• Journal of IKEEE
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• v.3 no.2 s.5
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• pp.250-258
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• 1999

This paper presents a decentralized adaptive controller design for a Magnetically Levitated Fine Manipulator to follow the given trajectory as close as possible in spite of coupling effects between motion axes(degree of freedoms or subsystems). The present controller consists of two parts: the model reference controls based on known subsystems and the local adaptive controls. The former stabilizes the motion of the manipulator so as to follow that of the reference model. The latter reduces tracking errors due to coupling disturbances by adjusting the local gains to such levels that override interactions and assure the stability of the overall system. Through several experimental results, it has been shown that the decentralized adaptive control scheme has better tracking performances comparing to the PID controller case as well as good disturbance(coupling) rejection property.

• ETRI Journal
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• v.34 no.3
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• pp.474-477
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• 2012

The MPEG-D unified speech and audio coding (USAC) standardization process was initiated by MPEG to develop an audio codec that is able to provide consistent quality for mixed speech and music contents. The current USAC reference model structure consists of frequency domain (FD) and linear prediction domain (LPD) core modules and is controlled using a signal classifier tool. In this letter, we propose an LPD single-mode USAC structure using an adaptive widowing-based transform-coded excitation module. We tested our system using official test items for all mono-evaluation modes. The results of the experiment show that the objective and subjective performances of the proposed single-mode USAC system are better than those of the FD/LPD dual-mode USAC system.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.7
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• pp.437-442
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• 2005

In order to realize the speed control of an induction motor, the information of the rotor speed is needed. So the speed sensor as an encoder or a pulse generator is used to obtain it. But the use of speed sensor occur the some problems in the control system of an induction motor. To solve the problems, the appropriate speed estimation algorithm is used instead of the speed sensor. Also there is the limitation to improve the speed control performance of an induction motor using the existing speed estimation algorithm. Therefore, in this paper, intelligent speed estimator using Fuzzy-Neural systems as adaptive laws in Model Reference Adaptive System is proposed so as to improve the existing estimation algorithm and ,using the rotor speed estimated by the Proposed estimator, the speed control of an induction motor without speed sensor is performed. The computer simulation and the experiment is executed to prove the performance of the speed control system usinu the proposed speed estimator.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.5
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• pp.845-851
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• 2008

A simple RMRAC (Robust Model Reference Adaptive Control) scheme for the PMSM (Permanent Magnent Synchronous Motor) is proposed in the synchronous frame. A current control of PMSM is the most inner loop of electro-mechanical driving systems and it requires a fast and simple control law to play a foundation role in the control hierarchy. In the proposed synchronous current model, the input signal is composed of a calculated voltage by proposed adaptive laws and real system disturbance. The gains of feed-forward and feedback controllers are estimated by the proposed modified Gradient method respectively, where the system disturbances are assumed as filtered current tracking errors. After the estimation of the system disturbances from the tracking errors, the corresponding voltage is fed forward to control input voltage to compensate for the disturbances. The proposed method is robust against high frequency disturbance and has a fast dynamic response. It also shows a good real-time performance due to it's simplicity of control structure. Through the simulations and real experiments, efficiency of the proposed method is verified.

• Journal of Advanced Navigation Technology
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• v.24 no.2
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• pp.101-106
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• 2020

In order to smoothly control the speed of the induction motor, it is necessary to obtain the required rotor speed information. In order to obtain the speed information, it must be obtained using a sensor, but it can also be obtained using an appropriate algorithm without using a sensor. In order to obtain speed information, a system was designed using a model reference adaptive system (MARS). Indirect vector control, one of the speed control methods of induction motors, was calculated from the motor current and rotor parameter values. The method of obtaining the position information of the magnetic flux by combining the slip frequency with the rotor speed was used. It is possible to simply perform instantaneous current control in a wide speed range without actual magnetic flux information, and has the advantage that the structure of the controller is simple. Therefore, in this paper, the control system was constructed based on the indirect vector control method, and the speed control system of the induction motor was developed by estimating the required rotor speed information as an intelligent algorithm developed without using it as a sensor.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.48 no.11
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• pp.632-639
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• 1999

