“…However the application of such models has been mainly restricted to off-line simulation and actuator design and rarely has been used for control purposes. Preisach [19], Prandtl-Ishlinskii [20], and Krasnoselskii-Pokrovskii [21] models are among the second category of modeling methods. These models are mainly successful in predicting magnetic hysteresis.…”
Section: Comparison With Conventional Rheological Actuatorsmentioning
confidence: 99%
“…These models are mainly successful in predicting magnetic hysteresis. However, implementation problems associated with such methods limit their use in closed-loop controllers [19]. The implementation of non-model based controllers for MRF-based system have also been reported in the literature [22].…”
Section: Comparison With Conventional Rheological Actuatorsmentioning
confidence: 99%
“…To this end, several efforts were made by our group to develop an efficient model-based control scheme. A novel nonlinear adaptive observer that relates the internal magnetic field to the applied current was introduced in [19]. This model facilitates accurate control of the actuator using its input current.…”
Section: Comparison With Conventional Rheological Actuatorsmentioning
In our previous work [1], the potential benefits of Magneto-Rheological Fluid based actuators to the field of haptics were studied. Our results showed that the superior mechanical attributes of such actuators contribute to improvement of stability and transparency in haptic devices. To this end, a novel design of a small-scale MRF-based clutch, was proposed in [1]. This paper reports on the development and validation of the proposed MRF-based clutch. In addition, a closed-loop torque control strategy is presented. The feedback signal used in this control scheme comes from the magnetic field measurement and is used to compensate for the nonlinear behavior using an estimated model, based on Artificial Neural Networks (ANNs). Such a control strategy eliminates the need for torque sensors for providing feedback signals. The performance of the developed design and the effectiveness of the proposed modeling and control techniques are experimentally validated. The results clearly demonstrate that the clutch shows great potential for use in a multiple degrees-of-freedom (DOF) haptic interface for a class of medical applications.The authors are with the
“…However the application of such models has been mainly restricted to off-line simulation and actuator design and rarely has been used for control purposes. Preisach [19], Prandtl-Ishlinskii [20], and Krasnoselskii-Pokrovskii [21] models are among the second category of modeling methods. These models are mainly successful in predicting magnetic hysteresis.…”
Section: Comparison With Conventional Rheological Actuatorsmentioning
confidence: 99%
“…These models are mainly successful in predicting magnetic hysteresis. However, implementation problems associated with such methods limit their use in closed-loop controllers [19]. The implementation of non-model based controllers for MRF-based system have also been reported in the literature [22].…”
Section: Comparison With Conventional Rheological Actuatorsmentioning
confidence: 99%
“…To this end, several efforts were made by our group to develop an efficient model-based control scheme. A novel nonlinear adaptive observer that relates the internal magnetic field to the applied current was introduced in [19]. This model facilitates accurate control of the actuator using its input current.…”
Section: Comparison With Conventional Rheological Actuatorsmentioning
In our previous work [1], the potential benefits of Magneto-Rheological Fluid based actuators to the field of haptics were studied. Our results showed that the superior mechanical attributes of such actuators contribute to improvement of stability and transparency in haptic devices. To this end, a novel design of a small-scale MRF-based clutch, was proposed in [1]. This paper reports on the development and validation of the proposed MRF-based clutch. In addition, a closed-loop torque control strategy is presented. The feedback signal used in this control scheme comes from the magnetic field measurement and is used to compensate for the nonlinear behavior using an estimated model, based on Artificial Neural Networks (ANNs). Such a control strategy eliminates the need for torque sensors for providing feedback signals. The performance of the developed design and the effectiveness of the proposed modeling and control techniques are experimentally validated. The results clearly demonstrate that the clutch shows great potential for use in a multiple degrees-of-freedom (DOF) haptic interface for a class of medical applications.The authors are with the
“…Although certain types of helical-motion motors have been developed over the years [13][14][15][16][17], many areas require further research. For example, modeling coupling effects is a significant challenge as it requires a solution considering the two degrees of mechanical freedom in the motion.…”
-The two-degree-of-freedom direct drive induction motor, which is capable of linear, rotary and helical motion, has a wide application in special industry such as industrial robot arms. It is inevitable that the linear motion and rotary motion generate coupling effect on each other on account of the high integration. The analysis of this effect has great significance in the research of two-degreeof-freedom motors, which is also crucial to realize precision control of them. The coupling factor considering the coupling effect is proposed and addressed by 3D finite element method. Then the corrected mathematical model is presented by importing the coupling factor. The results from it are verified by 3D finite element model and prototype test, which validates the corrected mathematical model.
“…The study of this subject has led to the study of new control and actuation mechanisms for robots. It has been shown that new actuation technologies are essential components of the future generations of human-safe robots [1]- [4].…”
In this paper, a new open-loop model for a magnetorheological-based actuator is presented. The model consists of two parts relating the output torque of the actuator to its internal magnetic field, and the internal magnetic field to the applied current. Each part possesses its own hysteretic behavior. The first part uses a novel nonlinear adaptive model that relates the internal magnetic field to the applied current. The second part uses an open-loop Bingham model to relate the output torque to an internal magnetic field. The model facilitates accurate control of the actuator using its input current. It also eliminates the need for force/torque sensors for providing feedback signals. The accuracy of the constructed model is validated through simulations. The model is assessed against a widely accepted hysteresis modeling approach, known as the Preisach model and its advantages are highlighted. Experimental results using the prototyped actuation mechanism further verify the accuracy of the model and demonstrate its effectiveness.Index Terms-Adaptive modeling, hysteresis, magnetorheological fluids (MRFs), smart actuators.
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