• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.2
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• pp.58-69
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• 1998

A contrp; suste, fpr SCARA robot is designed for implememting a robust dynamic control algorithm. this study forcuses on the use of DSPs in the design of joint controllers and interfaces in between the host cotroller and four joint controllers and in between the joint controllers and four servo drives. The mechanical body of SCARA robot and the servo drives are selected from the commercially available ones. The four joint controllers, assigned to each joint one by one, are combined into a common system through a mother board hardwarewise and through the global memeory softwarewise. The mother board is designed to connect joint controllers onto the board through the slots adopting PC/104 bus structures. And, the global memory stores the common data which can be shared by joint controllers and the host computer directly, which virtually combines the whole system into one. To demonstrate the performance and efficienty of the sytem, a robust inverse dynamic algorithm is proposed and implemented for a faster and more precise control. The robust inverse dynamic algorithm is basically derived from an inverse dynamci algorithm and a PID compensator. Based upon the derived dynamic equitions of SCARA robot, the inverse dynamic algorithm is intitially implemented within 0.3 msec of the control cycle in this system. The algoithm is found to be not accurate enough for the high speed and precision tasks due to inherent modelling errors and time-varying factors. Therefore, a variable PID algorithm is combined with the inverse dynamic algorithm to support robustness of control performance. Experimental datfor the proposed algorithm are presented and compared with the result obtained from PID and inverse dynamic algorithm.

• Journal of the Korean Society for Precision Engineering
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• v.3 no.1
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• pp.29-39
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• 1986

An adaptive controller which is robust to the unknown load disturbance is developed for electro-hydraulic speed control systems. Since the load disturbance degrades the performance of the controller such as a steady state error and rise time in the conventional control system, appropriate adjustment of the controller is necessary in order to obtain the desired performances. The adaptation mechanism was designed to tune the feedforward gain, based upon minimization of ITAE (integral of time-multiplied absolute error) performance. The unknown load distrubance was identified by using an analog computer from the relationship between the velocity of the hydraulic motor and the load pressure. To evaluate the performance of the controller a series of simulations and experiments were conducted for various load conditions. Both results show that the proposed adaptive controller shows abetter performance than the conventional controller in terms of the steady state error and rise time.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.994-996
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• 2000

Switched reluctance motor generally operates in the magnetically saturated region because the saturation gives several benefits to its performance. This paper investigates the modelling and fuzzy tuning PI control of a nonlinear switched reluctance motor. The modelling is performed through neural network technique. Fuzzy auto-tuning PI control is designed for a robust performance in load and speed variations. Simulation and experimental results indicate better performances compared with simple PI control.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.8 no.1
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• pp.46-52
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• 1994

In this paper, we implemented the variable speed controller of an induction motor by the Fuzzy control algorithms, which recently is invoking the remarkable interest. As the fuzzy controller is designed on the base of expert's knowlede and experience, it is difficult to expect the perfect control performance of fuzzy controller. Therefore, the adjustment techniques for optimization of scale factors were presented to design the robust fuzzy controller comparing with conventional PI control the usefullness of proposed fuzzy controller was showed by the experimental results.

• Proceedings of the KIPE Conference
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• 2001.07a
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• pp.1-4
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• 2001

SRM(Switched Reluctance Motor) uses reluctance torque by pulse excitation control. SRM drives are much studied in electrical vehicles and industrial application due to the simple, robust mechanical structure and high speed characteristics. For the high performance control of SRM, it is necessary to synchronize the stator phase excitation with the rotor position. This paper proposes a new encoder for high performance excitation control of SRM. The proposed encoder has complex structures of incremental and absolute encoder. An each phase inductance profile can be synchronized with 4-bit absolute position signal and incremental pulses are used for speed detection. Low cost and simple manufacturing of SRM encoder is possible.

