• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.1
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• pp.145-152
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• 2016

The usage of LED(Light Emitting Diode) has been rapidly increased and energy efficient management of LED light system is regarded as an important technology to enhance the energy efficiency. In this paper, we design and implementation of LED lighting controller which can control the LED lighting by using the wire and wireless communication technology based on the LAN(Local Area Network) and PAN(Personal Area Network). The implemented system can reduce the cost of LED lighting installing and avoids complicated wiring problem. And it is possible to minimize power consumption through automatic or manual LED control that they wished. In experimental results, the implemented LED lighting controller was satisfactory for all of the desired functions.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.451-459
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• 2018

This work presents an approach for modeling of electric vehicle considering the vehicle dynamics, drive train, rotational wheel and load dynamics. The system is composed of IPMSM (Interior Permanent Magnet Synchronous Motor) coupled with the wheels through a drive train. Generally, IPMSM is controlled by ordinary PID controllers. Performance of the ordinary PID controller is not satisfactory owing to the difficulties of optimal gain selections. To overcome this problem, a new type of fuzzy logic gain tuner for PID controllers of IPMSM is required. Therefore, in this paper fuzzy logic based gain tuning method for PID controller is proposed and compared with some previous control techniques for the better performance of electric vehicle with an optimal balance of acceleration, speed, travelling range, improved controller quality and response. The model was developed in MATLAB/Simulink, simulations were carried out and results were observed. The simulation results have proved that the proposed control system works well to remove the transient oscillations and assure better system response in all conditions.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.2074-2079
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• 2018

Global state space's optimal policy is used for offline controller in the form of table by using Dynamic Programming. If an optimal policy table has a large amount of control data, it is difficult to use the system in a low capacity system. To resolve these problem, controller using the compressed optimal policy table is proposed in this paper. A DCT is used for compression method and the cosine function is used as a basis. The size of cosine function decreased as the frequency increased. In other words, an essential information which is used for restoration is concentrated in the low frequency band and a value of small size that belong to a high frequency band could be discarded by quantization because high frequency's information doesn't have a big effect on restoration. Therefore, memory could be largely reduced by removing the information. The compressed output is stored in memory of embedded system in offline and optimal control input which correspond to state of plant is computed by interpolation with Inverse DCT in online. To verify the performance of the proposed controller, computer simulation was accomplished with a one link inverted pendulum.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.4
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• pp.49-56
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• 2002

In this paper, a new controller using non-linear compensator for position control is presented, which we can satisfy the given specifications more easily than the existing one. We suggest an improved PDFE(Integral with Proportional-Derivative-plus-Feedforward) controller by which both phase margin and bandwidth are controlled simultaneously in the controller design problem. Replacing the feed forward term in the PDFF system with a CDIDF(Complex Dual Input Describing Function), the desired phase margin is obtained without diminishing the bandwidth of the closed loop system. The effectiveness of the proposed controller is confirmed through simulations and experiments. As The results of these, we know that it is possible to adjust overall specifications by varying parameters in the improved PDFF system.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.103-108
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• 2009

Robust control for DC motor is needed according to the highest precision of industrial automation. However, when a motor control system with PID controller has an effect of load disturbance, it is very difficult to guarantee the robustness of control system. In this paper, PID-Expert hybrid control method for motor control system as a compensation method solving this problem is presented. If PID control system is stable, the Expert controller is idle. if the error hits the boundary of the constraint, the Expert controller begins operation to force the error back to the constraint set. The disturbance effect decrease remarkably, robust speed control of DC motor using PID-Expert Hybrid controller is demonstrated by the simulation.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.5
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• pp.558-568
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• 2021

The existing underwater vehicle controller design is applied by linearizing the nonlinear dynamics model to a specific motion section. Since the linear controller has unstable control performance in a transient state, various studies have been conducted to overcome this problem. Recently, there have been studies to improve the control performance in the transient state by using reinforcement learning. Reinforcement learning can be largely divided into value-based reinforcement learning and policy-based reinforcement learning. In this paper, we propose the roll controller of underwater vehicle based on Deep Deterministic Policy Gradient(DDPG) that learns the control policy and can show stable control performance in various situations and environments. The performance of the proposed DDPG based roll controller was verified through simulation and compared with the existing PID and DQN with Normalized Advantage Functions based roll controllers.

