• Journal of Power Electronics
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• v.18 no.3
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• pp.736-745
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• 2018

This paper presents an extended state observer (ESO) based direct torque control (DTC) for use in induction motor systems to handle the issues of time delays, load torque disturbances and parameter uncertainties. Direct torque control offers an excellent torque response and it does not require a proportion integration (PI) controller in the current loop. However, a PI controller is still adopted in the outer speed loop to generate the torque reference value, which is a slow method. An ESO based compound control scheme is proposed to improve the response rate and accuracy of the torque reference signal, especially when load torque is injected. In addition, the time delay problem is analyzed and compensated for in this paper to reduce torque ripples. The proposed disturbance compensation technique based direct control scheme is shown to have good performance both in the transient and stable states via simulations and experimental results.

• Journal of Dental Rehabilitation and Applied Science
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• v.26 no.4
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• pp.419-432
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• 2010

Various torque generating devices have been developed and employed to apply a proper torque. These devices are usually calibrated by the manufacturer to apply appropriate torque levels for their specific implants and attachments. The purpose of this investigation was to determine and compare the accuracy of the torque controllers. In this study, 4 types of torque controllers were used; torque limiting device(TLD), torque indicating device(TID) and contra angle torque driver(CA), electronic torque controller(ETC). Digital torque gauge was employed to measure the de-torque value. Thirty cycles of tightening and loosening were repeated with each torque controller. All implant torque controllers have shown slight errors and deviations. The contra angle torque driver exhibited the most accurate data. In the limitation of this study, it would be recommended that the implant torque controllers should be checked whether uniformed and precise torque can be generated and a measuring error should be corrected.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.4
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• pp.104-109
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• 1997

A robust controller design to corrdinate a robot manipulator under unknown system parameters and bounded disturbance inputs is presented in this paper. Generally, robust controllers require high input torque so that they may face input saturation in actual application due to the power limitation of the actuator. To solve this problem, an improved robust controller with saturated input torque using a fuzzy logic control is proposed. Numerical examples are shown to validate the proposed controller using two degree-of-freedom planar arm.

• The Journal of Korean Academy of Prosthodontics
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• v.49 no.3
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• pp.197-205
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• 2011

Purpose: This study was to evaluate the accuracy of the implant torque controller used in dental clinics and to investigate whether it was applied appropriately. Materials and methods: Fifty dentists who work in dental clinics were enrolled in this study. Dental (implant) practice career, experience frequency of implant screw loosening and fracture, education of implant torque controller application and infection control methods were included in the survey. 25 Ncm and 30 Ncm of the tightening torque applied to the implant screw were measured by 50 clinicians. After measuring the torque value by using the torque controller, the torque mean according to where education about the implant torque controller was received was analyzed with independent t-test at the significance level of 0.05. Results: The torque controller used in private dental clinics showed 4.78% error ratio. When 50 dentists applied 25 Ncm to the implant screw was $29.0{\pm}8.4$ Ncm, and that in 30 Ncm was $34.3{\pm}9.1$ Ncm. Statistical significance was found between the group that was educated about implant torque application and the group that was not educated. Conclusion: During the prosthodontic treatment with implant, there was difference between actual applied torsion force and the amount torque controller indicated. Clinicians have to not only be well-informed about the accurate usage method of the torque controller, but also keep and manage the torque controller so as to maintain continuous and accurate torque values. Through this, it is considered to achieve clinical results to minimize problems of screw loosening or fracture.

• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.725-728
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• 2000

This paper presents the switching angle and voltage for maximizing torque of 4-phase 6-poles SRM. The switching angle and voltages was determined through the approximated analysis and computer simulation by using SIMULINK according to the speed and torque required by load but we used new analytic equation from maximum torque characteristic And then one-chp micro-controller controls the switching angle and voltage of an asymmetrical inverter in the SRM driver. Also we expects that this method reduce micro-controller load and realize approximated real time control

• The Transactions of the Korean Institute of Power Electronics
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• v.9 no.6
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• pp.612-619
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• 2004

Servo motor systems with ball-screw and timing-belt are widely used in NC, robot, FA and industrial applications. However, the nonlinear friction torque and damping effect in machine elements reduce the control performance. Especially tracking errors in trajectory control and very low velocity control range are serious due to the break-away friction and Stribeck effects. In this paper, a new double speed controller is proposed for compensation of the nonlinear friction torque. The proposed double speed controller has outer speed controller and inner friction torque compensator. The proposed friction torque compensator compensates the nonlinear friction torque with actual speed and speed error information. Due to the actual information for friction torque compensator without parameters and mathematical model of motor, proposed compensator is very simple structure and the stability is very high. The proposed compensator is verified by simulation and experimental results.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.8
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• pp.33-39
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• 2005

The maximum output torque and power developed by the machine is ultimately depended on the allowable inverter current rating and maximum voltage which the inverter can supply to the machine. Therefore, considering the limited voltage and current capacities, it is desirable to consider a control method which yields the best possible torque per ampere. In this paper, we propose fuzzy neural network(FNN) controller that combines a fuzzy control and the neural network for high performance control of induction motor drive. This controller composes antecedence of the fuzzy rules and consequence by a clustering method and a multi-layer neural networks. This controller is compounding of advantages that robust control of a fuzzy control and high-adaptive control of the neural networks. Also, this paper is proposed control of maximum torque per ampere(MTPA) of induction moor. This strategy is reposed which is simple in structure and has the honest goal of minimizing the stator current magnitude for given load torque. The performance of the proposed induction motor drive with maximum torque control using FNN controller is verified by analysis results at dynamic operation conditions.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.10
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• pp.1751-1756
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• 2007

This paper presents a high performance pressure control scheme for SR(Switched Reluctance) type hydraulic oil pump using DITC(Direct Instantaneous Torque Control). SR drive has a good feature for pump applications due to a high efficiency, high speed and high torque characteristics. But, SR drive has high torque ripple in commutation region. So, the pump pressure variation is high in the region. In order to reduce the pressure variation, DITC combined with pressure control scheme is presented in this paper. A simple PI controller with flow and pressure limit, generates a reference torque to keep the constant actual pump pressure. The direct torque controller of SR drive generates inverter switching signals according to a control rule and a torque estimator. Computer simulation and experiemtal results show the validation of the proposed control scheme.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.10
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• pp.1384-1392
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• 2014

This paper presents a torque ripple reduction algorithm for the switched reluctance motor drives using the fuzzy logic and the sliding mode control. A turn-on angle controller based on the fuzzy logic determines the optimal turn-on angle. In addition, a sliding mode torque control (SMTC) methods reduces torque ripples instantaneously in the commutation region. The proposed algorithm does not require complex system models considering nonlinear magnetizing or demagnetizing periods of the phase current. According to the rotor speed and torque, the proposed controller changes the turn-on angle and reference torque instantaneously until the torque ripples are minimized. The simulation and experimental results verify the validity of minimizing the torque ripple performance.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.91-99
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• 2003

When the driver suddenly depresses the brake pedal under critical conditions, the desired trajectory of the vehicle can be changed. In this study, the vehicle dynamics and fuzzy logic controller are used to control the vehicle trajectory. The dynamic vehicle model consists of the engine, the rotational wheel, chassis, tires and brakes. The engine model is derived from the engine experimental data. The engine torque makes the wheel rotate and generates the angular velocity and acceleration of the wheel. The dynamic equation of the vehicle model is derived from the top-view vehicle model using Newton's second law. The Pacejka tire model formulated from the experimental data is used. The fuzzy logic controller is developed to compensate for the trajectory error of the vehicle. This fuzzy logic controller individually acts on the front right, front left, rear right and rear left brakes and regulates each brake torque. The fuzzy logic controlling each brake works to compensate for the trajectory error on the split - $\mu$ road conditions follows the desired trajectory.