• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.2
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• pp.231-236
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• 2012

This paper presents the MPPT(Maximum Power Point Tracking)control method of the PMSG wind generation system using the turbine model with a squirrel cage induction motor. The torque of squirrel cage induction turbine model is controlled by mathematization of speed characteristics of real blade. In this paper, maintenance and cost issues into consideration, except for previous method using information of the velocity of the wind speed sensor, the algorithm is presented. The algorithm is controlled by tracking the optimal point, the generator speed and maximum grid power. The vector controls of the generator side converter and the grid side converter are controlled respectively to obtain maximum torque and regulate unity power factor. With Psim simulations and experiments, the efficiency of squirrel cage induction turbine model and the validity of control algorithm are verified.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.69-72
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• 1996

This paper considers a global resolution of kinematic redundancy under inequality constraints as a constrained optimal control. In this formulation, joint limits and obstacles are regarded as state variable inequality constraints, and joint velocity limits as control variable inequality constraints. Necessary and sufficient conditions are derived by using Pontryagin's minimum principle and penalty function method. These conditions leads to a two-point boundary-value problem (TPBVP) with natural, periodic and inequality boundary conditions. In order to solve the TPBVP and to find a global minimum, a numerical algorithm, named two-stage algorithm, is presented. Given initial joint pose, the first stage finds the optimal joint trajectory and its corresponding minimum performance cost. The second stage searches for the optimal initial joint pose with globally minimum cost in the self-motion manifold. The effectiveness of the proposed algorithm is demonstrated through a simulation with a 3-dof planar redundant manipulator.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.1
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• pp.48-55
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• 2005

Mobility of an indoor wheeled robot is affected by adhesion force that is related to various floor conditions. When the adhesion force between driving wheels and floor decreases suddenly, the robot begins slip. In order to overcome this slip problem, optimal slip velocity must be decided for stable movement of wheeled robot. First of all, this paper shows that conventional PI control can not be applied to a wheeled robot of the light weight. Secondly, proposed fuzzy logic is applied to the Takagi-Sugeno model for the configuration of fuzzy sets. For the design of Takagi-Sugeno model and fuzzy rule, proposed algorithm uses FCM(Fuzzy c-mean clustering method) algorithm. In additionally, this algorithm adjusts the driving torque for restraining re-slip. The proposed fuzzy logic controller(FLC) is pretty useful with prevention of the slip phenomena for the controller performance in the re-adhesion control strategy, These procedures are implemented using a Pioneer 2-DXE wheeled robot parameter.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2012.10a
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• pp.261-262
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• 2012

In this research, intelligent protection system for laser boat is introduced. The function of system is to measure the distance and velocity of object from our boat and generate control signals to avoid collision with moving targets. A novel approach to estimate object's position from our ship is tackled on this paper. To do this laser sensors are used to measure distance from ship to targets. The ship position and velocity is estimated by th Kalman filter algorithm. In the real phase, the filtering method will be applied to process signal gathered by laser sensors. Simulation to estimate ship's position and velocity under noise are executed and the results are introduced to show the effectiveness of the algorithm.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.8
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• pp.86-93
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• 2003

The development of a fast, accurate, and inexpensive position-controlled pneumatic actuator that may be applied to a variety of practical positioning applications with various external loads is described in this paper. A novel modified pulse width modulation (MPWM) valve pulsing algorithm allows on/off solenoid valves to be used in place of costly servo valves. A comparison between the system response of standard PWM technique and that of the novel modified PWM technique shows that the control performance is significantly increased. A state feedback controller with position, velocity and acceleration feedback is successfully implemented as the continuous controller. Switching algorithm of control parameter using learning vector quantization neural network (LVQNN) is newly proposed, which estimates the external loads of the pneumatic actuator. The effectiveness of the proposed control algorithms are demonstrated through experiments with various loads.

