• Journal of Institute of Control, Robotics and Systems
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• v.3 no.6
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• pp.555-562
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• 1997

With only the classical PID controller applied to control of a DC motor, good (target) performance characteristic of the controller can be obtained if all the model parameters of DC motor and operating conditions such as external load torque, disturbance, etc. are known exactly. However, in case when some of system parameters or operating conditions are uncertain or unknown, the fixed PID controller does not guarantee good performance, which is assumed with precisely known system parameters and operating conditions. In view of this and the robustness enhancement of DC motor control system, we propose a PID learning controller which consists of a set of learning rules for PID gain tuning and learning of an auxiliary input. The proposed PID learning controller is shown to drive the state of uncertain DC motor system with unknown system parameters and external load torque to the desired one world wide asymptotically. Computer simulation and experimental results are given to demonstrate the effectiveness of the proposed PID learning controller, thereby showing its superiority to the conventional fixed PID controller.

• The Transactions of the Korean Institute of Power Electronics
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• v.11 no.4
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• pp.349-360
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• 2006

Controller for doubly-fed induction-type wind generation system should be designed with mechanical power on blade. The controller in this paper consists of upper level controller and lower level controller. The upper level controller determines operating modes according to mechanical input power and calculates proper reference values. There are 4 operating modes - minimum speed control, variable torque control, torque limit control and idle mode. The lower level controller performs current regulated PWM control of rotor-side converter and grid-side inverter. A wind turbine simulator is implemented using doubly-fed induction-type generator and DSP based back-to-back converter to verify the performance of designed controller experimentally.

• Proceedings of the KIEE Conference
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• 1995.07a
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• pp.334-336
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• 1995

An adaptive feedback linearization technique of a PM synchronous motor with specified output dynamic performance is proposed. The adaptive parameter estimation is achieved by a model reference adaptive technique where the stator resistance and flux linkage can be estimated with the current dynamic model and the state observer. Using these estimated parameters, the linearizing control inputs are calculated and a nonlinear coupled model of a PM synchronous motor is input-output linearized. The resultant model has the load torque disturbance. To get ti perfect decoupled model, the load torque is estimated. The adaptation laws are derived by the hyperstability theory and positivity concept. The robustness of the proposed control scheme will be proven through the computer simulations.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.26 no.6_spc
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• pp.660-666
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• 2016

This paper presents performance comparison results of magneto-rheological (MR) brake in the sense of wear characteristics. To create wear circumstance, the brake is operated in 100 000 cycles by DC motor. To make wear test in same design parameters such as the radius of the housing, ferromagnetic disc and gap size, small sample of stainless are inserted in housing of MR brake. The performances of brake are compared between the initial stage (no wear) and 100 000 revolution cycles operated stage (wear). At each circumstance, torque of the brake is measured and compared by applying step current and sinusoidal control input. The controller used in this work is a simple, but effective PID controller. It is demonstrated that the wear behavior is more obvious as the operating cycle is increased in the torque control process.

• Journal of Magnetics
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• v.16 no.1
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• pp.74-76
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• 2011

Interior permanent-magnet synchronous motors (IPMSMs) produce both magnetic and reluctance torques. The reluctance torque is due to the difference between the d- and q-axis inductances based on the geometric rotor structure. The steady-state performance analysis and precise control of the IPMSMs greatly depend on the accurate determination of the parameters. The three essential parameters of the IPMSMs are the armature flux linkage of the permanent magnet, the d-axis inductance, and the q-axis inductance. In the basic design step of an IPMSM, the inductance parameters are very important for determining the motor characteristics, such as the input voltage, torque, and efficiency. Thus, it is very important to accurately estimate the values of the motor inductances. The inductance parameters of IPMSMs have nonlinear characteristics along the magnet size because the iron core is saturated by the magnet and armature reaction fluxes. In this study, the inductance parameters were calculated using both the magnetic-equivalent-circuit method and the finite-element method (FEM). Then the calculated parameters were compensated by the saturation coefficient function, which was also calculated via the magnetic-equivalent-circuit method and FEM.

• Journal of Magnetics
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• v.16 no.1
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• pp.71-73
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• 2011

Hybrid electric vehicles have attracted much attention of late, emphasizing the necessity of developing traction motors with a high input current and a wide speed range. Among such traction motors, various researches have been conducted on interior permanent-magnet synchronous motors (IPMSMs) with high power density and mechanical solidity. Due to the complexity of its parameters, however, with nonlinear motor characteristics and current vector control, it is actually difficult to accurately estimate the base speed within an actual operating speed range or a voltage limit. Moreover, it is impossible to construct an efficiency map as the efficiency differs according to the control mode. In this study, a simulation method for operation performance considering the nonlinearity of IPMSM was proposed. For this, datasets of various nonlinear parameters were made via the finite-element method and interpolation. Maximum torque-per-ampere and flux-weakening control were accurately simulated using the datasets, and an IPMSM efficiency map was accurately constructed based on the simulation. Lastly, the validity of the simulation was verified through tests.

