• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.2 s.314
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• pp.24-31
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• 2007

This paper presents self tuning PI(STPI) controller of IPMSM drive using neural network. In general, PI controller in computer numerically controlled machine process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness of fixed gain PI controller, STPI controller proposes a new method based neural network. STPI controller is developed to minimize overshoot, rise time and settling time following sudden parameter changes such as speed, load torque and inertia. Also, this paper is proposed speed control of IPMSM using neural network and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.2
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• pp.149-157
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• 2001

A nonlinear speed control for a permanent magnet synchronous motor (PMSM) using a simple disturbance estimation technique is presented. By using a feedback linearization scheme, the nonlinear motor model can be linearized in a controllable canonical form, and the desired speed dynamics can be obtained based on the linearized model. This technique, however, gives an undesirable output performance under the mismatch of the system parameters and load conditions. To cancel disturbance by parameter variation, the controller parameters will be estimated by using a disturbance observer theory where the disturbance torque and flux linkage are estimated. since only the two reduced order observers are used for the parameter estimations, the observer designs are considerably simple and the additional load for computation of the controller is negligibly small. The proposed control scheme is implemented on a PMSM using DSP TMS320C31 and the effectiveness is verified through the comparative simulations and experiments.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.6
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• pp.567-573
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• 2017

The drive shaft of passenger vehicle has an important role in transmitting the torque between the power train system and the wheels. Torsional fatigue failures occur generally in the connection parts of the spline edge of the drive shaft, when there is significant fatigue damage under repeated twisting loads. A heat treatment, an induction hardening process, has been adopted to increase the torsional strength as well as the fatigue life of the drive shaft. However, it is still unclear how the extension of the induction hardening process in a used material relates to its shear-strain fatigue life range. In this study, a shear-strain controlled torsional-fatigue test with a specially designed specimen was conducted by an electro-dynamic torsional fatigue test machine. A finite element analysis of the drive shaft was carried out using the results obtained by the fatigue experiment. The estimated fatigue life was verified through a twisting load test of the real drive shaft in a test rig.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.7
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• pp.65-73
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• 2006

This paper presents speed control of IPMSM drive using neural network(NN) PI controller. In general, PI controller in computer numerically controlled machine process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness of fixed gain PI controller, NNPI controller proposes a new method based neural network. NNPI controller is developed to minimize overshoot rise time and settling time following sudden parameter changes such as speed, load torque and inertia. Also, this paper is proposed speed control of IPMSM using neural network and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• The Journal of Korean Academy of Prosthodontics
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• v.44 no.4
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• pp.414-420
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• 2006

Purpose : The purpose of this study is to use finite element analysis to predict the fatigue life of an implant system subjected to fatigue load by mastication (chewing force). The reliability and the stability of implant system can be defined in terms of the fatigue strength. Not only an implant is expensive but also it is almost impossible to correct after it is inserted. From a bio-engineering standpoint, the fatigue strength of the dental implant system must be evaluated by simulation (FEA). Material and Methods Finite element analysis and fatigue test are performed to estimate the fatigue strength of the implant system. Mesh of implant is generated with the actual shape and size. In this paper, the fatigue strength of implant system is estimated. U-fit (T. Strong, Korea, internal type). The stress field in implant is calculated by elastic-plastic finite element analysis. The equivalent fatigue stress, considering the contact and preload stretching of a screw by torque for tightening an abutment, is obtained by means of Sine's method. To evaluate the reliability of the calculated fatigue strength, fatigue test is performed. Results: A comparison of the calculated fatigue strength with experimental data showed the validity and accuracy of the proposed method. The initiation points of the fatigue failure in the implant system exist in the region of high equivalent fatigue stress values. Conclusion: The above proposed method for fatigue life estimation tan be applied to other configurations of the differently designed and improved implant. In order to prove reliability of prototype implant, fatigue test should be executed. The proposed method is economical for the prediction of fatigue life because fatigue testing, which is time consuming and precision-dependent, is not required.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.3
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• pp.283-292
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• 2009

Considering an integral equation governing the motion of unfolding fin, an algebraic equation was acquired to get estimated minimum deployment energy required for the successful fin unfolding under the given wind condition. To complete the integration of moment, some approximations had to be introduced particularly to frictional moment and aerodynamic damping for which deployment angular speed of the unfolding fin was modelled as a function of deployment angle only with assumed profile using expected maximum angular speed. Technique for the estimation of the minimum required deployment energy was finalized by introducing the ideal deployment angular speed representing work done by the fin unfolding device alone during fin unfolding and was confirmed by comparing results from simulation with various aerodynamic conditions and profiles of the hinge torque.

