• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.203-208
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• 1998

This paper presents an adaptive fuzzy controller using an neural network and adaptation algorithm. Reference-model following neuro-fuzzy controller(RMFNFC) is invesgated in order to overcome the difficulty of rule selecting and defects of the membership function in the general fuzzy logic controller(FLC). RMFNFC is developed to tune various parameter of the fuzzy controller which is used for the discrete nonlinear system control. RMFNFC is trained with the identification information and control closed loop error. A closed loop error is used for design criteria of a fuzzy controller which characterizes and quantize the control performance required in the overall control system. A control system is trained up the controller with the variation of the system obtained from the identifier and closed loop error. Numerical examples are presented to control of the discrete nonlinear system. Simulation results show the effectiveness of the proposed controller.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.1168-1170
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• 1997

In this paper, the sliding mode-model following(SM-MF) power system stabilizer(PSS) including closed-loop feedback(CLF) for single machine system is extended to multimachine system. Simulation results show that the SM-MF multimachine stabilizer is able to achieve asymptotic tracking error between the reference model state and the controlled plant state at different initial conditions.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.1162-1164
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• 1997

This paper presents a power system stabilizer(PSS) using sliding mode-model following(SM-MF) including closed-loop f:edback(CLF) and compares the SM-MF PSS without CLF with that including CLF. The aim of this SM-MF PSS including CLF is to damp the low-frequency oscillation by using CLF and then is to obtain asymptotic tracking error between the reference model state and the plant state.

• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.327-338
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• 2008

A fault tolerant control system design technique has been proposed and analyzed for managing performance degradation in the presence of multiple faults in actuators. The method is based on a control structure with a model reference reconfigurable control design in an inner loop and command input adjustment in an outer loop. The reduced dynamic performance requirements in the presence of different actuator faults are accounted for through different performance reduced (degraded) reference models. The degraded steady-state performances are governed by the reduced levels of command input. The reconfigurable controller is designed on-line automatically in an explicit model reference control framework so that the dynamics of the closed-loop system follow that of the performance reduced reference model under each fault condition. The reduced command input level is determined to prevent potential actuator saturation. The proposed method has been evaluated and analyzed using an aircraft example against actuator faults subject to constraints on the magnitude and slew-rate of actuators.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2001.11a
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• pp.181-185
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• 2001

This paper presents a digitally speed sensorless control system for induction motor with direct torque control (DTC). The drive is based on Mode1 Reference Adaptive System (MRAS) using state observer as a reference model fat flux estimation. The system are closed loop stator flux and torque observer for wide speed range that inputs are currents and voltages sensing of motor terminal, model reference adaptive control (MRAS) with rotor flux linkages for the speed turning aignal at low speed range, two hysteresis controllers. The Proposed system is verified through simulation.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1840-1841
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• 2006

Plants with long time-delays can not be often controlled effectively using a simple PID controller. The main reason for this is that the additional phase lag contributed by the time-delay tends to destabilize the closed-loop system. The stability problem can be solved by smith predictor. However, in this case responses are very sensitive to the estimated model errors. To reduce sensitive problem, this paper is presented based on virtual reference feedback tuning of the time delay plant using the closed-loop test to find parameters for a PID controller using the closed-loop test data.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.1
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• pp.32-42
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• 2001

In this paper, a parameter estimator is developed for the plant model whose structure is represented by the Takagi-Sugeno model. The essential idea behind the on-line estimation is the comparison of the measured stated with the state of an estimation model whose structure is the same as that of the parameterized model. Based on the parameter estimation scheme, and indirect Model Reference Adaptive Fuzzy control(MRAFC) scheme is proposed to provide asymptotic tracking of a reference signal for the systems with uncertain for slowly time-varying parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop systems. In addition, the plant state tracks the state of the reference model asymptotically with time for any bounded reference input signal.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.174-178
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• 1987

In the design of reference model based STC (self-tuning controllers), parameters of the controllers are determined not from the true plant but from the estimated model. In this paper, we suggest a power spectrum estimation method for visualling the sensitivity of the closed loop system without knowing the explicit original plant.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.11
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• pp.53-67
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• 1998

This paper suggests a method designing the TSK fuzzy controller based on the TSK fuzzy model, which guarantees the stability of the closed loop system and makes the response of the closed loop system to be a desired one. This paper deals with the general type of TSK fuzzy model of which consequents are affine equations having a constant term. The TSK fuzzy controller suggested in this paper is designed by using the pole placement which developed for the linear systems and makes the closed loop system have the same behavior as a desired linear system. A reference input can be introduced to the suggested TSK fuzzy controller and an integral action also can be introduced. Simulation results reveal that the suggested methods are practically feasible. This paper deals with both the continuous systems and the discrete systems.