• 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.

• Journal of Power Electronics
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• v.13 no.1
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• pp.122-138
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• 2013

Adaptive control of a peak current mode controlled (PCM) boost converter supplied by a PEM fuel cell is described in this paper. The adaptive controller with reference model and signal adaptation is developed in order to compensate the deviation of the response during the change of the operating point. The procedure for determining the adaptive algorithm's weighting coefficients, based on a combination of the pole-zero placement method and an optimization method is proposed. After applying the proposed procedure, the optimal adaptive algorithm's weighting coefficients can be determined in just a few iterations, without the use of a computer, thus greatly facilitating the application of the algorithm in real systems. Simulation and experimental results show that the dynamic behavior of a highly nonlinear control system with a fuel cell and a PCM boost converter, can fairly accurately be described by the dynamic behavior of the reference model, i.e., a linear system with constant parameters.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.3
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• pp.250-254
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• 2008

Robot actuators are significantly important with respect to whole control system performance. This paper presents an adaptive control approach for flexible robot actuators with time-varying spring and damping nature. We first represent a perturbed system model with assumption that its information are partially known. Nominal model reference control method is employed for deriving our adaptive control law. We carry out numerical simulation to evaluate the proposed control system and compare simulation results to a well-known control method for demonstrating its effectiveness.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.5
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• pp.52-61
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• 1993

This paper deals with adaptive control method of a robot manipulator with one-flexible link. ARMA model is used as a prediction and estimation model, and adaptive control scheme consists of parameter estimation part and adaptive controller. Parameter estimation part estimates ARMA model's coefficients by using recursive least-squares(RLS) algorithm and generates the predicted output. Variable forgetting factor (VFF) is introduced to achieve an efficient estimation, and adaptive controller consists of reference model, error dynamics model and minimum prediction error controller. An optimal input is obtained by minimizing input torque, it's successive input change and the error between the predicted output and the reference output.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.483-488
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• 1989

In this paper, the concept of persistent excitation(PE) is examed and the model reference adaptive control of a linear plant subjected to bounded disturbances is considered. Computer simulation reasults of nonlinear differential equations shows that the global behavior of the adaptive system depends upon the PE of the reference input as well as the amplitude of the external disturbances. The sufficient conditions on the PE of the reference input for the signals in the adaptive system to be globally bounded has been derived.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.1114-1116
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• 2000

A direct model reference adaptive control (DMRAC) is applied to the speed control of brushless do(BLDC) motor. The main objective is to achieve precise speed control in the face of varying motor parameters and load. The control is described as an outer loop speed control and an inner current loop control which has raster dynamics than the speed loop. The adaptive control is applied to the outer speed control loop. DMRAC is compared to an indirect adaptive controller(IMRAC) and a PI controller. Simulation results show that the two adaptive controllers give similar respose and are superior to the PI controller. However, the DMRAC algorithm is simpler to implement.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.3
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• pp.166-172
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• 1989

The model reference adaptive control algorithm (MRAC), which is one of the methods for controlling the speed of a permanent magnet synchronous motor (PMSM), has been developed using the autoregressive (ARMAX) method. Applying this algorithm to a microprocessor which is used in driving PMSM with PI controller, it has been proved that the response speed of the reference input follows closely that of the reference model. It has also been proved by experiments that the quick speed response without over-shoot could be obtained for the motor system with variable parameters.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.746-748
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• 1988

A way of improving the transient performance is suggested for a class of model reference adaptive control systems. To increase the convergence rate of a model following error, an error feedback term is incorporated into the control law.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.5
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• pp.625-630
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• 1986

In this paper, an adaptive observer based upon the exponentially weighted least-square method is implemented in the design of a model reference adaptive controller for an unknown time-invariant discrete single-input single-output linear plant. The adaptive observer estimates the padrameter vectors and initial state vector. The control input is determined so that the output of the plant converges to the output of the stable model reference.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.4
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• pp.610-616
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• 2008

This paper presents a new robust sensorless control system for high performance induction motor drives fed by a matrix converter with variable structure. The lumped disturbances such as parameter variation and load disturbance of the system are estimated by a variable structure approach based on model reference adaptive scheme. A Reduced Order Extended Luenberger Observer(ROELO) is also employed to bring better responses at the low speed operation. Experimental results are shown to illustrate the performance of the proposed system.