• The Transactions of the Korean Institute of Power Electronics
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• v.7 no.3
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• pp.215-223
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• 2002

This paper investigates the adaptive control of a fuzzy logic based speed and flux controller fur 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(MRAC) 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.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1987-1992
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• 2004

A Variable Structure Model Reference Adaptive Controller (VS-MRAC) using state Variables is proposed for single input multi output systems. . The structure of the switching functions is designed based on stability requirements, and global exponential stability is proved. Transient behavior is analyzed using sliding mode control and shows perfect model following at a finite time. The effect of input disturbances on stability and transients is investigated and shows preference to the conventional MRAC schemes with integral adaptation law. Sliding surfaces are independent of system parameters and therefore VS-MRAC is insensitive to system parameter variations. Simulation is presented to clear the theoretical results.

• Journal of Power Electronics
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• v.14 no.3
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• pp.549-563
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• 2014

In this paper, the speed regulation problem of permanent synchronous motor (PMSM) systems under the vector control framework is studied. A model reference adaptive controller (MRAC) based on the Lyapunov stability theory is first designed. Since the standard MRAC method provides poor disturbance rejection performance in the case of strong disturbances, a composite control method which combines the MRAC method and the disturbance estimation method, called the MRAC+ESO method, is proposed. An extended state observer (ESO) is introduced to estimate the lumped disturbances. The obtained estimated value acts as a feedforward compensation term to the MRAC controller. A stability analysis of the composite control method is given. Simulation and experimental results are presented and compared to show the effectiveness of the proposed control method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.562-567
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• 2000

This paper proposed a speed estimator using MRAC(Model Reference Adaptive Control) for sensorless vector control. It is robust for parameter variation and the estimated speed is used as feedback in a vector control system. Computer simulation is presented to confirm the theoretical analysis.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.8 s.227
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• pp.1152-1158
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• 2004

In this study a MRAC(model reference adaptive control) for fluid power elevator model system was designed. The MRAC was compared with PI control in case of applying to the elevator model system with constant external load and changing external load. In this case external load was produced by a single fluid power cylinder combined with pressure control valve. In conclusion the MRAC control performance was better than PI control performance because overshoot and steady state error of the elevator model system controlled by the MRAC were not appeared for constant and changing external load.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.331-334
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• 1996

It is a well-known problem that the adaptive control has a poor transient response. In order to improve this problem, the scheme that model-reference adaptive control (MRAC) uses the genetic algorithm (GA) in the search for parameters is proposed. Use genetic algorithm (GA) in the searching for controller's parameters set and conventional gradient method for fine tuning. And show the reduction of the oscillations in transient response comparing with the conventional MRAC.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.3
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• pp.57-64
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• 2015

In this paper, a model reference adaptive control (MRAC) scheme is applied for the precise and robust motion control of a pneumatic system with load variation. The reference model for MRAC is designed systematically using linear quadratic Gaussian control with loop transfer recovery (LQG/LTR). The sigmoid function of inverse velocity is used to compensate for the nonlinear friction force between the sliding parts. The experimental results show that MRAC effectively overcame the limit of the PID controller when there was unknown disturbance, including abrupt load variation and model uncertainty in the pneumatic control system.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.40 no.8
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• pp.535-542
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• 2016

In this study, a model reference adaptive controller is developed to regulate the outlet air flow rate of centrifugal compressor for automotive supercharger. The centrifugal compressor is developed using the analytical based method to predict the transient behavior of operating and the designed model is validated with experimental data to confirm the system accuracy. The model reference adaptive control structure consists of a compressor model and a MRAC(model reference adaptive control) mechanism. The feedback control do not robust with variation of system parameter but the applied adaptive control is robust even if the system parameter is changed. As a result, the MRAC was regulated to reference air flow rate. Also MRAC was found to be more robust control compared with the feedback control even if the system parameter is changed.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.9
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• pp.749-757
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• 2021

In transportation missions using quadrotor, the payload may change the model parameters, such as mass, moment of inertia, and center of gravity. Moreover, if position of the payload is constantly changing during flight, the effect can adversely affect the control performances. To handle this issue, we suggest Model Reference Adaptive Control based on Linear Quadratic Regulator(LQR+MRAC) to compensate the uncertainty caused by payload. Firstly, the mathematical modeling with the fixed payload is derived. Second, Linear Quadratic Regulator (LQR) is used to design the reference model and baseline controller. Also, through the Stability method, Adaptive law is derived to estimate the model parameters. To verify the performance of proposed control scheme, we compared LQR and LQR+MRAC in situations where uncertainties exist. And, when the disturbance exist, the classic MRAC and proposed controller is compared to analyze the transient response and robustness.

• Journal of Power System Engineering
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• v.21 no.4
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• pp.42-50
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• 2017

A velocity controller using a modified model reference adaptive controller (M-MRAC) and a projection operator for a fish sorting belt conveyor system with uncertainty parameters, input saturation and bounded disturbances is proposed in this paper. To improve the tracking performance and robustness of the proposed controller in the presence of bounded disturbances, the followings are done. Firstly, the reference model for the conventional model reference adaptive controller (CMRAC) is replaced by a modified reference model for a M-MRAC to reduce unexpected high frequency oscillation in control input signal when the adaptation rate is increased. Secondly, estimated parameters in an adaptive law are varied smoothly under bounded external disturbances and a projection operator is utilized in an adaptive law for the proposed M-MRAC controller to be robust. Thirdly, an auxiliary error vector is introduced for compensating the error dynamics of the system when the saturation input occurs. Finally, the experimental results are shown to verify the better effectiveness and performance of the proposed controller under the bounded disturbance and saturated input than that of a CMRAC.