A novel haptic model and environment for maxillofacial surgical operation planning and manipulation

This paper presents a practical method and a new haptic model to support manipulations of bones and their segments during the planning of a surgical operation in a virtual environment using a haptic interface. To perform an effective dental surgery it is important to have all the operation related information of the patient available beforehand in order to plan the operation and avoid any complications. A haptic interface with a virtual and accurate patient model to support the planning of bone cuts is therefore critical, useful and necessary for the surgeons. The system proposed uses DICOM images taken from a digital tomography scanner and creates a mesh model of the filtered skull, from which the jaw bone can be isolated for further use. A novel solution for cutting the bones has been developed and it uses the haptic tool to determine and define the bone-cutting plane in the bone, and this new approach creates three new meshes of the original model. Using this approach the computational power is optimized and a real time feedback can be achieved during all bone manipulations. During the movement of the mesh cutting, a novel friction profile is predefined in the haptical system to simulate the force feedback feel of different densities in the bone

Identification of the Servomechanism used for micro-displacement

Friction causes important errors in the control of small servomechanism and should be determined with precision in order to increase the system performance. This paper describes the method to identify the model parameters of a small linear drive with ball-screw. Two kinds of friction models will be applied for the servomechanism looking to rise its micropositioning abilities. The first one includes the static, viscous and Stribeck friction with hysteresis, and the second one uses the Lugre model. The results will be compared taking into account the criterion error, the accuracy and the normalized mean-square-error of the identified mechanical parameters. The coefficients of the models are identified by a recursive identification method using data acquisition and special filtering technics. The least square identification method is used in this paper in order to establish the motor parameters used as initial condition of the recursive estimation method. Computer simulations and experimental results demonstrate the efficiency of the proposed model

Five-Axis Machine Tool Condition Monitoring Using dSPACE Real-Time System

This paper presents the design, development and SIMULINK implementation of the lumped parameter model of C-axis drive from GEISS five-axis CNC machine tool. The simulated results compare well with the experimental data measured from the actual machine. Also the paper describes the steps for data acquisition using ControlDesk and hardware-in-the-loop implementation of the drive models in dSPACE real-time system. The main components of the HIL system are: the drive model simulation and input – output (I/O) modules for receiving the real controller outputs. The paper explains how the experimental data obtained from the data acquisition process using dSPACE real-time system can be used for the development of machine tool diagnosis and prognosis systems that facilitate the improvement of maintenance activities

Optimal control design for robust fuzzy friction compensation in a robot joint

This paper presents a methodology for the compensation of nonlinear friction in a robot joint structure based on a fuzzy local modeling technique. To enhance the tracking performance of the robot joint, a dynamic model is derived from the local physical properties of friction. The model is the basis of a precompensator taking into account the dynamics of the overall corrected system by means of a minor loop. The proposed structure does not claim to faithfully reproduce complex phenomena driven by friction. However, the linearity of the local models simplifies the design and implementation of the observer, and its estimation capabilities are improved by the nonlinear integral gain. The controller can then be robustly synthesized using linear matrix inequalities to cancel the effects of inexact friction compensation. Experimental tests conducted on a robot joint with a high level of friction demonstrate the effectiveness of the proposed fuzzy observer-based control strategy for tracking system trajectories when operating in zero-velocity regions and during motion reversals

A new method for the identification of the parameters of the Dahl model

Postprint (author's final draft

Linear motor motion control using a learning feedforward controller

The design and realization of an online learning motion controller for a linear motor is presented, and its usefulness is evaluated. The controller consists of two components: (1) a model-based feedback component, and (2) a learning feedforward component. The feedback component is designed on the basis of a simple second-order linear model, which is known to have structural errors. In the design, an emphasis is placed on robustness. The learning feedforward component is a neural-network-based controller, comprised of a one-hidden-layer structure with second-order B-spline basis functions. Simulations and experimental evaluations show that, with little effort, a high-performance motion system can be obtained with this approach

Full- and Reduced-order Model of Hydraulic Cylinder for Motion Control

This paper describes the full- and reduced-order models of an actuated hydraulic cylinder suitable for system dynamics analysis and motion control design. The full-order model incorporates the valve spool dynamics with combined dead-zone and saturation nonlinearities - inherent for the orifice flow. It includes the continuity equations of hydraulic circuits coupled with the dynamics of mechanical part of cylinder drive. The resulted model is the fifth-order and nonlinear in states. The reduced model neglects the fast valve spool dynamics, simplifies both the orifice and continuity equations through an aggregation, and considers the cylinder rod velocity as output of interest. The reduced model is second-order that facilitates studying the system behavior and allows for direct phase plane analysis. Dynamics properties are addressed in details, for both models, with focus on the frequency response, system damping, and state trajectories related to the load pressure and relative velocity.Comment: 6 pages, 6 figures, IEEE conferenc

Implementation of a friction estimation and compensation technique

This thesis reports implementation of a friction estimation and compensation technique on a special laboratory apparatus. In this work, experimental results are reported for the Coulomb friction observer. The Coulomb friction observer estimates the total friction present in a system, assuming it to be a constant function of velocity. An extension of the observer, utilizing a coupled velocity observer, is used when velocity is not measurable. A modification to the velocity observer is also implemented. Experimental results show a remarkable improvement in the friction estimates which are also compared to the actual friction measurements. The estimates are qualitatively similar to the actual friction, demonstrating the ability of the modified design to track a non-constant friction. Finally, extremely low velocities are experimentally obtained by using the friction compensation technique mentioned above, further proving that accurate control at low velocities is possible by friction estimation and compensation

Dynamic friction measurement, modeling, and compensation for precise motion control

In this thesis, measurements of dynamic friction in a hydrodynamic journal bearing were performed for varying sinusoidal velocity excitations, loads, and lubricants. The results indicate that the friction data displays a negative slope in the mixed region of friction vs. velocity (f-v) curves, and also shows that the dynamic friction is not just a function of current velocity, but also a function of velocity history (hysteresis). These results are in agreement with previous experimental investigations by other investigators in lubricated friction. Secondly, a dynamic friction model is fully explored and partially extended to provide quantitative agreement to measured friction values. A contribution to friction modeling was made by reducing the model from a fourth to a second order equation. Parameters were determined for one lubricant and two non-nal loads, and the model output is compared to experimental data. Finally, model-based friction compensation was successfully performed. The dynamic friction model is used as a basis for velocity and position control of an apparatus with high friction by incorporating a function to constantly learn two parameters of the model. Results demonstrate the feasibility of using a rich friction model in real time, and its ability to greatly reduce the tracking errors caused by friction. This thesis was supported by the National Science Foundation under Grant MSS9215636