• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.316-321
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• 2003

This paper presents a design method of the wavelet neural network based controller using direct adaptive control method to deal with a stable intelligent control of chaotic systems. The various uncertainties, such as mechanical parametric variation, external disturbance, and unstructured uncertainty influence the control performance. However, the conventional control methods such as optimal control, adaptive control and robust control may not be feasible when an explicit, faithful mathematical model cannot be constructed. Therefore, an intelligent control system that is an on-line trained WNN controller based on direct adaptive control method with adaptive learning rates is proposed to control chaotic nonlinear systems whose mathematical models are not available. The adaptive learning rates are derived in the sense of discrete-type Lyapunov stability theorem, so that the convergence of the tracking error can be guaranteed in the closed-loop system. In the whole design process, the strict constrained conditions and prior knowledge of the controlled plant are not necessary due to the powerful learning ability of the proposed intelligent control system. The gradient-descent method is used for training a wavelet neural network controller of chaotic systems. Finally, the effectiveness and feasibility of the proposed control method is demonstrated with application to the chaotic systems.

• Current Photovoltaic Research
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• v.8 no.3
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• pp.86-93
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• 2020

The investment in solar and wind generation is rapidly increasing with government's renewable expansion policy and Renewable Portfolio Standard (RPS). Since the large penetration of solar and wind generation increases the variability and uncertainty of supply and demand balance in power system, the government is pursuing the policy of supplying energy storage system (ESS) linked to renewable energy. ESS contributes to the ease of transmission and distribution grid by shifting PV generation from daytime to evening hours. Recently, the declining market price of REC as ESS incentive, policies to cut down incentives and limited ESS storage due to fire events lead to the aggravation of long-term profitability, thus working as a barrier of ESS spreading. In this study, the factors affecting the profit of ESS are analyzed and brief indicators are derived. Based on the indicators, the profit changes are analyzed considering the variation of REC market price and REC incentive weights. Based on the profit change with respect to the increase of ESS capacity, economical ESS installation capacity is suggested.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.3
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• pp.419-426
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• 2018

An useful and effective design method for the gas identification system is presented in this paper. The proposed gas identification system adopts hierarchical structure with two level rule base combining fuzzy sets with rough sets. At first, a hybrid genetic algorithm is used in grouping the array sensors of which the measured patterns are similar in order to reduce the dimensionality of patterns to be analyzed and to make rule construction easy and simple. Next, for low level identification, fuzzy inference systems for each divided group are designed by using TSK fuzzy rule, which allow handling the drift and the uncertainty of sensor data effectively. Finally, rough set theory is applied to derive the identification rules at high level which reflect the identification characteristics of each divided group. Thus, the proposed method is able to accomplish effectively dimensionality reduction as well as accurate gas identification. In simulation, we demonstrated the effectiveness of the proposed methods by identifying five types of gases.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.356-362
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• 2017

This paper presents a robust position controller for a one degree-of-freedom (DOF) mechanical system using only position measurement. In order to alleviate the performance degradation owing to various uncertainties, a two-stage design method is studied by employing a proportional integral observer (PIO). In the first stage, a baseline backstepping controller is designed for a nominal system without accounting for uncertainties. The PIO is developed for estimating both the velocity information for the backstepping controller and an equivalent input disturbance for a feedforward compensation using the estimated uncertainty. It is shown that the estimation errors with the proposed PIO can be made arbitrarily small in a finite time. If the system suffers from undesirable actuator nonlinearities, however, it might be necessary to estimate the velocity and the disturbance with different rates of convergence. The proposed method combines the predesigned backstepping controller and dual PIOs to reduce mechanical vibrations as well as steady-state errors. The performance of the proposed method is tested through comparative computer simulations and experiments using a laboratory prototype.

• Smart Structures and Systems
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• v.22 no.5
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• pp.547-560
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• 2018

This paper investigates the operation of the $H_{\infty}$ static output-feedback controller to reduce dynamic responses under seismic excitation on the five-story and benchmark 20 story building with parametric uncertainties. Linear matrix inequality (LMI) control theory is applied in this system and then to achieve the desired LMI formulations, some transformations of the LMI variables is used. Conversely uncertainties due to material properties, environmental loads such as earthquake and wind hazards make the uncertain system. This problem and its effects are studied in this research. Also to decrease the transition of large amount of data between sensors and controller, avoiding the disruption of whole control system and economy problems, the operation of the decentralized controllers is investigated in this paper. For this purpose the comparison between the performance of the centralized, fully decentralized and partial decentralized controllers in uncoupled and coupled cases is performed. Also, the effect of the changing the number of stories in substructures is considered. Based on the numerical results, the used control algorithm is very robust against the parametric uncertainties and structural responses are decreased considerably in all the control cases but partial decentralized controller in coupled form gets the closest results to the centralized case. The results indicate the high applicability of the used control algorithm in the tall shear buildings to reduce the structural responses and its robustness against the uncertainties.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.657-659
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• 2004