• Proceedings of the KIPE Conference
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• 1997.07a
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• pp.60-63
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• 1997

A new approach to the position sensor elimination of PM synchronous motor drives is presented in this study. Using the position sensing characteristics of PMSM itself, the actual rotor position as well as the machine speed can be estimated by adaptive flux observer and used as the feedback signal for the vector controlled PMSM drive. The adaptive speed estimation is achieved by model reference adaptive technique. The adaptive laws are derived by the Popov's hyperstability theory and the positivity concept. In order to verify the effectiveness of the proposed scheme, computer simulations are carried out for the actual parameters of a PM synchronous motor and the results well demonstrate that the proposed scheme provides a good estimation value of the rotor speed without mechanical sensor. It is also shown that the actual rotor position as well as the machine speed can be achieved under the variation of the magnet flux linkage. Since the flux linkages are estimated by the adaptive flux observer and used for the identification of the rotor speed, robust estimation of the rotor speed can be performed.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1868-1870
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• 2006

Neural network is used in many fields of control systems, but input-output patterns of a control system are not easy to be obtained and by using as single feedback neural network controller. And also it is difficult to get a satisfied performance when the changes of rapid load and disturbance are applied. To resolve those problems, this paper proposes a new algorithm which is the neural network controller. The new algorithm uses the neural network instead of activation function to control object at the output node. Therefore, control object is composed of neural network controller unifying activation function, and it supplies the error back propagation path to calculate the error at the output node. As a result, the input-output pattern problem of the controller which is resigned by the simple structure of neural network is solved, and real-time learning can be possible in general back propagation algorithm. Application of the new algorithm of neural network controller gives excellent performance for initial and tracking response and it shows the robust performance for rapid load change and disturbance. The proposed control algorithm is implemented on a high speed DSP, TMS320C32, for the speed of 3-phase induction motor. Enhanced performance is shown in the test of the speed control.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.541-543
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• 1998

Generally, PI control is simple and easy to implement and gains of PI control are determined by specifying a dynamics of the servo driver system. However, the gain-tuning is so difficult that it is relied on an expert's effort. This paper presents a gain auto-tuning method for PI controllers based on a fuzzy inference mechanism. First, the proposed fuzzy inference system identifies a system moment of inertia and adjusts control gains by using the difference in speed responses between a real plant and a reference model. Second, this paper proposes an improved fuzzy PI controller. To reduce the speed overshoot, we adapt a control method that selects a proper PI gains with respect to the load inertia variation. To prove the validity of the proposed gain tuning algorithm and the feasibility of the servo drive, a high performance servo drive will be implemented by DSP(TMS320C31) and intelligent power module (IPM). The proposed controller is applied to the speed control of the 300W AC servo motor. Some simulations and experimental results show that the proposed fuzzy PI controller is more robust than the conventional PI controller against the load inertia variation.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.12 no.4
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• pp.70-74
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• 1998

Robust control for DC motor is needed according to the highest precision of industrial automation. However, when a motor control system with PID contoller has an effect of load disturbance, it is very difficult to guarantee the robustness of control system. In this paper, PID-supervision hybrid control methods for motor control system (without the supervisory controller) is stable in the sense that the error is inside the constraint set, the supervisory control is idle. If the error hits the boundary of the constraint, the supervisory controller beings operation to force the error back to the constraint set. We prove that the PID-supervision hybrid control system is globally stable in the sense that the error is guaranteed to be within the tolerance limits specified by the system designer.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.1
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• pp.7-14
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• 2015

To implement an automatic picking system (APS) in distribution center with high precision and high dynamics, this paper presents a high gain observer-based robust speed controller design for a linear induction motor (LIM) drive. The force disturbance as well as the mechanical parameter variations such as the mass and friction coefficient gives a direct influence on the speed control performance of APS. To guarantee a robust control performance, the system uncertainty caused by the force disturbance and mechanical parameter variations is estimated through a high gain disturbance observer and compensated by a feedforward manner. While a time-varying disturbance due to the mass variation can not be effectively compensated by using the conventional disturbance observer, the proposed scheme shows a robust performance in the presence of such uncertainty. A Simulink library has been developed for the LIM model from the state equation. Through comparative simulations based on Matlab - Simulink, it is proved that the proposed scheme has a robust control nature and is most suitable for APS.