• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1726-1727
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• 2007

In this paper, a systematic guideline is introduced to design a stable adaptive fuzzy wavelet controller with sliding mode for a class of uncertain nonlinear systems. Based on the Lyapunov synthesis approach, we construct the fuzzy wavelet controller such that it can basically control and guarantee the stability of the whole control system. On the other hand, a robust controller is design to restrain or eliminate the disturbance and assure the desired output accuracy of a control system. Some experimental results for a chaotic system are provided here to demonstrate the effectiveness of the control algorithm.

• Proceedings of the KIEE Conference
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• 1997.07f
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• pp.2088-2090
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• 1997

This paper consists of the speed sensorless vector control of induction motors with the estimation of rotor resistance. In the application of variable-speed induction motor drives, if an inaccurate rotor resistance is used because the rotor resistance can change due to skin effects and temperature variables, it is difficult to achieve a collect field orientation. In this paper, to overcome these difficulties adaptive algorithm is designed for rotor resistance identification. The proposed adaptive algorithm for rotor resistance estimation in the synchronous reference frame is applied by sliding mode current controller satisfing persistent excitation(PE) condition. Adaptive flux observer is here used for the purpose of estimating rotor flux and speed in the speed sensorless scheme. Computer simulations are carried out to verify the validity of the proposed algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.1
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• pp.63-69
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• 2003

The main property of VSC is that the system response is robust and insensitive to parameter variations and external disturbances in the sliding mode if their bounds are known to the designer of the system control. But sometimes these bounds may not be easily obtained. However, fuzzy control provides an effective way to design the controller of the system with the disturbances and parameter variations. Therefore, combination of the best feature of fuzzy control and sliding mode control is considered. When using the conventional VSC, generally the reaching phase problem occurs, which cause the system response to be sensitive to parameter variations and external disturbances. In order to overcome these problems, a robust position control method of the BLDC motor using an adaptive fuzzy VSC without leaching phase is presented.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.7
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• pp.75-84
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• 2003

To reduce the effects of the uncertainties due to the modeling error and aerodynamic coefficients, a nonlinear adaptive control system based on neural networks is proposed . Neural networks parameters are adjusted by using an adaptive law. The sliding mode control scheme is used to compensate for the effect of the approximation error of neural networks. Control parameters and neural networks structures are optimized to obtain better performance by using the genetic algorithm. By introducing the concept of multi-groups of populations, the genetic algorithm is modified so that individuals and groups can be simultaneously evolved . To verify the performance of the pro posed algorithm, the optimized neural networks control system is applied to an aircraft longitudinal dynamics.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.902-906
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• 2008

The linear motors are easily affected by load disturbance, force ripple, friction, and parameter variations because there is no mechanical transmission to reduce the effects of model uncertainties and external disturbance. For highspeed/high-accuracy position control of a linear-motor-driven two axes, a nonlinear adaptive controller including a cross-coupling algorithm is designed in this paper. The nonlinear effects such as friction and force ripple are estimated and compensated. An enhanced approach for cross-coupling algorithm is proposed to effectively improve the biaxial contour accuracy with the closed-loop stability. The proposed controller is evaluated through the computer simulations.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.9 no.1
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• pp.54-62
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• 1995

This paper is a study on a speed control of an induction motor used the MRA-DSM(Mode1 Reference Adaptive-Discrete Sliding Mode) controller. In this paper, when controls motor speed, DSM algorithm is proposed for having Robustness against disturbance and parameter variation. and it is also proposed MRA-DSM including the additional load model reference algorithm, which can be compensated the discontinuous control imputs at sliding mode and followed the model Preference independent of parameter variation of control subjects. The control system is composed of the parallel processing control system using the microprocessor for maximizing the performance of control systems and the real time processing. Also it simplifies the hardware composed of controlling the system by software and improves the reliability of the system. And while MRA-DSM control, faster response characteristics of 27.2 % is obtained than DSM control.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.2
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• pp.119-123
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• 2007

This paper investigates a speed sensorless control of induction motor. The control strategy is based on MRAS(Model Reference Adaptive System) using load-torque observer as a reference model for flux estimation. The speed response of conventional MRAS controller characteristics is affected by variations of load torque disturbance. In the proposed system, the speed control characteristics using a load-torque observer control isn't affected by a load torque disturbance. Control algorithm that propose whole system through MATLAB SIMULINK because do modelling simulation result are presented to prove the effectiveness of the adaptive sliding mode controller for the drive variable load of induction motor. Therefore we hope to be extended in industrial application.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1646_1647
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• 2009

In this paper, Takagi-Sugeno(T-S) fuzzy controller and search method are developed for efficiency optimization of induction motors(IMs). The proposed control scheme consists of efficiency controller and adaptive backstepping controller. A search controller for which information of input of T-S fuzzy controller is included in efficiency controller that uses a direct vector controlled induction motor. A sliding mode observer is designed to estimate rotor flux and an adaptive backstepping controller is used to control of speed of IMs. Simulation results are presented to validate the proposed controller.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1628-1631
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• 2005

Ship Autopilots are usually designed based on the PD and Pill controllers because of simplicity, reliability and easy to construct. However their performance in various environmental conditions is not as good as desired. This disadvantage can be overcome by adjusting works or constructing adaptive controllers. But those methods are complex and not easy to do. This paper presents a new method for constructing a Ship Autopilot based on the combination of Fuzzy Logic Control (FLC) and Linear Control Theory (Pill control). The new Ship Autopilot has the advantages of both the Pill and FLC control methodologies: easy to construct, and optimal control laws can be established based on ship masters' knowledge. Therefore, the new ship autopilot can be well adapted with parameter variations and strong environment effects. Simulation using MATLAB software for a ship with real parameters shows high effectiveness of the Fuzzy Pill autopilot in course keeping and course changing manoeuvres in comparison with the ordinary Pill ship autopilots.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.133-136
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• 1999

Many researches on the identification of a system have been carried out using a least square method, an adaptive filter, and so on. However, it is difficult to apply these methods in a nonlinear system. In the case of a nonlinear system, it is known that the signal compression method is able to estimate uncertain parameters of linear element in a nonlinear system because it is able to separate linear element and nonlinear element in a nonlinear system. However, the signal compression method cannot be applied to a motion simulator because actuators of the simulator is single-rod cylinders which includes expansion and compression dynamic properties. Therefore, this paper proposes a modified signal compression method which is able to estimate uncertain parameters of the motion simulator dynamics. The dynamic properties of this system are identified by separating expansion and compression properties when applying the signal compression method. And then, the identified parameters are applied to design a sliding mode controller for the simulator. The performance of the designed sliding mode controller is evaluated experimentally.