• Journal of the Earthquake Engineering Society of Korea
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• v.5 no.4
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• pp.75-81
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• 2001

Fuzzy supervisory control method is studied for the active control of earthquake excited structures. The proposed algorithm supervises and tunes previously designed control gains by evaluating the state of a structure through the fuzzy inference mechanism, which uses the information of relative displacements and velocities. Example designs and numerical simulations of earthquake exited three degrees of freedom structures are performed to prove the validity of the proposed control algorithm. Comparative results with conventional LQR method show that the proposed method is effective for the vibration suppression of earthquake excited structures.

• Journal of the Earthquake Engineering Society of Korea
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• v.9 no.4 s.44
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• pp.55-66
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• 2005

The effectiveness of fuzzy supervisory control technique for the control of seismic responses of smart base isolation system is investigated in this study. To this end, first generation base isolated building benchmark problem is employed for the numerical simulation. The benchmark structure under consideration is an eight-story base isolated building having irregular plan and is equipped with low-damping elastometric bearings and magnetorheological (MR) dampers for seismic protection. Lower level fuzzy logic controllers (FLC) for far-fault or near-fault earthquakes are developed in order to effectively control base isolated building using multi-objective genetic algorithm. Four objectives, i.e. reduction of peak structural acceleration, peak base drift, RMS structural acceleration and RMS base drift, are used in multi-objective optimization process. When earthquakes are applied to benchmark building, each of low level FLCs provides different command voltage and supervisory fuzzy controller combines two command voltages io one based on fuzzy inference system in real time. Results from the numerical simulations demonstrate that base drift as well as superstructure responses can be effectively reduced using the proposed supervisory fuzzy control technique.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.84-89
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• 2003

Fuzzy controller is one of the succeed controller used in the process control in case of model uncertainties. But it my be difficult to fuzzy controller to articulate the accumulated knowledge to encompass all circumstance. Hence, it is essential to provide a tuning capability. There are many parameters in fuzzy controller can be adapted, scale factor tuning of normalized fuzzy controller is one of the adaptation parameter. Two adaptation methods are implemented in this work on an experimental thermal process, which simulate heating process in liquefied petroleum gases (LPG) recovery process in one of petrochemical industries: Gradient decent (GD) adaptation method; supervisory fuzzy controller. A comparison between the two methods is discussed.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.4
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• pp.627-637
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• 1994

In this study, a predictive fuzzy control algorithm to supervise the elevator system with plural cars is developed and its performance is evaluated. The proposed algorithm is based on fuzzy in-ference system to cope with multiple control objects and uncertainty of system state. The control objects are represented as linguistic predictive fuzzy rules and simplified reasoning method is utilized as a fuzzy inference method. Real-time simulation is performed with respect o all possible modes of control, and the resultant controls ard predicted. The predicted rusults are then utilized as the control in-puts of the fuzzy rules. The feasibility of the proposed control algorithm is evaluated by graphic simulator on computer. Finallu, the results of graphic simulation is compared with those of a conventional group control algorighm.

• Journal of the Earthquake Engineering Society of Korea
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• v.8 no.4
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• pp.51-62
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• 2004

Fuzzy supervisory control technique for the seismic response control of cable-stayed bridges subject to earthquakes is studied. The proposed technique is a hybrid control method, which adopts a hierarchical structure consisting of several sub-controllers and a fuzzy supervisor. Sub-controllers are independently designed to reduced the responses to be controlled of a cable-stayed bridge, and a fuzzy supervisor achieves improved seismic control performance by tuning the pre-designed sub-controllers. It is realized by converting static gains of the sub-controllers into time-varying dynamic gains through the fuzzy inference mechanism. To evaluate the feasibility of the proposed technique, the benchmark control problem of cable-stayed bridge proposed by Dyke et al. is adopted. The control variables for the seismic response control of the cable-stayed bridge are determined to be t도 shear forces and bending moments at the base of the towers, the longitudinal displacements at the top of the towers, the relative displacements between the deck and the tower, and the tensions in the stay cables. Comparative results between the fuzzy supervisory controller and LQG controller demonstrate the effectiveness of the proposed control technique.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.172-175
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• 1996

In the paper is proposed a hierarchical self-learning fuzzy controller for balancing and position control of an circular inverted pendulum system. To stabilize the pendulum at a specified position, the hierarchical fuzzy controller consists of a supervisory controller, a self-learning fuzzy controller, and a forced disturbance generator. Simulation example shows the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.356-356
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• 2000

For irregular nonlinear systems, switching controlk form is proposed recently. This control law is designed to overcome the singularities through the scheme that switches between an approximate tracking law close to the singularities, and an exact tracking law away from the singularities. But, that form has problems which may break the system's stability through unstable control input value at switching procedure. In this paper, We propose new switching control law which supervises approximate tracking control law and exact tracking control law by fuzzy rules to overcome unstability problem in switching procedure.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.2
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• pp.155-160
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• 2006

In the paper a robust indirect adaptive fuzzy controller is proposed for balancing and position control of the inverted pendulum system. Because balancing control rules of the pendulum and position control rules of the cart can be opposite, it is difficult to design an adaptive fuzzy controller that satisfy both objectives. To stabilize the pendulum at a specified position, the proposed fuzzy controller consists of a robust indirect adaptive fuzzy controller for balancing and a supervisory fuzzy controller which emulates heuristic control strategy and arbitrate two control objectives. It is proved that the signals in the overall system are bounded. Simulation results are given to verify the proposed adaptive fuzzy control method.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.45.1-45
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• 2002

$\textbullet$ Introduction $\textbullet$ Takagi-Sugeno Fuzzy Model and Sliding Mode Controller $\textbullet$ Observer and Controller Design $\textbullet$ Simulations $\textbullet$ References

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.180-186
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• 1998

This paper deals with the application of fuzzy Petri net to control the line tracking mobile robot. Comparing with the Petri net and the fuzzy Petri net, the fuzzy Petri net model is more effective than the use of Petri net, so the line tracking mobile robot has a little shake and also has a little moving distance than one of using the Petri, And thus the mobile robot shows less energy consumption