• Journal of the Korean Society of Marine Environment & Safety
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• v.17 no.1
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• pp.83-88
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• 2011

There are various environmental conditions under which ship may navigate over ocean or in harbor. Ship's torque and speed change frequently under the voyage conditions. In this case, harmonics is created in the electrical power systems. The major adverse impacts of voltage and current harmonics in the electrical power systems on generator, transformer, converter, inverter and propulsion motor lead to the increase of machine heating caused by iron and copper losses which are dependent on frequency. In this paper, an analysis of THD(total harmonic distortion) for currents and voltages in the propulsion equipment was carried out. The THD and torque ripple in the input currents of the propulsion motor have been confirmed by the simulation results.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1202-1211
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• 2018

In this paper, induction machine operation efficiency and torque is improved using Machine Learning based Gene Optimization (ML-GO) Technique is introduced. Optimized Genetic Algorithm (OGA) is used to select the optimal induction machine data. In OGA, selection, crossover and mutation process is carried out to find the optimal electrical machine data for induction machine design. Initially, many number of induction machine data are given as input for OGA. Then, fitness value is calculated for all induction machine data to find whether the criterion is satisfied or not through fitness function (i.e., objective function such as starting to full load torque ratio, rotor current, power factor and maximum flux density of stator and rotor teeth). When the criterion is not satisfied, annealed selection approach in OGA is used to move the selection criteria from exploration to exploitation to attain the optimal solution (i.e., efficient machine data). After the selection process, two point crossovers is carried out to select two crossover points within a chromosomes (i.e., design variables) and then swaps two parent's chromosomes for producing two new offspring. Finally, Adaptive Levy Mutation is used in OGA to select any value in random manner and gets mutated to obtain the optimal value. This process gets iterated till finding the optimal value for induction machine design. Experimental evaluation of ML-GO technique is carried out with performance metrics such as torque, rotor current, induction machine operation efficiency and rotor power factor compared to the state-of-the-art works.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.6
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• pp.802-808
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• 2019

DC motors are used extensively on shipboard, including as the ship's winch operating motor, owing to their simple speed control and excellent output torque characteristics. Moreover, they were used as propulsion motors in the early days of electric propulsion ships. However, mechanical rectifiers, such as brushes, used in DC motors have certain disadvantages. Hence, brushless DC (BLDC) motors are increasingly being used instead. While the electrical characteristics of both types of motors are similar, BLDC motors employ electronic rectifying devices, which use semiconductor elements, instead of mechanical rectifying devices. The inverter system for driving conventional BLDC motors uses a two-phase excitation method so that the waveform of the back electromotive force becomes trapezoidal. This causes harmonics and torque ripple in the phase current switching period in which the winding wire through which the current flows is changed. Researchers have studied and presented various methods to reduce the harmonics and torque ripple. This study applies a cascaded H-bridge multilevel inverter, which implements a proportional-integral speed current controller algorithm in the driving circuit of the BLDC motor for electric propulsion ships using a power analysis program. The simulation results of the modeled BLDC motor show that the driving method of the proposed BLDC motor improves the voltage waveform of the input side of the motor and remarkably reduces the harmonics and torque ripple compared with the conventional driving method.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.1
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• pp.80-85
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• 2011

This paper presents the design of the power-assisted controller for the in-wheel type smart wheelchair by using torque estimation that is predicted by relationship between input voltage and output wheel angular velocity. Nowadays, interest of the moving assistant aids is increased according to the increase in population of the elderly and the handicapped person. However some of the moving assistant aids have problems. For example, manual wheelchair has difficulty moving at the slope, because users lack the muscular strength of their arm. In electric wheelchair case, users should be weak by being decreased muscles of upper body. To overcome these problems, power-assisted electric wheelchair are proposed. Most of the power-assisted electric wheelchair have the special rims that can measure the user's power. In here, the rims have to be designed to install the sensors to measure user's power. In this paper, we don't design the rim to measure the man power. To predict the man power, we propose a control algorithm of the in-wheeled electric wheelchair by using torque estimation from the wheel. First, we measure the wheel velocity and voltage at the in-wheel electric wheelchair. And then we extract driving will forces by using proposed mathematical model. Also they are applied at the controller as the control input, we verify to be able to control in-wheel type smart wheelchair by using simulation.