• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.341-344
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• 1993

This paper presents the general MRAC algorithm design, it's real time implementation and investigates the effect of purely deterministic disturbances to adaptive control algorithm. The design of adaptive control algorithm to reject the disturbances properly is also presented. In real time application, adaptive control algorithm is considered to investigate its performance by using DC motor. Disturbance rejection algorithm is investigated in simulation.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2252-2254
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• 2001

This paper proposes a algebraic parameter determination of MRAC (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 in 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.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.33 no.1
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• pp.17-20
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• 1984

The motivation in this paper is in constructing the controller with faster adapting speed than the one using the errors between the states of the plant and the model as the adaptive criterion. In the first part of this work, the adaptive law is found by using the state errors. In the later part, the adaptive law is obtained by introducing the companion model method. Finally the justification for the adaptive speed characteristics are compared.

• Journal of Korean Port Research
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• v.14 no.3
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• pp.291-301
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• 2000

T his paper presents the lateral and longitudinal control algorithm for the driving of a 4WS AGV(Automated Guided Vehicle). The control law to the lateral and longitudinal control of the AGV includes adaptive agin tuning ability, that is the controller gain of the gravity compensated PD controller can be changed on a real-time. The gain tuning law is derived from the Lyapunov direct method using the output error of the reference model and the actual model, And to show the performance of the presented lateral and longitudinal control algorithm, we simulate toe nonlinear AGV equations of the motion by deriving the Newton-Euler Method, The read path is from quay yard area to docking position in loading yard area. The quay yard area is where the quay crane loads the container to the AGV and the docking position is where the container is transferred to the gantry crane. The road types are constructed in a straight line and J-turn. When driving the straight line, the driving velocity is 6㎧ and the J-turn is 3㎧.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.2 no.4
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• pp.46-52
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• 2003

For position control of electro-hydraulic servo system, single rod cylinders and double rod cylinders are used. Single rod cylinders have simple structure for manufacturing but different volume ratio of two sides induce to non-linearity in process of then mathematical modeling. So only with conventional PID control method it is difficult to control single rod cylinders precisely. For mole precise position control of single rod cylinders, a controller which is inserted a velocity feedback PID controller and MRAC controller are proposed. With experiment control performances of three control methods are compared. In case of experiment, for external varying load to the system, a hydraulic cylinder and a pressure control valve are used. In conclusion a MRAC is considered a suitable control method for external varying load.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.243-247
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• 1992

This paper describes a neural network based control scheme with MRAC. The system consists of two neural network; one is for identifier and the other is for controller. Identification is firstly performed to learn the behavior of the nonlinear plant. Neural net controller is next trained by backpropagating the error at the output of plant through the identifier. Also the training method used in this paper repeatedly updates weights of neural network to track the reference model.

• Journal of the Korean Society of Industry Convergence
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• v.2 no.2
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• pp.91-102
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• 1999

The paper describes a robust adaptive control algorithm for induction motor drive without speed sensor at low speed range. The control algorithm use only current sensors in a space vector pulse width modulation within loop control with rotor speed estimation and voltage source inverter. On-line rotor speed estimation is based on utilizing parallel model reference adaptive control system. MRAC of the modified flux model for flux and rotor speed estimator uses dual-adaptation mechanism, ${\omega}_r$ and ${\omega}_e$ scheme. The estimated flux components in the model can be compensated from the effects of offset errors on pure integrals. It can be compensated to the parameter variations and torque fluctuation with speed estimation in less then 10 rad/sec. In a simulation, the proposed induction motor control algorithm without speed sensor at very low speed range are shown to operate very well in spite of variable rotor time constant and fluctuating load without change the controller parameters. The suggested control strategy and estimation method have been validated by simulation study, and it proposed the designed system for the implementation using TI320C31 DSP/ASIC controller.

• Journal of the Korean Institute of Telematics and Electronics
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• v.20 no.1
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• pp.37-44
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• 1983

A class of adaptive control algorithms applied to discrete-time single-input single-output deterministic linear systems is analyzed by using direct model reference adaptive control. Controller parameters are identified with weighted least square Method. And computer simulations reveal that proposed weighted least square method in which the value of depends on the identification error can be used regardless of the sufficient condition of reference input signal.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1492-1495
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• 1996

In this paper, an approach to autopilot design based on the robust nonlinear dynamic inversion method is proposed. Both unknown parameters and uncertainty bounds are estimated and parameter estimates are used in the fast inversion. Furthermore, to get more robustness slow inversion is incorporated with MRAC(Model Reference Adaptive Control) and sliding mode control where the estimates of uncertainty bounds are used. The proposed method is applied to the pitch autopilot design of a missile system and excellent performance is shown via computer simulation.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.3
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• pp.171-179
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• 1988

This paper deals with the controller design of the flight control system using the model reference adaptive control approach. The structure of the adaptive control system is based on the structure suggested by NARENDRA and VALAVANI. In particular, the problem is considered in case of the relative degree n=2 of plant. The flight control system is single-input single-output system, and the control input is given from the input-output data of the referencemodel and plant. For the analysis of the designed control system, thesimulation is perfarmed in cases of analog plant and analog plant with flight motion table, and reviewed.