• Journal of Broadcast Engineering
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• v.27 no.2
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• pp.244-247
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• 2022

In this paper, the performance of the decoding schemes using linear MMSE filters in the frequency and time domains and the reinforcement Gauss-Seidel algorithm for the orthogonal time frequency space (OTFS) system that can improve robustness under high-speed mobile environments are compared. The reinforcement Gauss-Seidel algorithm can improve the bit error rate performance by suppressing the noise enhancement. The simulation results show that the performance of the decoding scheme using the linear MMSE filter in the frequency domain is severely degraded due to the effect of Doppler shift as the mobile speed increases. In addition, the decoding scheme using the reinforcement Gauss-Seidel algorithm under the channel environment with 120 km/h and 500 km/h speeds outperforms the decoding schemes using linear MMSE filters in the frequency and time domains.

• Nuclear Engineering and Technology
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• v.17 no.4
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• pp.247-255
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• 1985

This paper describes a new method for the design of variable structure model-following control systems(VSMFC). This design concept is developed using the theory of variable structure systems (VSS) and slide mode. The new results are presented on the sliding control methodology to achieve accurate tracking for a class of nonlinear, multi-input multi-output(MIMO), time varying systems in the presence of parameter variations. The design requires little computational effort. The dynamic response is insensitive to parameter variations. The feasibility and the advantages of the method are illustrated by applying it to a 1000 MWe boiling water reactor(BWR). The control is studied in the range of 85%∼90% of rated power for load-following control. A set of 12 nonlinear differential equations is used to simulate the total plant. A 6-th order linear model has been developed from these equations at 85% of rated power. The obtained controller is shown by simulations to be able to compensate for a plant parameter variation over a wide power range.

• Journal of Korea Water Resources Association
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• v.48 no.12
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• pp.1051-1064
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• 2015

Currently, the H purification plant determines the hourly water intake amount based on operator experience and skill. Therefore, inevitably, there are deviations among operators. While meeting time-varying demand and maintaining the proper water level in the clean water reservoir, the methodology for minimizing electricity cost, when dealing with different electricity rate time zones, is a very complicated problem, which is beyond an operator's capability. To solve this problem, a linear programming (LP) model is proposed, which can determine the optimal hourly water intake amount for minimizing the daily electricity cost. It is shown that an inaccurate estimate for the hourly water usage in the demand areas causes the water level constraint to be violated, which is the weak point of the proposed LP method. However, several examples with real-field data show that we can practically and safely solve this problem with safety margins. It is also shown that the safety margin method still works effectively whether the estimate is accurate or not. The operators need not attend the site at all times under the proposed LP method, and we can additionally expect reductions in labor costs.

• Smart Structures and Systems
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• v.21 no.3
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• pp.257-262
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• 2018

Vibrational problems in the domestic Small Horizontal Axis Wind Turbines (SHAWT) are due to flap wise vibrations caused by varying wind velocities acting perpendicular to its blade surface. It has been reported that monitoring the structural health of the turbine blades requires special attention as they are key elements of a wind power generation, and account for 15-20% of the total turbine cost. If this vibration problem is taken care, the SHAWT can be made as commercial success. In this work, Shape Memory Alloy (SMA) wires made of Nitinol (Ni-Ti) alloys are embedded into the Glass Fibre Reinforced Polymer (GFRP) wind turbine blade in order to reduce the flapwise vibrations. Experimental study of Nitinol (Ni-Ti) wire characteristics has been done and relationship between different parameters like current, displacement, time and temperature has been established. When the wind turbine blades are subjected to varying wind velocity, flapwise vibration occurs which has to be controlled continuously, otherwise the blade will be damaged due to the resonance. Therefore, in order to control these flapwise vibrations actively, a non-linear current controller unit was developed and fabricated, which provides actuation force required for active vibration control in smart blade. Experimental analysis was performed on conventional GFRP and smart blade, depicted a 20% increase in natural frequency and 20% reduction in amplitude of vibration. With addition of active vibration control unit, the smart blade showed 61% reduction in amplitude of vibration.

• Earthquakes and Structures
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• v.4 no.1
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• pp.109-132
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• 2013

Current codes incorporate simplified methods for the prediction of acceleration demands on secondary structural and non-structural elements at different levels of a building. While the use of simple analysis methods should be advocated, damage to both secondary structural and non-structural elements in recent earthquakes have highlighted the need for improved design procedures for such elements. In order to take a step towards the formation of accurate but simplified methods of predicting floor spectra, this work examines the floor spectra on elastic and inelastic single-degree of freedom systems subject to accelerograms of varying seismic intensity. After identifying the factors that appear to affect the shape and intensity of acceleration demands on secondary structural and non-structural elements, a new series of calibrated equations are proposed to predict floor spectra on single degree of freedom supporting structures. The approach uses concepts of dynamics and inelasticity to define the shape and intensity of the floor spectra at different levels of damping. The results of non-linear time-history analyses of a series of single-degree of freedom supporting structures indicate that the new methodology is very promising. Future research will aim to extend the methodology to multi-degree of freedom supporting structures and run additional verification studies.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.2
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• pp.36-42
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• 2021