• Nuclear Engineering and Technology
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• v.53 no.11
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• pp.3665-3674
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• 2021

One of the important parts of the in-core fuel management is loading pattern optimization (LPO). The loading pattern optimization as a reasonable design of the in-core fuel management can improve both economic and safe aspects of the nuclear reactor. This work proposes the hybrid of fuzzy logic controller with harmony search algorithm (HS) for loading pattern optimization in a pressurized water reactor. The music improvisation process to find a pleasing harmony is inspiring the harmony search algorithm. In this work, the adjustment of the harmony search algorithm parameters such as the bandwidth and the pitch adjustment rate are increasing performance of the proposed algorithm which is done through a fuzzy logic controller. Hence, membership functions and fuzzy rules are designed to improve the performance of the HS algorithm and achieve optimal results. The objective of the method is finding an optimum core arrangement according to safety and economic aspects such as reduction of power peaking factor (PPF) and increase of effective multiplication factor (Keff). The proposed approach effectiveness has been tried in two cases, Michalewicz's bivariate function problem and NEACRP LWR core. The results show that by using fuzzy harmony search algorithm the value of the fitness function is improved by 15.35%. Finally, with regard to the new solutions proposed in this research it could be used as a trustworthy method for other optimization issues of engineering field.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.73-78
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• 1999

This paper presents an effective construction method of adaptive multiple control systems utilizing some knowledge upon the plants. The adaptive multiple control system operates plants un-der widely changing environmental conditions. The adaptive multiple control system is composed of a family of candidate controllers together with a supervisor. The system does not require any identification schemes of environmental conditions. Monitoring outputs of the plant, the supervisor switches from one candidate controller to another, The basic ideas of adaptation are as follows: (1)each candidate controller is prepared for each environmental condition in advance; (2)the supervise. applies a sequence of speculative controls to the plant with candidate controllers just after the start of control or just after the detection of a change in the environmental condition. Each candidate controller can keep the system stable during one-step period of the speculative control and the most appropriate candidate controller for the environmental condition to which the system is exposed can be selected before the last trial of speculative control step comes to an end. We proposed a construction method of adaptive multiple control system without any knowledge of plant dynamics and applied the method to a cart-pole balancing problem and a vehicle anti skid braking system. In real applications, as we can often easily obtain a piece of knowledge upon plant dynamics beforehand, we intend to extend the method such that multiple control systems can be efficiently designed using the knowledge. We apply the new idea to the cart-pole balancing problem with variable length of the pole. The simulation experiments lead us to the conclusion that the new attempt can reduce the manpower to design the candidate controllers for adaptive multiple control systems.

• Nuclear Engineering and Technology
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• v.47 no.7
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• pp.838-848
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• 2015

One of the most important operations in nuclear power plants is load following, in which an imbalance of axial power distribution induces xenon oscillations. These oscillations must be maintained within acceptable limits otherwise the nuclear power plant could become unstable. Therefore, bounded xenon oscillation is considered to be a constraint for the load following operation. In this paper, the design of a sliding mode control (SMC), which is a robust nonlinear controller, is presented.SMCis ameansto control pressurized water nuclear reactor (PWR) power for the load following operation problem in a way that ensures xenon oscillations are kept bounded within acceptable limits. The proposed controller uses constant axial offset (AO) strategy to ensure xenon oscillations remain bounded. The constant AO is a robust state constraint for the load following problem. The reactor core is simulated based on the two-point nuclear reactor model with a three delayed neutron groups. The stability analysis is given by means of the Lyapunov approach, thus the control system is guaranteed to be stable within a large range. The employed method is easy to implement in practical applications and moreover, the SMC exhibits the desired dynamic properties during the entire output-tracking process independent of perturbations. Simulation results are presented to demonstrate the effectiveness of the proposed controller in terms of performance, robustness, and stability. Results show that the proposed controller for the load following operation is so effective that the xenon oscillations are kept bounded in the given region.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.612-618
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• 1998

The success of a fuzzy logic control system solving any given problem critically depends on the architecture of th network. Various attempts have been made in optimizing its structure its structure using genetic algorithm automated designs. In a regular genetic algorithm , a difficulty exists which lies in the encoding of the problem by highly fit gene combinations of a fixed-length. This paper presents a new approach to structurally optimized designs of a fuzzy model. We use a messy genetic algorithm, whose main characteristics is the variable length of chromosomes. A messy genetic algorithms used to obtain structurally optimized fuzzy models. Structural optimization is regarded important before neural network based learning is switched into. We have applied the method to the exampled of a cart-pole balancing.