• Journal of Korean Association for Spatial Structures
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• v.16 no.1
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• pp.43-51
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• 2016

A novel vibration control method for vibration reduction of a spacial structure subjected to earthquake excitation was proposed in this study. Generally, spatial structures have various vibration modes involving high-order modes and their natural frequencies are closely spaced. Therefore, in order to control these modes, a spatially distributed MTMDs (Multiple TMDs) method is proposed previously. MR (Magnetorheological) damper were used to enhance the control performance of the MTMDs. Accordingly, MSTMDs (Multiple Smart TMDs) were proposed in this study. An arch structure was used as an example structure because it has primary characteristics of spatial structures and it is a comparatively simple structure. MSTMDs were applied to the example arch structure and the seismic control performance were evaluated based on the numerical simulation. Fuzzy logic control algorithm (FLC) was used to generate command voltages sent for MSTMSs and the FLC was optimized by genetic algorithm. Based on the analytical results, it has been shown that the MSTMDs effectively decreased the dynamic responses of the arch structure subjected to earthquake loads.

• Journal of Korean Association for Spatial Structures
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• v.15 no.2
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• pp.105-112
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• 2015

A shared tuned mass damper (STMD) was proposed in previous research for reduction of dynamic responses of the adjacent buildings subjected to earthquake loads. A single STMD can provide similar control performance in comparison with two traditional TMDs. In previous research, a passive damper was used to connect the STMD with adjacent buildings. In this study, a smart magnetorheological (MR) damper was used instead of a passive damper to compose an adaptive smart STMD (ASTMD). Control performance of the ASTMD was investigated by numerical analyses. For this purpose, two 8-story buildings were used as example structures. Multi-input multi-output (MIMO) fuzzy logic controller (FLC) was used to control the command voltages sent to two MR dampers. The MIMO FLC was optimized by a multi-objective genetic algorithm. Numerical analyses showed that the ASTMD can effectively control dynamic responses of adjacent buildings subjected to earthquake excitations in comparison with a passive STMD.

• Journal of Korean Association for Spatial Structures
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• v.16 no.3
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• pp.79-88
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• 2016

An outrigger damper system has been proposed to reduce dynamic responses of tall buildings. In previous studies, an outrigger damper system was optimally designed to decrease a wind-induced or earthquake-induced dynamic response. When an outrigger damper system is optimally designed for wind excitation, its control performance for seismic excitation deteriorates. Therefore, a smart outrigger damper system is proposed in this study to make a control system that can simultaneously reduce both wind and seismic responses. A smart outrigger system is made up of MR (Magnetorheological) dampers. A fuzzy logic control algorithm (FLC) was used to generate command voltages sent for smart outrigger damper system and the FLC was optimized by genetic algorithm. This study shows that the smart outrigger system can provide good control performance for reduction of both wind and earthquake responses compared to the general outrigger system.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1374-1376
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• 1996

In this paper We proposed a new method to generate fuzzy logic controllers through genetic algorithm(GA). In designing of fuzzy logic controllers encounters difficulties in the selection of optimized member-ship functions, gains and rule base, which is conventionally achieved by a tedious trial-and-error process. This paper develops genetic algorithms for automatic design of high performance fuzzy logic controllers which can overcome nonlinearities in many engineering control applications. The rule-base is coded in base-7 strings by generated from random function. Which can be presented in discrete fuzzy linguistic value, and using membership function with Gaussian curve. To verify the validity of this fuzzy logic controller it is compared with conventional fuzzy logic controller(FLC) and PID controller.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.967-969
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• 1996

This paper presents fuzzy control rules for automatically driving a model car. The model car has a two sensors. This sensors measure a road outline and get a distance between a model car and a road outline. A Fuzzy Logic Controller(FLC) bases on a knowledge of the human experience. A FLC designed successfully controls the model car. Simulations results verifies the validity of proposed algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.12
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• pp.7277-7282
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• 2014

In this study, the gradient descent algorithm was used for FLC analysis and the algorithm was used to represent the effects of nonlinear parameters, which alter the antecedent and consequence fuzzy variables of FLC. The controller parameters choose the control variable by iteration for gradient descent algorithm. The FLC consists of 7 membership functions, 49 rules and a two inputs - one output system. The system adopted the Min-Max inference method and triangle type membership function with a 13 quantization level.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.499-502
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• 1996

In this paper, we propose a fuzzy iterative learning controller(FILC). It can control fully unknown dynamic plants through iterative learning. To design learning controllers based on the steepest descent method, it is one of the difficult problems to identify the change of plant output with respect to the change of control input(.part.e/.part.u). To solve this problem, we propose a method as follows: first, calculate .part.e/.part.u using a similarity measure and information in consecutive time steps, then adjust the fuzzy logic controller(FLC) using the sign of .part.e/.part..u. As learning process is iterated, the value of .part.e/.part.u is reinforced. Proposed FILC has the simple architecture compared with previous other controllers. Computer simulations for an inverted pendulum system were conducted to verify the performance of the proposed FILC.

• Journal of Electrical Engineering and Technology
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• v.6 no.1
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• pp.133-138
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• 2011

This paper proposes a simple but robust self-tuning fuzzy logic controller for the speed regulation of a dual star induction machine based on indirect field oriented control. For feed the two star of this machine, two voltage source inverters based on sinus-triangular pulse-width modulation techniques are introduced. The simulation results show the robustness and good performance of the proposed controller.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.1886-1900
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• 2018

This paper proposes a confronting feedback control structure and controllers for positive output elementary super lift Luo converters (POESLLCs) working in discontinuous conduction mode (DCM). The POESLLC offers the merits like high voltage transfer gain, good efficiency, and minimized coil current and capacitor voltage ripples. The POESLLC working in DCM holds the value of not having right half pole zero (RHPZ) in their control to output transfer function unlike continuous conduction mode (CCM). Also the DCM bestows superlative dynamic response, eliminates the reverse recovery troubles of diode and retains the stability. The proposed control structure involves two controllers respectively to control the voltage (outer) loop and the current (inner) loop to confront the time-varying ON/OFF characteristics of variable structured systems (VSSs) like POESLLC. This study involves two different combination of feedback controllers viz. the proportional integral controller (PIC) plus sliding mode controller (SMC) and the fuzzy logic controller (FLC) plus SMC. The state space averaging modeling of POESLLC in DCM is reviewed first, then design of PIC, FLC and SMC are detailed. The performance of developed controller combinations is studied at different working states of the POESLLC system by MATLAB-Simulink implementation. Further the experimental corroboration is done through implementation of the developed controllers in PIC 16F877A processor. The prototype uses IRF250 MOSFET, IR2110 driver and UF5408 diodes. The results reassured the proficiency of designed FLC plus SMC combination over its counterpart PIC plus SMC.

• The Journal of Korean Association of Computer Education
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• v.7 no.1
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• pp.67-77
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• 2004

In this paper, a new approach to the automation of the cultivation in a green house is suggested and a practical automatic control cultivation system is implemented. To automatically control and optimize the very nonlinear and time-varying growth of farm products, a hybrid strategy(FECA, Fuzzy Expertized Control Algorithm) is proposed which serially combines a fuzzy expert system with the fuzzy logic control. The fuzzy expert system(FMES, Fuzzy Model-based Expert System is intended to overcome the non-linearity of the growth of farm products. The part of fuzzy controller(FLC, Fuzzy Logic Controller) is incorporated to solve the time-variance of the growth of farm products. Finally, the efficiency and the effectiveness of the implemented agricultural automation system is presented through the cultivation results.