• Journal of Power Electronics
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• v.9 no.1
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• pp.109-116
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• 2009

This paper addresses the output control of a utility-connected double-fed induction machine (DFIM) for wind power generation systems (WPGS). DFIM has a back-to-back converter to control outputs of DFIM driven by the wind turbine for WPGS. To supply commercially the power of WPGS to the grid without any problems related to power quality, the real and reactive powers (PQ) at the stator side of DFIM are strictly controlled at the required level, which in this paper is realized with the Fuzzy PI controller based on the field orientation control. For the Sinusoidal Pulse Width Modulation (SPWM) converter connected to the rotor side of DFIG to maintain the controllability of PQ at the state side of DFIM, the DC voltage of the DC link capacitor is also controlled at a certain level with the conventional Proportion-Integral (PI) controller of the real power. In addition, the power quality at the grid connected to the rotor side of DFIM through the back-to-back converter is maintained in a certain level with a PI controller of the reactive power. The controllers for the PQ at the stator side of DFIM, the DC link voltage of the back-to-back inverter and the reactive power at the grid connected to the rotor side of DFIM are designed and simulated in the PSIM program, of which the result verifies the performance of the proposed controllers.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.11
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• pp.31-35
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• 1992

This paper presents a decentralized adaptive controller design for a robot manipulator to track the given desired trajectory in the joint space. The controller is of distributed structure and does not require the complex manipulator dynamic model, thereby it is computationally very efficient. Each joint is independently controlled by a PID feedback part and a velocity-acceleration feedforward part. Simulation results for a two-link direct drive manipulator conform that the proposed decentralized scheme is feasible.

• Management & Information Systems Review
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• v.2
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• pp.335-354
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• 1998

In this study I construct CAN(Controller Area Network) for automobiles similar to LAN(Local Area Network) and build communication modules in the major part of an automobile to link several sub-systems. Since each station replaces the communication function of sub-systems and has various types of sensor, actuator, controller, and switch, every information about automobile's status is obtained from the network. The manufactured system showed a superior capability. The following is the contents of study. 1. The definition of communication packet through the analysis of CAN protocol. 2. The Design of modules using micro-controller 80C196CA. 3. The Network configuration.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.3
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• pp.316-325
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• 1991

This paper presents the design of a new sliding mode controller to improve the rate of convergence by Lyapunov's stability analysis. The proposed controller shows that the elimination of the steady state position errors can be achieved by replacing the desired trajectory by the virtual reference trajectory. The proposed control scheme which consists of the upper bounded and estimated values of eac term of the manipulator dynamic equation does not require good knowledge of the parameters and the computation of matrix inversion. The performance of proposed controller is evaluated by the simulation for a two-link manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.177-182
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• 1989

In this paper a new adaptive control algorithm is derived, with the unknown manipulator and payload parameters being estimated online. In practice, we may simplify the algorithm by not explicity estimating all unknown parameters. Further, the controller must be robust to residual time-varying disturbance, such as striction or torque ripple. Also, the reference model is a simple douple integrator and the acceleration input for robot manipulator consists of a proportion and derivative controller for trajectory tracking purposes. The validity of this control is confirmed in simulation where two-link robot manipulator shows the robust performances in spite of the existing nonlinear interaction and unknown parametrictings

• Journal of the Korean Society for Precision Engineering
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• v.23 no.9 s.186
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• pp.92-101
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• 2006

In this paper a adaptive backstepping control scheme is proposed for control of a do motor driving a one-link manipulator. Fuzzy logic systems are used to approximate the unknown nonlinear function including the parametric uncertainty and disturbance throughout the entire electromechanical system. A compensation controller is also proposed to estimate the bound of approximation error. Thus the asymptotic stability of the closed-loop control system can be obtained. Numerical simulations are included to show the effectiveness of the proposed controller.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.13-17
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• 1990

In this paper we propose the force controller using a neural network for a redundant manipulator. Jacobian transpose matrix of a redundant manipulator constructed by a neural network is trained by using a feedback torque as an error signal. If the neural network is sufficiently trained well, the kinematic inaccuracy of a manipulator is automatically compensated. The effectiveness of the proposed controller is demonstrated by computer simulation using a three-link planar robot.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.74-74
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• 2000

This paper presents a neural network controller for a rigid-link electrically-driven robot. The proposed controller is designed in conjunction with three neural networks approximating for complicated nonlinear functions. Particularly, the fact, different from conventional schemes, is that the neural network based current observer is used. Therefore, no accurate measurement of the actuator driving current is required. In the proposed controller-observer scheme, the derived weight update rule guarantees the stability of closed-loop system in the sense of Lyapunov. The effectiveness and performance of the proposed method are demonstrated through computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.420-420
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• 2000

In this paper, we propose an adaptive controller using RBFN(radial basis function network) for robot manipulators The structure of the proposed controller consists of a RBFN and VSC-1 ike control. RBFN is used in order to approximate かon system, and VSC-like control to guarantee robustness On the basis of the Lyapunov stability theorem, we guarantee the stability for the total system. And the learning law of RBFN is established by the Lyapunov method, Finally, we apply the proposed controller to tracking control for a 2 link SCARA type robot manipulator.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.435-438
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• 2002

In this paper, a robust controller is proposed to control a robot manipulator which is governed by highly nonlinear dynamic equations. The controller is computationally efficient since it does not require the dynamic model or parameter values of a robot manipulator. It, however, requires uncertainty bounds which are derived by using properties of serial link robot dynamics. The stability of the robot with the controller is proved by Lyapunov theory. The results of computer simulations show that the robot system is stable, and has excellent trajectory tracking performance.