• Journal of Institute of Control, Robotics and Systems
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• v.8 no.11
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• pp.928-934
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• 2002

A natural way to cope with fault tolerant control (FTC) problems is to modify the control parameters according to an online identification of the system parameters when a fault occurs. However. due to not only difficulties Inherent to the online multivariable identification in closed-loop systems, such as modeling errors, noise or the lack of excitation signals, but also long time requirement to identify the post-fault system and implemeutation of control problems during the identification process, we propose an alternative approach based on the observer-based fault detection and isolation (FDI) and model reference adaptive control (MRAC). The proposed robust fault diagnosis method is based on a bank of observers. We also propose a model reference adaptive control with changeable reference models according to the occurred faults. Simulation results of a flight control example show the validity and applicability of the proposed algorithms.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.10
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• pp.748-754
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• 1987

A robustness analysis for model reference adaptive control(MRAC) system with plant uncertainty is discussed in this paper. The adaptive control system is designed under assumptions that the controlled plant is represented by a lst order nominal model and that the system is drived by a constant reference signal. When using general gradient method(GGM), it is shown that unmodelled dynamics in plant model can cause the instability of the overall control loop during the adaptation process. However, as the algorithm of least square method(LSM) is introduced, the global stability of the system can be hold. And it is also given that the boundedness of adjustable parameters may be verified using the concept of an equilibrium point analysis.

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.3
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• pp.206-213
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• 1998

In this paper, an adaptive compensation technique for parameter variation is proposed which can perform quick torque response in vector control of an induction motors. To solve the problem of control performance degradation due to parameter variation in an induction motor, a rotor resistance estimation is performed by the model reference adaptive control(MRAC). The algorithm of rotor resistance estimation is composed of the error relationship which is generated between a motor real instantaneous reactive power and an estimated instantaneous reactive power. The advantage of such a real reactive power reference model is independence of the motor parameter variation. The estimation rotor resistance values are applied to the direct vector control system with a flux observer. Finally, the simulations and experiment are presented to validate the rotor resistance estimation algorithm of induction motor.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.1048-1053
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• 2003

This paper proposed a MR(Magneto-rheological) seat damper for a commercial vehicle. After formulating the governing equation of motion, an appropriate size of damper is designed and manufactured. Following the equation of fie d-dependent damping force characteristics, a semi-active seat suspension installed with the proposed MR-damper is constructed and its dynamic model id established, Subsequently, vibration isolation performance of the semi-active suspension system is demonstrated by incorporating with a MRAC(Model referenced adaptive control) fer the MR Seat Damper

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.12
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• pp.1170-1176
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• 2010

This study addresses adaptive control of UAVs(Unmanned Aerial Vehicles) pitch-axis maneuver. The MRAC(Model Referenced Adaptive Control) approach is employed to accommodate uncertainties which are introduced by feedback linearization of pitch attitude control by elevator input. The model uncertainty is handled by adaptation laws which update model parameters while the UAV is under control by the feedback control law. Steady-state pitch attitude achieved by the stabilizing control law is derived to provide insight on the closed-loop behavior of the controlled system. The proposed idea is free of linearization, gain-scheduling procedures, so that one can design high maneuverability of UAVs for pitching motion in the presence of significant model uncertainty.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.6
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• pp.946-961
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• 2004

A new adaptive controller which combines a model reference adaptive controller (MRAC) and a fuzzy controller is developed for unstable nonlinear time-invariant systems. The fuzzy controller is used to analyze and to compensate the nonlinear time-invariant characteristics of the plant. The MRAC is applied to control the linear time-invariant subsystem of the unknown plant, where the nonlinear time-invariant plant is supposed to comprise a nonlinear time-invariant subsystem and a linear time-invariant subsystem. The stability analysis for the overall system is discussed in view of global asymptotic stability. In conclusion. the unknown nonlinear time-invariant plant can be controlled by the new adaptive control theory such that the output error of the given plant converges to zero asymptotically.

• Proceedings of the KIPE Conference
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• 2002.07a
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• pp.222-224
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• 2002

This paper investigates the adaptive control of a fuzzy logic based speed and flux controller for a vector controlled induction motor drive. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the model reference adaptive control(mAC) fuzzy controller is evaluated by simulation for various operating conditions. The validity of the proposed MRAC fuzzy controller is confirmed by performance results for induction motor drive system.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.1
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• pp.37-46
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• 2004

A novel rotor speed estimation method using model reference adaptive control(MRAC) is proposed to improve the performance of a sensorless vector controller. In the proposed method, the stator current is used as the model variable for estimating the speed. In conventional MRAC methods, the relation between the two model errors and the speed estimation error is unclear. In the proposed method, the stator current error is represented as a function of the first degree for the error value in the speed estimation. Therefore, the proposed method can produce a fast speed estimation. The robustness of the rotor flux-based MRAC, back EMF-based MRAC, and proposed MRAC is compared based on a sensitivity function about each error of stator resistance, rotor time constant, mutual inductance. Consequently, the proposed method is much more robust than the conventional methods as regards errors in the mutual inductance, stator resistance. Therefore, the proposed method offers a considerable improvement in the performance of a sensorless vector controller at a low speed. In addition, the superiority of the proposed method and the validity of sensitivity functions were verified by simulation and experiment.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.1
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• pp.1-7
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• 2002

This paper proposes a algebraic parameter determination of MRA(Model Reference Adaptive Control) controller using block Pulse functions and block Pulse function's differential operation. Generally, adaption is performed by solving differential equations which describe adaptive low for updating controller parameter. The proposes algorithm transforms differential equations into algebraic equation, which can be solved much more easily inn a recursive manner. We believe that proposes methods are very attractive and proper for parameter estimation of MRAC controller on account of its simplicity and computational convergence.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.1169-1172
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• 1995

In this paper, the external force control and hybrid force control algorithms are proposed to apply Deburring process. the purpose of adjust which can be implemented to on unknown environments, adaptive control law(MRAC) is adopted. IF a model system is given, the plant system can be controlled on the way which we will introduce to. We showed the validation and the possibility of Deburring process with multi-dimensional force control through experiments. the experimental result show the validity of Deburring in the robot manipulator.