• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1062-1065
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• 1993

Nuclear reactor operation is a human intensive task; one of the features of a problem for which fuzzy controllers present the most suitable solution. The performance of the fuzzy controllers can further be improved through tuning. In this work, application of a fuzzy controller in real-time control of a nuclear reactor is presented. The fuzzy controller is tuned on-line using direct gradient search method.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.684-686
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• 1998

This paper consider fuzzy control of a single-inverted pendulum attached to the tip end of a rotating arm driven by a direct driven motor. Control objectives stabilization of the pendulum at the upright position and regulation of the arm at an arbitrary specified position. Fuzzy control is an effective method to achieve multiple control objectives in control of nonlinear systems. In this paper, fuzzy logic control is proposed to obtain increased control performance and stability.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1186-1188
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• 1996

Neural networks and fuzzy systems have attracted the attention of many researehers recently. In general, neural networks are used to obtain information about systems from input/output observation and learning procedure. On the other hand, fuzzy systems use fuzzy rules to identify or control systems. In this paper we present a generalized FCMAC(Fuzzified Cerebellar Model Articulation Controller) networks, by integrating fuzzy systems with the CMAC(Cerebellar Model Articulation Controller) networks. We propose a direct adaptive controller design based on FCMAC(fuzzified CMAC) networks. Simulation results reveal that the proposed adaptive controller is practically feasible in nonlinear plant control.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2849-2852
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• 1999

This paper describes the fuzzy PD controller using simplified indirect inference method. First, the fuzzy PD controller is derived from the conventional continuous time linear PD controller. Then the fuzzification, control-rule base, and defuzzification using SIIM in the design of the fuzzy controller are discussed in detail. The resulting controller is a discrete time fuzzy version of the conventional PD controller. which has the same linear structure. but are nonlinear functions of the input signals. The proposed controller enhances the self-tuning control capability. particularly when the process to be controlled is nonlinear. As the SIIM is applied, the fuzzy Inference results can be calculated with splitting fuzzy variables into each action component and are determined as the functional form of corresponding variables. So the Proposed method has the capability of the high speed inference and extending the fuzzy input variables easily. Computer simulation results have demonstrated the superior to the control Performance of the one Proposed by D. Misir et at. Final)y. we simulated the contour control of the X-Y tables with direct control strategies using the proposed fuzzy PD controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.1
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• pp.130-135
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• 2007

In this paper, a direct model reference adaptive fuzzy control (MRAFC) scheme is developed for the plant model whose structure is represented by the MIMO Takagi-Sugeno fuzzy model. The MRAFC scheme is proposed to provide asymptotic tracking of a reference signal lot the systems with uncertain or slowly time-varying parameters. The developed control law and adaptive law guarantee that all signals in the closed-loop system are bounded. In addition, the plant state tracks the state of the reference model asymptotically with time tot any bounded reference input signal.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.4
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• pp.240-250
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• 2015

The development of the control algorithms for under-actuated systems is important. Decoupled sliding mode control has been successfully employed to control under-actuated systems in a decoupling manner with the use of sliding mode control. However, in such a control scheme, the system functions must be known. If there are uncertainties in those functions, the control performance may not be satisfactory.In this paper, the direct adaptive fuzzy sliding mode control is employed to control a class of under-actuated uncertain systems which can be regarded as a combination of several subsystems with one same control input. By using the hierarchical sliding control approach, a sliding control law is derived so as to make every subsystem stabilized at the same time. But, since the system considered is assumed to be uncertain, the sliding control law cannot be readily facilitated. Therefore, in the study, based on Lyapunov stable theory a fuzzy compensator is proposed to approximate the uncertain part of the sliding control law. From those simulations, it can be concluded that the proposed compensator can indeed cope with system uncertainties. Besides, it can be found that the proposed compensator also provide good robustness properties.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.525-528
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• 2005

The tracking antenna system must be always pointed to target moving vehicle. Especially, for an antenna mounted on a movable vehicle, it needs the stabilized antenna system. In this paper, two types of fuzzy controller were derived and applied to a data link antenna system and the altitude control of unmanned helicopter, respectively. A simplified Fuzzy-PID controller was designed for 2-axes antenna stabilization and tracking system and the performance was verified by simulations and experiments. Computer simulations were performed by Matlab and SIMULINK. A 2-Axes antenna (SeaTel 1898 model) was selected as test platform of this research. The antenna was modified by using two Blushless Direct Current motors and an embedded DSP controller. To verify the performance of designed antenna servo control system, the performance of the conventional PID controller and that of the Fuzzy-PID controller, designed by the same PID control gains, were compared.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.2
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• pp.98-106
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• 2006

This paper proposes to position and speed control of interior Permanent magnet synchronous motor(IPMSM) drive without mechanical sensor. Also, this paper develops a adaptive fuzzy controller based fuzzy logic control for high performance of PMSM drives. In the proposed system, fuzzy control is used to implement the direct controller as well as the adaptation mechanism. A Gopinath observer is used for the mechanical state estimation of the motor. The observer was developed based on nonlinear model of IPMSM, that employs a d-q rotating reference frame attached to the rotor. A Gopinath observer is implemented to compute the speed and position feedback signal. The validity of the proposed scheme is confirmed by various response characteristics.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.465-467
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• 1998

A lane change maneuver is a part of lateral control of an automated highway system. Assuming no direct measurement of its position during transition from one lane to another. A vehicle is controlled to follow the virtual desired trajectory using only on-board sensors. This paper investigates the development of a fuzzy controller for automated lateral control during emergencies. The performance of the fuzzy controller is presented at 20m/s for a step lane change and a double lane change. The robustness of fuzzy controller is investigated with respect to change in tire parameters and the number of passengers.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.724-727
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• 1999

In this paper, the direct and indirect neural adaptive controller are combined based on the Lyapunov synthesis approach. The proposed adaptive controller is constructed from RBF neural network and a set of fuzzy IF-THEN rules. And the weighting parameters are adjusted on-line according to some adaptation law for the purpose of controlling the plant to track a given trajectory. In this scheme, fuzzy IF-THEN rules are used to decide the combined weighting factor. It is shown that all the signals in the closed-loop system are uniformly bounded under mild assumptions. The effectiveness of the proposed control scheme is demonstrated through the control of one-link rigid robotics manipulator.