CAN is a serial communication bus for real-time controls and automations in distributed control systems. In distributed control systems, occasionally a sensor module and a controller are not in the same node and physically separated. In order for the signal from a sensor node to reach the controller node, the signal must travel through network. CAN has a certain capabilities to deal with real-time data. However, when many nodes on the networks try to send data on the same network, the arbitration mechanism to solve the data collision problem is necessary. This situation causes the time delay which has detrimental effects on the performance of the control systems. This paper proposes a method to solve the problem due to the time delay in distributed control system using CAN. Time delay is approximated to an element with a rational transfer function using Pade approximation and Mu~synthesis method is applied. Since time delay in the network is not constant, the time delay element is considered to be an uncertainty block with a bound. The proposed method is applied to the experimental system with CAN and proved to be effective.

• International Journal of Aeronautical and Space Sciences
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• v.14 no.2
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• pp.172-182
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• 2013

This paper focuses on the modeling and intelligent control of the new Eight-Rotor MAV, which is used to solve the problem of the low coefficient proportion between lift and gravity for the Quadrotor MAV. The Eight-Rotor MAV is a nonlinear plant, so that it is difficult to obtain stable control, due to uncertainties. The purpose of this paper is to propose a robust, stable attitude control strategy for the Eight-Rotor MAV, to accommodate system uncertainties, variations, and external disturbances. First, an interval type-II fuzzy neural network is employed to approximate the nonlinearity function and uncertainty functions in the dynamic model of the Eight-Rotor MAV. Then, the parameters of the interval type-II fuzzy neural network and gain of sliding mode control can be tuned on-line by adaptive laws based on the Lyapunov synthesis approach, and the Lyapunov stability theorem has been used to testify the asymptotic stability of the closed-loop system. The validity of the proposed control method has been verified in the Eight-Rotor MAV through real-time experiments. The experimental results show that the performance of the interval type-II fuzzy neural network based adaptive sliding mode controller could guarantee the Eight-Rotor MAV control system good performances under uncertainties, variations, and external disturbances. This controller is significantly improved, compared with the conventional adaptive sliding mode controller, and the type-I fuzzy neural network based sliding mode controller.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.5
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• pp.1133-1138
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• 2012

In the paper, design of nonlinear sliding surfaces which are based on optimal control is studied, The state trajectory by the input of optimal control was obtained by Frobenius theorem and matrix decomposition method, was set the nonlinear sliding surfaces of the system. The states is maintained to sliding surfaces from initial states. As the result, robustness of the system can be guaranteed throughout an entire response of the system starting form the initial time instance, the uncertainty and external disturbance that can occur during the reaching time is removed, the problem of large control input was solved, and setting the sliding surfaces optimal path was able to reduce the tracking time. The validity of the proposed control scheme is shown in computer simulation for inverted pendulum.

• Journal of Power Electronics
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• v.16 no.4
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• pp.1578-1586
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• 2016

A power quality improvement scheme for grid connected inverters, even in the presence of the disturbances in grid voltages due to harmonic distortions and three-phase imbalance, is presented for distributed generation (DG) power systems. The control objective is to force the inverter currents to follow their references with robustness even under external disturbances in grid voltages. The proposed scheme is realized by a disturbance observer (DOB) based current control scheme. Since the uncertainty in a system can be effectively canceled out using an estimated disturbance by the DOB, the resultant system behaves like a closed-loop system consisting of a disturbance-free nominal model. For experimental verification, a 2 kVA laboratory prototype of a grid connected inverter has been built using a digital signal processor (DSP) TMS320F28335. Through comparative simulations and experimental results under grid disturbances such as harmonic distortion and imbalance, the effectiveness of the proposed DOB based current control scheme is demonstrated.

• 한국신재생에너지학회:학술대회논문집
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• 2011.05a
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• pp.195.2-195.2
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• 2011

The borehole heat exchanger of Geothermal Heat Pump (GHP) system should be sustainable and cost effective for long term operation. To guaranty the performance of the system thermal Response Tests (TRTs) with simple recommended procedures have been applied in many countries. Korea government developed a standard TRT procedure in order to control the quality on GHP projects. In the TRT procedure interpretation method has a rule that data set has to be interpreted by the line source model(LSM). The LSM employes some assumptions that surrounding medium is homogeneous and the line source is infinite and constant heat flux, however real ground condition is unisotropic and heterogeneous, and showing regional or local ground water flows in many cases. We need to develope improved evaluation models to estimate accurate ground thermal conductivity with respect to geological and influence of ground water because current TRT standard test procedure has limitations to be applied for every locations and system. This study surveyed the uncertainty of the thermal parameters from the interpretation method considering different evaluation period. The interpretation of 208 TRT data sets represents limitations of LSM application that some obtained ground thermal conductivities are statistically unstable and convergence time of ground thermal conductivity over test period shows trends responding the length of test period. This evaluation study will be helpful to provide some effective procedure for the thermal parameter estimation and to complement current TRT standard procedure.