• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.6
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• pp.577-582
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• 1999

Using a sole input variable simplifies the design process for the fuzzy logic controller(FLC). This is called single-input fuzzy logic controller(SFLC). However it is still deficient in the capability of adapting to the varying operating conditions. We here design a single-input adaptive fuzzy logic controller(AFLC) using a switching function of the sliding mode control. The AFLC can directly incorporate linguistic fuzzy control rules into the controller. Hence some parameters of the membership functions characterizing the linguistic terms of the fuzzy rules can be adjusted by an adaptive law. In the proposed AFLC center values of fuzzy sets are directly adjusted by a fuzzy logic system. We prove that 1) its closed-loop system is globally stable in the sense that all signals involved are bounded and 2)its tracking error converges to zero asymptotically. We perform computer simulation using a nonlinear plant.

• Journal of Korean Society for Quality Management
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• v.22 no.2
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• pp.20-32
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• 1994

This paper is concerned with the design of four control charts for real-time monitoring of the continuous flow processes. Control charts for both uncorrelated data and correlated data are designed using the Kalman filtering techinque. The relative performance between the designed control charts and traditional control charts is evaluated in terms of the Average Run Length(ARL). Results show that the Adaptive EWMA control charts designed for uncorrelated data has better performance when process mean is shifted, while the residual control charts for correlated data has better performance when process is in control.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.605-609
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• 1996

Continuous sliding mode control is applied to turning process for cutting force regulation. The highest feedrate compatible with the allowable cutting force is applied in rough cutting process such that maximum productivity is ensured and tool breakage is avoided. The programmed feedrate is overridden after the control algorithm is carried out. However, most CNC lathe manufacturers offer limited number of data bits far feedrate override, thus resulting in nonlinear behavior of the machine tools. Such nonlinearity brings “quantized” effect, and the optimal faedrate is rounded off before being fed into the CNC system. To compensate for this problem, continuous sliding mode control is applied. Conventional switching control law at a sliding surface is replaced by a smooth control interpolation in a selected boundary layer to avoid the excitation of high-frequency dynamics. Simulation results are presented in comparison with those obtained by applying adaptive control.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1293-1302
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• 1999

In this paper, an on-line process scheme is presented for implementation of a intelligent on-line modeling of nonlinear complex system. The proposed on-line process scheme is composed of FNN-based model algorithm and PLC-based simulator, Here, an adaptive fuzzy-neural networks and HCM(Hard C-Means) clustering method are used as an intelligent identification algorithm for on-line modeling. The adaptive fuzzy-neural networks consists of two distinct modifiable sturctures such as the premise and the consequence part. The parameters of two structures are adapted by a combined hybrid learning algorithm of gradient decent method and least square method. Also we design an interface S/W between PLC(Proguammable Logic Controller) and main PC computer, and construct a monitoring and control simulator for real process system. Accordingly the on-line identification algorithm and interface S/W are used to obtain the on-line FNN model structure and to accomplish the on-line modeling. And using some I/O data gathered partly in the field(plant), computer simulation is carried out to evaluate the performance of FNN model structure generated by the on-line identification algorithm. This simulation results show that the proposed technique can produce the optimal fuzzy model with higher accuracy and feasibility than other works achieved previously.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1132-1136
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• 2005

In this paper, adaptive equalizer receiver for a turbo code direct sequence code division multiple access (DSCDMA) by using least mean square (LMS) adaptive algorithm is presented. The proposed adaptive equalizer is using soft output of decision feedback adaptive equalizer (DFE) to examines the output of the equalizer and the Log- maximum a posteriori (Log-MAP) algorithm for the turbo decoding process of the system. The objective of the proposed equalizer is to minimize the bit error rate (BER) of the data due to the disturbances of noise and intersymbol interference (ISI)phenomenon on the channel of the DS-CDMA digital communication system. The computer program simulation results shown that the proposed soft output decision feedback adaptive equalizer provides a good BER than the others one such as conventional adaptive equalizer, infinite impulse response adaptive equalizer.

