in this regard gives better force representations of highly compliant objects. In this article, the model is utilized in forcefeedback control of both a SDOF system and a 2DOF system. A state-feedback control algorithm is employed to track both the SDOF system, and the 2DOF system using specially designed MR force-feedback joysticks. The results demonstrate that the MR fluid-based forcefeedback joysticks can be used effectively as haptic devices. It is also observed that both SDOF and 2DOF systems are nearly transparent in replicating the stiffness of different external objects, due to the light weight of the semiactive system and controller implementation.
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