SRM(Switched Reluctance Motor) drives require the accurate position and speed information of the rotor. These informations are generally provided by a shaft encoder or resolver. High temperature, EMI, and dust may make detection performance deteriorate. Therefore, the elimination of the position and speed sensor is desirable. In this paper, a nonlinear adaptive observer using the MRAS(Model Reference Adaptive System) is proposed. The rotor speed and position are estimated by the adaptation law using the real and estimated currents. The stability of the adaptive observer is proved by Lyapunov stability theory. The proposed methods are implemented with TMS320C31 DSP. Experimental results prove that the observer has a good estimation performance of the rotor speed and position despite of the parameter variations and loads, and the speed control can be accomplished in the wide speed range.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.51 no.7
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• pp.399-405
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• 2002

This paper presents an implementation of digital high-performance Position sensorless motion control system of an induction motor drives with Direct Torque Control(DTC). The system consist of closed loop stator flux and torque observer, speed and torque estimators, two hysteresis controller, optimal switching look-up table, IGBT voltage source inverter, and TMS320C31 DSP board. The stator flux observer is based on the combined current and voltage model with stator flux feedback adaptive control of which inputs are current and voltage sensed on motor terminal for wide speed range. The speed observer is using the model reference adaptive system(MRAS) with rotor flux linkages for speed turning signal. The simulation and experimental results are provided to evacuate the consistency and the performance of the suggested position sensorless control algorithm. The developed position sensorless system are shown a good motion control response characteristic and high performance features using 2.2[kw] general purposed induction motor.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.191-196
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• 2003

This paper presents a method to design an adaptive controller for the kinematic model of a two-wheeled welding mobile robot (WMR) with unknown parameters. We propose a nonlinear controller based on the Lyapunov function to enhance the tracking properties of the WMR. The WMR can track any smooth curved welding path at a constant velocity of the welding point. The system has three degrees of freedom including two wheels and one torch slider. Torch slider motion is used for fast tracking. To design the tracking performance, the errors from WMR to steel wall is defined, and the controller is designed to drive the errors to zero as fast as possible. The effectiveness of the proposed controller is shown through simulation results.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2254-2259
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• 2005

In this paper, we propose a wavelet based fuzzy neural network(WFNN) based direct adaptive control scheme for the solution of the tracking problem of mobile robots. To design a controller, we present a WFNN structure that merges advantages of neural network, fuzzy model and wavelet transform. The basic idea of our WFNN structure is to realize the process of fuzzy reasoning of wavelet fuzzy system by the structure of a neural network and to make the parameters of fuzzy reasoning be expressed by the connection weights of a neural network. In our control system, the control signals are directly obtained to minimize the difference between the reference track and the pose of mobile robot using the gradient descent(GD) method. In addition, an approach that uses adaptive learning rates for the training of WFNN controller is driven via a Lyapunov stability analysis to guarantee the fast convergence, that is, learning rates are adaptively determined to rapidly minimize the state errors of a mobile robot. Finally, to evaluate the performance of the proposed direct adaptive control system using the WFNN controller, we compare the control performance of the WFNN controller with those of the FNN, the WNN and the WFM controllers.

• Journal of Power Electronics
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• v.15 no.3
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• pp.730-740
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• 2015

This paper presents model reference adaptive system speed estimators based on Type-1 and Type-2 fuzzy logic controllers for the speed sensorless direct torque and flux control of an induction motor drive (IMD) using space vector pulse width modulation. A Type-1 fuzzy logic controller (T1FLC) based adaptation mechanism scheme is initially presented to achieve high performance sensorless drive in both transient as well as in steady-state conditions. However, the Type-1 fuzzy sets are certain and cannot work effectively when a higher degree of uncertainties occurs in the system, which can be caused by sudden changes in speed or different load disturbances and, process noise. Therefore, a new Type-2 FLC (T2FLC) - based adaptation mechanism scheme is proposed to better handle the higher degree of uncertainties, improve the performance, and is also robust to different load torque and sudden changes in speed conditions. The detailed performance of different adaptation mechanism schemes are performed in a MATLAB/Simulink environment with a speed sensor and sensorless modes of operation when an IMD is operates under different operating conditions, such as no-load, load, and sudden changes in speed. To validate the different control approaches, the system is also implemented on a real-time system, and adequate results are reported for its validation.