• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.3
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• pp.468-477
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• 1994

Existing fuzzy control methods do not perform well when applied to systems containing nonlinearities arising from unkonwn deadzones. In particular, we show that a conventional fuzzy logic controller applied to a system with a deadzone suffers from poor transient performance and a large steady-syate error. In this paper, we propose a novel two-layered fuzzy logic controller for controlling systems with deadzones. The two-layered control structure consists of a fuzzy logic-based precompensator followed by a conventional fuzzy logic controller. Our proposed controller exhibits superior transient and steady-state performance compared to conventional fuzzy controllers. In addition, the controller is robust to variations in deadzone nonlinearities. We illustrate the effectiveness of our scheme using computer simulation examples.

• Journal of the Korean Institute of Navigation
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• v.20 no.1
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• pp.87-96
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• 1996

In this paper, The Fuzzy Logic Controller based on T-operators is designed. Some typical T-operators and their mathematical properties are studied. A generalized fuzzy inference model is proposed by introducing the general notion of T-operators into the conventional one which is based only on the Min and Max operators. Fuzzy Logic Control algorithms based on the T-operators are suggested. Then, by computer simulations, the effect of various T-operators on the performance of the fuzzy logic controller are studied. The purpose of these simulation studies were to observe the flexibility and system responses using the processed class of T-operators in the fuzzy inference mechanisms. This observation was made on parameters such as speed of reponses, steady-state behavior and non oscillatory responses.

• Structural Engineering and Mechanics
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• v.41 no.3
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• pp.349-363
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• 2012

Fuzzy logic based control has recently been proposed for regulating the properties of magnetorheological (MR) dampers in an effort to reduce vibrations of structures subjected to seismic excitations. So far, most studies showing the effectiveness of these algorithms have focused on the use of a single MR damper. Because multiple dampers would be needed in practical applications, this study aims to evaluate the effects of multiple individually tuned fuzzy-controlled MR dampers in reducing responses of a multi-degree-of-freedom structure subjected to seismic motions. Two different fuzzy-control algorithms are considered, a traditional controller where all parameters are kept constant, and a gain-scheduling control strategy. Different damper placement configurations are also considered, as are different numbers of MR dampers. To determine the robustness of the fuzzy controllers developed to changes in ground excitation, the structure selected is subjected to different earthquake records. Responses analyzed include peak and root mean square displacements, accelerations, and interstory drifts. Results obtained with the fuzzy-based control schemes are compared to passive control strategies.

• Proceedings of the KIPE Conference
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• 2008.06a
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• pp.127-129
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• 2008

This paper describes a method of approximate reasoning for fuzzy control of servo system, based on decomposition of -level fuzzy sets. It is propose that logic circuits for fuzzy PI+PD are a body from fuzzy inference to defuzzificaion in cases where the output variable u directly is generated PWM. The effectiveness for robust and faster response of the fuzzy control scheme is verified for a variable parameter by comparison with a PID control and fuzzy control. A position control of DC servo system with a fuzzy logic controller successfully demonstrated.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.897-900
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• 1998

Through fuzzy logic controller is very useful to many areas, it is difficult to build up the rule-base by experience and trial-error. So, effective self-tuning fuzzy controller for the position control of ball and beam is designed. In this paper, we developed the neural network control system with fuzzy-neuron which conducts the adjustment process for the parameters to satisfy have nonlinear property of the ball and beam system. The proposed algorithm is based on a fuzzy logic control system using a neural network learinign algorithm which is a back-propagation algorithm. This system learn membership functions with input variables. The purpose of the design is to control the position of the ball along the track by manipulating the angualr position of the serve. As a result, it is concluded that the neural network control system with fuzzy-neuron is more effective than the conventional fuzzy system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.44-49
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• 2001

For minimum phase systems, the conventional fuzzy logic controllers (FLCs) use the error and the change-of-error as fuzzy input variables. Then the control rule table is a skew symmetric type, that is, it has UNLP (Upper Negative and Lower Positive) or UPLN property. This property allowed to design a single-input FLC (SFLC) that has many advantages. But its control parameters are not automatically adjusted to the situation of the controlled plant. That is, the adaptability is still deficient. We here design a single-input direct adaptive FLC (SDAFLC). In the AFLC, some parameters of the membership functions characterizing the linguistic terms of the fuzzy rules are adjusted by an adaptive law. The SDAFLC is designed by a stable error dynamics. We prove that its closed-loop system is globally stable in the sense that all signals involved are bounded and its tracking error converges to zero asymptotically. We perform computer simulations using a nonlinear plant and compare the control performance between the SFLC and the SDAFLC.

• Journal of Korean Society of Transportation
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• v.21 no.3
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• pp.71-83
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• 2003

An arterial street control is performed for the purpose of the progression of a traffic flow using the arterial. However during the progression in the arterial, the change according to the time is one of the most representative problems occurring at a signal plan. This paper intends to efficiently operate the arterial progression by applying fuzzy logic, which is thought to be the most possible one in the inference as that of the human logic, to the traffic responsive control system. Fuzzy Logic controller is appliable to the daily human language (linguistic). can be dealt with the uncertain traffic data and is useful on planning the signal control to sensitively confront the randomly changing traffic condition. This study, based on the signal control part of the isolated intersection in "A Development of a Real-time, Traffic Adaptive Control Scheme Through VIDs"(Seong Ho. Kim. 1996). suggested the strategy for the progression control in the arterial and analyzed its effect by comparing the effect of the existing control method. In addition, the study compared each effect by using TRAF-NETSIM which is the traffic simulation software to analyze each control method.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1483-1486
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• 2002

In this paper, a new scheme of iterative loaming control of a robot manipulator is presented. The proposed method uses a fuzzy sliding mode controller(FSMC), which is designed based on the similarity between the fuzzy logic control(FLC) and the sliding mode control(SMC), for the feedback. With this, the proposed method makes possible fDr fast iteration and has advantages that no linear approximation is used for the derivation of the learning law or in the stability proof Full proof of the convergence of the fuzzy sliding base learning scheme Is given.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.11a
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• pp.85-90
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• 1996

In this paper, the self-organizing fuzzy logic controller is developed for water level control of steam generator. In comparison with conventional fuzzy logic controllers, this controller performs control task with no control rules at initial and creates control rules as control behavior goes on, and also modifies its control structure when uncertain disturbance is suspected. Selected parameters in the fuzzy logic controller are updated on-line by the gradient descent loaming algorithm based on the performance cost function. This control algorithm is applied to water level control of steam generator model developed by Lee, et al. The computer simulation results confirm good performance of this control algorithm in all power ranges. This control algorithm can be expected to be used for automatic control of feedwater control system in the nuclear power plant with digital instrumentation and control systems.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.845-847
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• 2015

A suspending force control based on fuzzy logic control is proposed to apply on a novel hybrid bearingless switched reluctance motor(BLSRM) which has separated torque and suspending force pole. Due to the unique structure, the suspending force control system can be easily decoupled from torque control system. In this paper, two fuzzy controller targeted at x-axis direction and y-axis direction are adopted to maintain the shaft at center position, which is very necessary for stable operation of BLSRM. By replacing the traditional PI block with modified fuzzy logic controller, the suspending system can behave a good performance, and the proposed scheme can be verified by simulation results.