• Structural Engineering and Mechanics
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• v.30 no.6
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• pp.679-698
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• 2008

On marine vessels, delicate instruments such as navigation radars are normally mounted on ship masts. However the vibrations at the top of mast where the radar is mounted often cause serious deterioration in radar-tracking resolution. The most serious problem is caused by the rotational vibrations at the top of mast that may be due to wind loading, inertial loading from ship rolling and base excitations induced by the running propeller. This paper presents a method of semi-active vibration control using magneto-rheological (MR) dampers to reduce the rotational vibration of the mast. In the study, the classical optimal control algorithm, the independent modal space control algorithm and the double input - single output fuzzy control algorithm are employed for the vibration control. As the phenomenological model of an MR damper is highly nonlinear, which is difficult to analyse, a back- propagation neural network is trained to emulate the inverse dynamic characteristics of the MR damper in the analysis. The trained neural network gives the required voltage for each MR damper based on the displacement, velocity and control force of the MR damper quickly. Numerical simulations show that the proposed control methods can effectively suppress the rotational vibrations at the top of mast.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.6
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• pp.74-80
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• 2009

Path tracking of unmanned vehicle is a basis of autonomous driving and navigation. For the path tracking, it is very important to find the exact position of a vehicle. GPS is used to get the position of vehicle and a direction sensor and a velocity sensor is used to compensate the position error of GPS. To detect path lines in a road image, the bird's eye view transform is employed, which makes it easy to design a lateral control algorithm simply than from the perspective view of image. Because the driving speed of vehicle should be decreased at a curved lane and crossroads, so we suggest the speed control algorithm used GPS and image data. The control algorithm is simulated and experimented from the basis of expert driver's knowledge data. In the experiments, the results show that bird's eye view transform are good for the steering control and a speed control algorithm also shows a stability in real driving.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.6
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• pp.182-193
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• 2000

Several metrics have been used in crash discrimination algorithms in order to have timely air bag deployment during all frontal crash modes. However, it is still challengine to have timely air bag deployment especially during the oblique, the pole and the underride crash mode. Therefore, in this paper a new crash discrimination algorithm was proposed, using the absolute value of the deceleration change multiplied by the velocity change as a metric, and processing the metric as a function of the velocity change. The new algorithm was applied for all frontal crash modes of a minivan and a sports utility vehicle, and it resulted in timely air bag deployment for all frontal crash modes including the oblique, the pole and the underride crash mode. Moreover, it was proposed that an accelerometer be installed at each side of the rails, rockers or pillars to assess the crash severity of each side and to deploy the frontal air bags at different time especially during an asymmetric crash such as an oblique and an offset crash. As an example, the deceleration pulses measured at the left and right B-pillar·rocker locations were processed through the new algorithm, and faster time-to-fires were obtained for the air bag at the struck side for the air bag at the other side.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.173-182
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• 2005

In this paper, a target tracking algorithm for tracking maneuvering vehicles is presented. The overall algorithm belongs to the category of an interacting multiple-model (IMM) algorithm used to detect multiple targets using fused information from multiple sensors. First, two kinematic models are derived: a constant velocity model for linear motions, and a constant-speed turn model for curvilinear motions. Fpr the constant-speed turn model, a nonlinear information filter is used in place of the extended Kalman filter. Being equivalent to the Kalman filter (KF) algebraically, the information filter is extended to N-sensor distributed dynamic systems. The model-matched filter used in multi-sensor environments takes the form of a federated nonlinear information filter. In multi-sensor environments, the information-based filter is easier to decentralize, initialize, and fuse than a KF-based filter. In this paper, the structural features and information sharing principle of the federated information filter are discussed. The performance of the suggested algorithm using a Monte Carlo simulation under the two patterns is evaluated.

• Proceedings of the KIPE Conference
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• 2009.11a
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• pp.135-138
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• 2009

In this paper, a novel maximum power point tracking (MPPT) for a PMSG-based variable speed wind power system is proposed using the fuzzy logic algorithm. The control algorithm is developed based on the normal hill climb searching (HCS) method, commonly used in wind energy conversion systems (WECS). The inputs of fuzzy-based controller are the derivations of DC output power and the step size of DC/DC converter duty cycles. The main advantages of the proposed MPPT method are no need to measure the wind velocity and the generator rotational speed. As such, the control algorithm is independent of turbine characteristics, achieving the fast dynamic responses with non-linear fuzzy systems. The effectiveness of the proposed MPPT strategy has been verified through the simulated results.