• Journal of the Korea Institute of Military Science and Technology
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• v.3 no.2
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• pp.71-80
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• 2000

In Underwater Flight Vehicle depth control system, the followings must be required. Firstly, It need robust depth control performance which can get over parameter variation, modeling error and disturbance. Secondly, It need no oveshoot phenomenon to avoid colliding with ground surface and obstables. Thirdly, It need continuous control input to reduce the acoustic noise and propulsion energy consumption. Finally, It need effective interpolation method which can reduce the dependency of control parameters on speed. To solve these problems, we propose the Fuzzy-PID depth controller with the control parameter interpolators. Simulation results show the proposed control scheme has robust and accurate performance with continuous control input.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.6
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• pp.526-531
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• 2012

This paper, we describe the vector control of surface mounted PMSM (Permanent Magnet Synchronous Motor) using the fuzzy controller which is suggested algorithm. In these days, when vehicle is operated or not, whether the road is covered or not, the sensitivity of the steering column is not stable. To make up for it, the PI gain of a steering column controller is adjusted by experience. It becomes the price because it need a lot of sensor. Also it is difficult to implement robust control because we need a lot of parameters for variable road conditions which are the off road, the on road, a low battery voltage, a high battery voltage, a vehicle speed. In this paper, we propose fuzzy controller using the suggested algorithm which suitable for steering system. We test the fuzzy controller with the various condition. We get the good performance of fuzzy controller even if it is nonlinear system. We check a robust the fuzzy controller using the suggested algorithm.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.1
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• pp.37-46
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• 2004

A novel rotor speed estimation method using model reference adaptive control(MRAC) is proposed to improve the performance of a sensorless vector controller. In the proposed method, the stator current is used as the model variable for estimating the speed. In conventional MRAC methods, the relation between the two model errors and the speed estimation error is unclear. In the proposed method, the stator current error is represented as a function of the first degree for the error value in the speed estimation. Therefore, the proposed method can produce a fast speed estimation. The robustness of the rotor flux-based MRAC, back EMF-based MRAC, and proposed MRAC is compared based on a sensitivity function about each error of stator resistance, rotor time constant, mutual inductance. Consequently, the proposed method is much more robust than the conventional methods as regards errors in the mutual inductance, stator resistance. Therefore, the proposed method offers a considerable improvement in the performance of a sensorless vector controller at a low speed. In addition, the superiority of the proposed method and the validity of sensitivity functions were verified by simulation and experiment.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.4
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• pp.427-432
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• 1998

There are many demands for ship control system and many studies have been proposed. For example, if a ship diesel engine is operated by consolidated control with Controllable Pitch Propeller(CPP), the minimum fuel consumption is achieved, satisfying the demanded ship speed. For this, it is necessary that the ship is operated on the ideal operating line which satisfies the minimum fuel consumption. In this context of view, this paper presents a controller design method for a ship propulsion system with CPP by Linear Matrix Inequality(LMI) which satisfies the given $H_{\infty}$ control performance and robust stability in the presence of physical parameter perturbations. The validity and applicability of this approach are illustrated through a simulation in the all operating ranges.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.5
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• pp.977-983
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• 2011

This paper proposes a new adaptive speed controller to achieve a robust speed control of a permanent magnet synchronous motor(PMSM). The proposed adaptive regulator does not require any information on the motor parameter and load torque values, so it is very insensitive to model parameter and load torque variations. Also, the stability of the proposed adaptive control system is proven. To validate the robustness of the proposed adaptive speed controller, both simulation and experimental results are provided under motor parameter and load torque variations. It is clearly demonstrated that the proposed adaptive regulator can accurately control the speed of permanent magnet synchronous motors.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.1088-1090
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• 2002

This paper described a robust control of an induction motor using a disturbance cancellation observer of a feedforward control. The speed response of conventional PI controller characteristic is affected by variations of load torque disturbance. In the proposed system. the speed control characteristic using a feedforward control isn't affected by a load torque disturbance.

• Proceedings of the KIPE Conference
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• 2002.07a
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• pp.150-153
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• 2002

This paper designed a robust control of an induction motor using a disturbance cancellation observer of a feedforward control. The speed response of conventional Pl controller characteristic is affected by variations of load torque disturbance. In the proposed system the speed control characteristic using a feedforward control isn't affected by a load torque disturbance.

• Proceedings of the KIPE Conference
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• 2003.07b
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• pp.816-819
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• 2003

This paper described a robust control of an induction motor using a disturbance cancellation observer of a feedforward control with Matlab simulink. The speed response of conventional PI controller characteristics is affected by variation of load torque disturbance. In this system, the speed control characteristics using a feedforward control toughen about a load torque disturbance.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.404-408
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• 2001

This paper deals with speed control of induction motors with a gain tuning based on simple Genetic Algorithms, which are search algorithms based on the mechanics of natual selection and genetics. Based on the designed control system structure, the indirect vector control system of induction motors is simulated. The simulation results show that the system has a strong robust to the parameter variation and is insensitive to the load disturbance. Thus, the proposed PI controller based on genetic algorithms is superior to manually tuned classical PI controller in improving the speed control performance of induction motors.

• Journal of Electrical Engineering and information Science
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• v.2 no.6
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• pp.82-89
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• 1997

In this paper, an adaptive speed controller with an FNN(Feedforward Neural Network) is proposed for servo motor drives. Generally, the motor system has nonlinearities in friction, load disturbance and magnetic saturation. It is necessary to treat the nonlinearities for improving performance in servo control. The FNN can be applied to control and identify a nonlinear dynamical system by learning capability. In this study, at first, a robust speed controller is developed by Lyapunov stability theory. However, the control input has discontinuity which generates an inherent chattering. To solve the problem and to improve the performances, the FNN is introduced to convert the discontinuous input to continuous one in error boundary. The FNN is applied to identify the inverse dynamics of the motor and to control the motor using coordination of feedforward control combined with inverse motor dynamics identification. The proposed controller is developed for an SR motor which has highly nonlinear characteristics and it is compared with an MRAC(Model Reference Adaptive Controller). Experiments on an SR motor illustrate te validity of the proposed controller.