Yun-Joon Lee
Korea Advanced Institute of Science and Technology · Computer Science
About the Lab
Professor Yun-Joon Lee's research lab specializes in advanced control systems and intelligent optimization techniques, with a strong focus on nuclear reactor power control and energy system dynamics. The lab integrates model predictive control, fuzzy logic, genetic algorithms, and system identification to develop robust, adaptive, and high-performance controllers for complex industrial systems. Research directions include intelligent control strategies for nuclear reactors, optimization of control parameters using hybrid metaheuristic algorithms, and the application of data-driven modeling techniques to improve system stability and efficiency. The lab also explores the integration of machine learning and control theory for real-time dynamic system management.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15A prominent parallel data processing tool MapReduce is gaining significant momentum from both industry and academia as the volume of data to analyze grows rapidly. While MapReduce is used in many areas where massive data analysis is required, there are still debates on its performance, efficiency per node, and simple abstraction. This survey intends to assist the database and open source communities in understanding various technical aspects of the MapReduce framework. In this survey, we charact
There have been several document ranking methods to calculate the conceptual distance or closeness between a Boolean query and a document. Though they provide good retrieval effectiveness in many cases, they do not support effective weighting schemes for queries and documents and also have several problems resulting from inappropriate evaluation of Boolean operators. We propose a new method called Knowledge‐Based Extended Boolean Model (kb‐ebm) in which Salton's extended Boolean model is incorpo
In this paper, a fuzzy model predictive control method is applied to design an automatic controller for thermal power control in pressurized water reactors. The future reactor power is predicted by using the fuzzy model identified by a subtractive clustering method of a fast and robust algorithm. The objectives of the proposed fuzzy model predictive controller are to minimize both the difference between the predicted reactor power and the desired one, and the variation of the control rod positio
The robust controller for the nuclear reactor power control system is designed. Since the reactor model is not exact, it is necessary to design the robust controller that can work in the real situations of perturbations. The reactor model is described in the form of transfer function and the bound of each coefficient is determined to set up the linear interval system. By the Kharitonov and the edge theorem, a frequency based design template is made and applied to the determination of the control
The reactor power control system is described in the fashion of the order increased LQR system. To obtain the optimal state feedback gain vectors, the weighting matrix of the performance function should be determined. Since the contentional method has some limitations, stochastic searching methods are investigated to optimize the LQR weighting matrix using the modified genetic algorithm combined with the simulated annealing, a new optimizing tool named the hybrid MGA-SA is developed to determine
The controller for the control of nuclear reactor power is designed. The reactor is modelled by using the three dimensional reactor design code of MASTER. From the relation of the input and output of the reactor code, the reactor dynamic model is derived by the system identification method. With this model, a controller is designed by the extended frequency response method. Since this method has the same theoretical background as the classical method, all the existing design techniques of the cl
The robust controller for the nuclear reactor power control system is designed. The nuclear reactor is modeled by use of the point kinetics equations and the singly lumped energy balance equations, Since the model is not exact, the controller which can make the actual system robust is necessary. The perturbed plant is investigated by employing the uncertainties of the initial power level and the physical properties, and by introducing the delay into the modeled plant The overall system is config
The steam generator feedwater and level control system is designed by two steps of the feedwater control design and the feedback loop controller design. The feedwater sen system is designed by the optimal LQR/LQG approach and then is modified by the LTR method to recover the robustness. The plant characteristics are subject to change with the power variation and these dynamic properties are considered in the design of the feedback controller. All the designs are made in the continuous domain and
The nuclear steam generator level control system is designed by robust control methods. The feedwater controller is designed by three methods of the H, the mixed weight sensitivity and the structured singular value. Then the controller located on the feedback loop of the level control system is designed. For the system performance, the controller of simple PID whose coefficients vary with the power is selected. The simulations show that the system has a good performance with proper stability mar
Research Areas
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