• Journal of Power Electronics
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• v.8 no.3
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• pp.280-290
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• 2008

This paper deals with an investigation and evaluation of the performance of a state observer based Permanent Magnet Synchronous Motor (PMSM) drive controlled by PI (Proportional Integral), PID (Proportional Integral and Derivative), SMC (sliding mode control), ANN (Artificial neural network) and FLC (Fuzzy logic) speed controllers. A detailed study of the steady state and dynamic performance of estimated speed and angle is given to demonstrate the capability of the controllers.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.22 no.5
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• pp.275-281
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• 2010

Car HVAC is one of main factors influencing a potential customer's first impression. It should be fault-free, which requires the most stable control performance. So, the control algorithm consists of a proportional feedback only, not with an integral action needed for elimination of steady-state errors. To reduce the errors and make the response faster, feedforward algorithm based on predicted thermal load is added. To evaluate the performance, car HVAC is dynamically modelled and its control logic is simulated. The results shows that the proportional feedback leads to about $4^{\circ}C$ of steady-state error. When the feedback is combined with the feedforward algorithm and with a set value update based on disturbances, it predicts less than $1^{\circ}C$ of control error and improved thermal comfort.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.255-257
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• 1992

The expert system described in this article tunes a proportional-integral-derivative(PID) controller for a single-input single-ouput process. The expert system examines features of each transient response and the corresponding controller parameters. It determines a new set of controller gains to obtain a more desirable time reponse using fuzzy logic. This technique can be used to determine and implement a different set of PID gains for each operating regime and, once in steady state, the system can be used to find optimal parameters for load disturbance rejection.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.758-761
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• 1991

Using one chip microcontroller 87Cl96 (On chip EPROM type) and EPLD (Erasable & Programable Logic Device), an implantable control system to drive pendulum type electromechanical total artificial heart was developed. This control system consists of 4 parts, main management system, motor driver with power regulator, state monitoring system and communication part. The main system has the functions for speed detection, PI(proportional and integration) control, PWM generation, communication and analog data processor. Two kinds of power system were used and separated by 8 photo coupler arrays to improve the system stability. The performances of each compartments were compared with our previous z80 microprocessor based control system and good correspondences was shown. Logic power consumption was reduced to a one third of our previous controller. Using mock circulation tests, the overall performances of control system are evaluated.

• Proceedings of the SAREK Conference
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• 2009.06a
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• pp.161-166
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• 2009

Condensing gas boiler units may make a big role for the reduction of energy consumption in heating industries. In order to decrease the energy consumption of a boiler unit, the effective operation is necessary. In this study, the supply water temperature algorithm of a condensing gas boiler was developed. This includes the setpoint algorithm and the control algorithm of the supply water temperature. The setpoint algorithm was developed by the fuzzy logic and the control algorithm was developed by the proportional integral algorithm. In order to analyse the performance of the supply water temperature algorithm, the dynamic model of a condensing gas boiler system was used. Simulation results showed that the supply water temperature algorithm developed for this study may be practically applied for the control of the condensing gas boiler.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.5
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• pp.25-32
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• 1994

A nonlinear control algorithm for the depth control of underwater vehicles is presented. In order to consider the deadzone effect of the flow control valve, a nonlinear fuzzy logic controller (FLC) is synthesized and combined with a linear proportional-derivative-acceleration (PDA) controller, which is called the PDA/FLC controller. And to show the effectiveness of the PDA/FLC control system, it is compared with the linear PDA control system through computer simulation. It is found that the PDA/FLC control system is suitable one to maintain the desirable depth of underwater vehicles with deadzone.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.4
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• pp.8-15
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• 2013

Recently many kinds of electric vehicles have been developed as many governments demand the environmental friendly vehicles. In this paper, study of load optimization for the electric vehicle which has multiple axle power system was conducted. For the analysis of the vehicle which has three or four driving axles, a method based on the geometry and assumptions that considering axles as a spring model and normal forces of the axles are proportional to the displacement of the axles was applied with basic vehicle dynamics. With the developed vehicle analysis technique, algorithm to find the optimal motor operating points was developed. Using this algorithm, it was possible to find the optimization of vehicle load distribution for multiple axles according to the driving cycles. Also, control logic for the vehicle can be developed based on the optimization simulation results.

• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.2170-2178
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• 2015

This paper presents the effective and reliable speed control of PMDC motors under variable loads and reference speeds. As is known DC motors are more preferred in industrial practices. This is that, the PMDC motors don’t require brush and commutator care and to increase in torque per motor depending on developments in power electronics. In this study, proportional-integral controller (PI) and fuzzy logic controller (FL) have been designed for speed control of PMDC motor. In the design of these controllers, characteristics such as minimum overrun time, response time to the load, settling time and ideal rise time have been taken into consideration for better stability performance. In this design, the best system response was searched by examining the effect of different defuzzification methods onto the fuzzy logic system response. In conclusion, it has been seen that FL controller has a better performance for variable speed-load control of PMDC motor compared to PI controller.

• Journal of ILASS-Korea
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• v.24 no.4
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• pp.163-170
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• 2019

In this study, feedback logic using dual O₂ sensor values were developed to increase the purification capability of a three-way catalyst (TWC) in a compressed natural gas (CNG) engine. A heavy-duty inline 6-cylinder engine was used and the CNG was supplied to the engine through a mixer. This study consists of two main parts, namely, the proportional integral (PI) control with a front O₂ sensor and the feedback control with dual O₂ sensors. In the PI control experiment, effects of various parameters, such as P gain, I gain, and lean delay, on the TWC capability were identified. Based on the results of the PI control experiment, the feedback logic using dual O₂ sensor values were developed. In both cases, the nitrogen oxides (NO_X) emissions were nearly zero. However, the carbon monoxide (CO) emissions were reduced significant in the feedback logic with dual O₂ sensors than in the PI control with the front O₂ sensor.

• Journal of Power Electronics
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• v.11 no.4
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• pp.393-400
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• 2011

The main objective of this paper is to control the speed of Nonlinear Hybrid Electric Vehicle (HEV) by controlling the throttle position. Various control techniques such as well known Proportional-Integral-Derivative (PID) controller in conjunction with state feedback controller (SFC) such as Pole Placement Technique (PPT), Observer Based Controller (OBC) and Linear Quadratic Regulator (LQR) Controller are designed. Some Intelligent control techniques e.g. fuzzy logic PD, Fuzzy logic PI along with Adaptive Controller such as Self Organizing Controller (SOC) is also designed. The design objective in this research paper is to provide smooth throttle movement, zero steady-state speed error, and to maintain a Selected Vehicle (SV) speed. A comparative study is carried out in order to identify the superiority of optimal control technique so as to get improved fuel economy, reduced pollution, improved driving safety and reduced manufacturing costs.