• Journal of Power Electronics
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• v.19 no.5
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• pp.1224-1234
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• 2019

Hybrid rotor position estimation methods that integrate a fundamental model and high frequency (HF) signal injection are widely used for the wide speed-range sensorless control of interior permanent-magnet synchronous machines (IPMSMs). However, the direct transition of two different schemes may lead to system fluctuations or system instability since two estimated rotor positions based on two different schemes are always unequal due to the effects of parameter variations, system delays and inverter nonlinearities. In order to avoid these problems, a seamless transition strategy to define and construct a virtual q-axis inductance is proposed in this paper. With the proposed seamless transition strategy, an estimated rotor position based on a fundamental model is forced to track that based on HF signal injection before the transition by adjusting the constructed virtual q-axis inductance. Meanwhile, considering that the virtual q-axis inductance changes with rotor position estimation errors, a new observer with a two-phase phase-locked loop (TP-PLL) is developed to accurately obtain the virtual q-axis inductance online. Furthermore, IPMSM sensorless control with maximum torque per ampere (MTPA) operations can be tracked automatically by selecting the proper virtual q-axis inductance. Finally, experimental results obtained from an IPMSM demonstrate the feasibility of the proposed seamless transition strategy.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.10
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• pp.895-901
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• 2013

Last blades of LP turbine in nuclear power plant are the highly damaged part and suffered from nozzle steam impulses during the turbine operation. Nozzle impulse is known as a common cause of damage or failure in the turbine blade and results from steam flow distortions due to uneven steam flow patterns between the stationary blade vanes. If impulse force was continuously acting on the blade for a long time, crack or wear will occur in weak parts such as root. So, it is important to know variation of nozzle impulse during the blade moving. But there is no way to measure and estimate the magnitude and direction of nozzle impulse. Therefore, this study was performed to know the variation of nozzle impulse force according to the positions of the blade and to obtain blade equivalent force and torque. This results can be used for blade stress estimation.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.620-622
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• 2004

Mobility of an indoor wheeled robot is affected by adhesion force that is related to various floor conditions. When the adhesion force between driving wheels and the floor decreases suddenly, the robot has a slip state. In order to overcome this slip problem, optimal slip velocity must be decided for stable movement of wheeled robot. First of all, this paper shows that conventional PI control can not be applied to a wheeled robot of the light weigh. Secondly, reposed fuzzy logic applied by the Takagi-Sugeno model for the configuration of fuzzy sets. For the design of Takaki-Sugeno model and fuzzy rule, proposed algorithm uses FCM(Fuzzy c-mean clustering method) algorithm. In additionally, this algorithm controls recovered driving torque for the restrain the re-slip. The proposed fuzzy logic controller(FLC) is pretty useful with prevention of the slip phenomena through that compare fuzzy with PI control for the controller performance in the re-adhesion control strategy. These procedures are implemented using a Pioneer 2-DXE wheeled robot parameter.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.4
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• pp.755-760
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• 2013

The dynamics of the winder roller of a roll-to-roll printing system for printed electronics is a time-varying system because of the variation of the winder roller radius owing to rewinding or unwinding of the web. Therefore, an adaptive control method considering the time-variant characteristics is required for precise tension control. In this study, the variable PID gain method is applied to the actual roll-to-roll system and verified by experiments for unwinder tension control. The required value of the winder roller radius for the application of the variable PID gain is estimated from the measurement of the winder tension and winder motor torque. The simulation results as well as experimental results show that the fixed PID gain control cannot stabilize the tension of the winder roller with varying winder roller radius. On the other hand, the variable PID gain method can control the tension of the winder roller regardless of the winder roller radius.