• Journal of Power Electronics
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• v.15 no.4
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• pp.1105-1118
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• 2015

Battery energy storage devices (ESDs) have become more and more commonplace to maintain the stability of islanded power systems. Considering the limitation in inverter capacity and the requirement of flexibility in the ESD, the droop control was implemented in paralleled ESDs for higher capacity and autonomous operation. Under the conventional droop control, state-of-charge (SoC) errors between paralleled ESDs is inevitable in the discharging operation. Thus, some ESDs cease operation earlier than expected. This paper proposes an adaptive accelerating parameter to improve the performance of the SoC error eliminating droop controller under the constraints of a microgrid. The SoC of a battery ESD is employed in the active power droop coefficient, which could eliminate the SoC error during the discharging process. In addition, to expedite the process of SoC error elimination, an adaptive accelerating parameter is dedicated to weaken the adverse effect of the constraints due to the requirement of the system running. Moreover, the stability and feasibility of the proposed control strategy are confirmed by small-signal analysis. The effectiveness of the control scheme is validated by simulation and experiment results.

• Journal of the Korea Convergence Society
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• v.5 no.4
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• pp.163-169
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• 2014

A stable neural network control scheme for unknown non-linear systems is developed in this paper. While the control variable is optimised to minimize the performance index, convergence of the index is guaranteed asymptotically stable by a Lyapnov control law. The optimization is achieved using a gradient descent searching algorithm and is consequently slow. A fast convergence algorithm using an adaptive learning rate is employed to speed up the convergence. Application of the stable control to a single input single output (SISO) non-linear system is simulated. The satisfactory control performance is obtained.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1016-1026
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• 2017

An adaptive extended Kalman filter based on the maximum likelihood (EKF-ML) is proposed for detecting voltage sag in this paper. Considering that the choice of the process and measurement error covariance matrices affects seriously the performance of the extended Kalman filter (EKF), the EKF-ML method uses the maximum likelihood method to adaptively optimize the error covariance matrices and the initial conditions. This can ensure that the EKF has better accuracy and faster convergence for estimating the voltage amplitude (states). Moreover, without more complexity, the EKF-ML algorithm is almost as simple as the conventional EKF, but it has better anti-disturbance performance and more accuracy in detection of the voltage sag. More importantly, the EKF-ML algorithm is capable of accurately estimating the noise parameters and is robust against various noise levels. Simulation results show that the proposed method performs with a fast dynamic and tracking response, when voltage signals contain harmonics or a pulse and are jointly embedded in an unknown measurement noise.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.766-771
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• 1997

In this strip casting,size of the roll separating force is a index representing the solidifying status of the melt. Rolling forces at the start of the casting process can change abruptly due to the overcooling of the leader strip. This inconsistensy leads to machine damage or deficient solidification which results in the failure of the casting. In this study, a mathematical model is derived for the hydraulic servo pressure control system for the twin roll strip caster and its parameters are estimated by the RLS algorithm. Based on the identified model, an one-step ahead predictive control method is applied in order to minimize the transient fluctuation of the rolling force. Its simulation results are compared with those of the conventional PI controllers.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.724-729
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• 2001

This paper discusses the composition of the theory of reinforcement learning, which is applied in real-time learning, and evolutionary strategy, which proves its the superiority in the finding of the optimal solution at the off-line learning method. The individuals are reduced in order to learn the evolutionary strategy in real-time, and new method that guarantee the convergence of evolutionary mutations are proposed. It possible to control the control object varied as time changes. As the state value of the control object is generated, applied evolutionary strategy each sampling time because the learning process of an estimation, selection, mutation in real-time. These algorithms can be applied, the people who do not have knowledge about the technical tuning of dynamic systems could design the controller or problems in which the characteristics of the system dynamics are slightly varied as time changes. In the future, studies are needed on the proof of the theory through experiments and the characteristic considerations of the robustness against the outside disturbances.