• Journal of the Earthquake Engineering Society of Korea
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• v.9 no.6 s.46
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• pp.75-90
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• 2005

This paper proposes semi-active fuzzy control technique of magneto-rheological dampers for seismic response control of cable-stayed bridges. Through the fuzzy inference process, the proposed technique performs the semi-active control with the responses of MR dampers only. Moreover, differently from the conventional semi-active control technique, this technique does not require additional active controller for the primary controller, which provides a simple design process. in order to validate the control performance of the proposed technique, the semi-active fuzzy control technique is applied to the benchmark control problem of cable-stayed bridge and its control performance is compared with those of conventional semi-active control techniques. The comparative results show that the proposed fuzzy control technique can be an effective control strategy by efficiently and simultaneously reducing the mutual conflicting responses such as the shear forces and moments at the base of the lowers, longitudinal displacement of the deck, and tensions in the stay cables.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.3
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• pp.81-88
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• 1997

This paper dealt with the position control of a flexible miniature finger driven by piezoelectric bimorph cells, cemented on both side of the finger. Bending moments generated by cells drives the finger, and end-point of the finger is controlled, so as to move in synchrony with fluctation of target and maintain a constant distance between target surface and inger's tip. The voltage applied for the cell is controlled by tip displacement error and error rate. We proposed a PD-Fuzzy controller under conception of PD control strategy. It brought and advantage which reduce number of rules than that of same type conventional fuzzy system and more correct redponse than PID control results.

• Proceedings of the KIEE Conference
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• 1995.07a
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• pp.344-346
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• 1995

In this paper a drive strategy of AC Servo Motor using Fuzzy method was proposed. Since the transfer function of the plant is nonlinear and very complicated, there are difficultly in driving the system with real time. The performance of out method is confirmed by computer simulation and experimental results. The high performance and high accuracy of the driving system. Fuzzy is designed and proposed.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.2
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• pp.195-203
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• 2016

In order to overcome the influence of system stability and accuracy caused by uncertainty, estimation errors and external disturbances in Eight-Rotor MAV, L2 gain control method was proposed based on interval type II fuzzy neural network identification here. In this control strategy, interval type II fuzzy neural network is used to estimate the uncertainty and non-linearity factor of the dynamic system, the adaptive variable structure controller is applied to compensate the estimation errors of interval type II fuzzy neural network, and at last, L2 gain control method is employed to suppress the effect produced by external disturbance on system, which is expected to possess robustness for the uncertainty and non-linearity. Finally, the validity of the L2 gain control method based on interval type II fuzzy neural network identifier applied to the Eight-Rotor MAV attitude system has been verified by three prototy experiments.

• Wind and Structures
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• v.22 no.6
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• pp.635-662
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• 2016

This paper deals with the comparison of different control strategies for the Induction generators in wind energy conversion system. Mainly, two types of induction machines, Self excited induction generator (SEIG) and doubly Fed Induction generators (DFIG) are studied. The different control strategies for SEIG and DFIG are compared. For SEIG, Electronic load Controller mechanism, Static Compensator based voltage regulator are studied. For DFIG the main control strategy namely vector control, direct torque control and direct power control are implemented. Apart from these control strategies for both SEIG and DFIG to improve the performance, the ANFIS based controller is introduced in both STATCOM and DTC methods. These control methods are simulated using MATLAB/SIMULINK and performances are analyzed and compared.

• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1439-1450
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• 2013

This paper investigates a robust neuro-fuzzy control (NFC) method which can accurately follow the speed reference of an interior permanent magnet synchronous motor (IPMSM) in the existence of nonlinearities and system uncertainties. A neuro-fuzzy control term is proposed to estimate these nonlinear and uncertain factors, therefore, this difficulty is completely solved. To make the global stability analysis simple and systematic, the time derivative of the quadratic Lyapunov function is selected as the cost function to be minimized. Moreover, the design procedure of the online self-tuning algorithm is comparatively simplified to reduce a computational burden of the NFC. Next, a rotor angular acceleration is obtained through the disturbance observer. The proposed observer-based NFC strategy can achieve better control performance (i.e., less steady-state error, less sensitivity) than the feedback linearization control method even when there exist some uncertainties in the electrical and mechanical parameters. Finally, the validity of the proposed neuro-fuzzy speed controller is confirmed through simulation and experimental studies on a prototype IPMSM drive system with a TMS320F28335 DSP.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.270-275
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• 2005

This paper presents a fuzzy model-based adaptive approach for synchronization of chaotic systems which consist of the drive and response systems. Takagi-Sugeno (T-S) fuzzy model is employed to represent the chaotic drive and response systems. Since the parameters of the drive system are assumed unknown, we design the response system that estimates the parameters of the drive system by adaptive strategy. The adaptive law is derived to estimate the unknown parameters and its stability is guaranteed by Lyapunov stability theory. In addition, the controller in the response system contains two parts: one part that can stabilize the synchronization error dynamics and the other part that estimates the unknown parameters. Numerical examples, including Doffing oscillator and Lorenz attractor, are given to demonstrate the validity of the proposed adaptive synchronization approach.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.766-771
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• 1993

A mathematical model is developed to represent the batch reactor for free radical polymerization of PMMA The model is validated by comparing the simulation result with the experimental data. A computational scheme is proposed to determine the trajectory of the reactor temperature that will produce polymer product having the desired molecular weight distribution. For this instantaneous number average chain length and polydispersity are introduced to calculate the reactor temperature. The former is assumed to be a second order polynomial of the sum of the living and dead polymer concentrations. Various reactor temperature, trajectories are observed depending on the reactor conditions and prescribed molecular weight distributions. Fuzzy and PID control algorithms are applied to trace the reactor temperature trajectory. While the PID control gives rise to an overshoot when the trajectory changes its direction, the fuzzy controller yields a more satisfactory performance because it secures information on the trajectory pattern.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1118-1120
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• 1998

In this study, an adaptive evolutionary computation (AEC), which uses adaptively a genetic algorithm having global searching capability and an evolution strategy having local searching capability with different methodologies, is suggested. We applied the AEC to design of fuzzy logic controllers for a PSS (power system stabilizer). FLCs for PSS controllers are designed for damping the low frequency oscillations caused by disturbances such as tile sudden changes of loads, outages in generators, transmission line faults, etc. The membership functions of FLCs is optimally determined by AEC.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.831-836
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• 2010

In real system application, the path planning and following system for the coordinated control of heterogeneous marine robots based on the underwater acoustic communication has the following problems: surface and underwater robots have different maneuvering properties, an underwater robot requires more effective operating, it has a limited communication range because of the transmission loss (TL) of acoustic wave, it has a communication error because of the Doppler distortion of acoustic wave, and further, it requires an easy design procedure in terms of its structures and parameters. To solve these problems, an intelligent path planning algorithm using the evolution strategy (ES) and the fuzzy logic controller (FLC) based on system modeling, is proposed. To verify the performance of the proposed algorithm, the path planning and following of an underwater robot is performed according to the maneuvering of a surface robot. Simulation results show that the proposed algorithm effectively solves the problems.