This paper deals with a vehicle routing problem with resource repositioning (VRPRR) which is a variation of well-known vehicle routing problem with pickup and delivery (VRPPD). VRPRR in which static repositioning of public bikes is a representative case, can be defined as a multi-objective optimization problem aiming at minimizing both transportation cost and the amount of unmet demand. To obtain Pareto sets for the problem, famous multi-objective optimization algorithms such as Strength Pareto Evolutionary Algorithm 2 (SPEA2) can be applied. In addition, a linear combination of two objective functions with weights can be exploited to generate Pareto sets. By varying weight values in the combined single objective function, a set of solutions is created. Experiments accomplished with a standard benchmark problem sets show that Variable Neighborhood Search (VNS) applied to solve a number of single objective function outperforms SPEA2. All generated solutions from SPEA2 are completely dominated by a set of VNS solutions. It seems that local optimization technique inherent in VNS makes it possible to generate near optimal solutions for the single objective function. Also, it shows that trade-off between the number of solutions in Pareto set and the computation time should be considered to obtain good solutions effectively in case of linearly combined single objective function.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3498-3511
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• 2016

We investigate the channel state information (CSI) in multi-input multi-output (MIMO) cooperative networks that employ the amplify-and-forward transmission scheme. Least squares and expectation conditional maximization have been proposed in the system. However, neither of these two approaches takes advantage of channel sparsity, and they cause estimation performance loss. Unlike linear channel estimation methods, several compressed channel estimation methods are proposed in this study to exploit the sparsity of the MIMO cooperative channels based on the theory of compressed sensing. First, the channel estimation problem is formulated as a compressed sensing problem by using sparse decomposition theory. Second, the lower bound is derived for the estimation, and the MIMO relay channel is reconstructed via compressive sampling matching pursuit algorithms. Finally, based on this model, we propose a novel algorithm so called sparsity adaptive expectation maximization (SAEM) by using Kalman filter and expectation maximization algorithm so that it can exploit channel sparsity alternatively and also track the true support set of time-varying channel. Kalman filter is used to provide soft information of transmitted signals to the EM-based algorithm. Various numerical simulation results indicate that the proposed sparse channel estimation technique outperforms the previous estimation schemes.

• Journal of Integrative Natural Science
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• v.15 no.3
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• pp.99-110
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• 2022

Solar photovoltaic (PV) system shows a non-linear current (I) -voltage (V) characteristics, which depends on the surrounding environment factors, such as irradiance, temperature, and the wind. Solar PV system, with current (I) - voltage (V) and power (P) - Voltage (V) characteristics, specifies a unique operating point at where the possible maximum power point (MPP) is delivered. At the MPP, the PV array operates at maximum power efficiency. In order to continuously harvest maximum power at any point of time from solar PV modules, a good MPPT algorithms need to be employed. Currently, due to its simplicity and easy implementation, Perturb and Observe (P&O) algorithms are the most commonly used MPPT control method in the PV systems but it has a drawback at suddenly varying environment situations, due to constant step size. In this paper, to overcome the difficulties of the fast changing environment and suddenly changing the power of PV array due to constant step size in the P&O algorithm, least mean Square (LMS) methods is proposed together with P&O MPPT algorithm which is superior to traditional P&O MPPT. PV output power is predicted using LMS method to improve the tracking speed and deduce the possibility of misjudgment of increasing and decreasing the PV output. Simulation results shows that the proposed MPPT technique can track the MPP accurately as well as its dynamic response is very fast in response to the change of environmental parameters in comparison with the conventional P&O MPPT algorithm, and improves system performance.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2617-2622
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• 2003

The pH neutralization process has long been taken as a representative benchmark problem of nonlinear chemical process control due to its nonlinearity and time-varying nature. For general nonlinear processes, it is difficult to control with a linear model-based control method so nonlinear controls must be considered. Among the numerous approaches suggested, the most rigorous approach is the dynamic optimization. However, as the size of the problem grows, the dynamic programming approach is suffered from the curse of dimensionality. In order to avoid this problem, the Neuro-Dynamic Programming (NDP) approach was proposed by Bertsekas and Tsitsiklis (1996). The NDP approach is to utilize all the data collected to generate an approximation of optimal cost-to-go function which was used to find the optimal input movement in real time control. The approximation could be any type of function such as polynomials, neural networks and etc. In this study, an algorithm using NDP approach was applied to a pH neutralization process to investigate the feasibility of the NDP algorithm and to deepen the understanding of the basic characteristics of this algorithm. As the global approximator, the neural network which requires training and k-nearest neighbor method which requires querying instead of training are investigated. The global approximator requires optimal control strategy. If the optimal control strategy is not available, suboptimal control strategy can be used even though the laborious Bellman iterations are necessary. For pH neutralization process it is rather easy to devise an optimal control strategy. Thus, we used an optimal control strategy and did not perform the Bellman iteration. Also, the effects of constraints on control moves are studied. From the simulations, the NDP method outperforms the conventional PID control.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.1
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• pp.7-14
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• 2015

To implement an automatic picking system (APS) in distribution center with high precision and high dynamics, this paper presents a high gain observer-based robust speed controller design for a linear induction motor (LIM) drive. The force disturbance as well as the mechanical parameter variations such as the mass and friction coefficient gives a direct influence on the speed control performance of APS. To guarantee a robust control performance, the system uncertainty caused by the force disturbance and mechanical parameter variations is estimated through a high gain disturbance observer and compensated by a feedforward manner. While a time-varying disturbance due to the mass variation can not be effectively compensated by using the conventional disturbance observer, the proposed scheme shows a robust performance in the presence of such uncertainty. A Simulink library has been developed for the LIM model from the state equation. Through comparative simulations based on Matlab - Simulink, it is proved that the proposed scheme has a robust control nature and is most suitable for APS.