• Journal of Power Electronics
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• v.9 no.2
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• pp.173-179
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• 2009

This paper proposes a new three-phase diode rectifier system with a sinusoidal input current at unity power factor and a regulated and isolated output voltage at low level. The inherent natural wave-shaping capability of the reduced kVA polyphase transformer together with an active current wave-shaping technique results in a significant reduction of input and output filter requirements associated with switching ripple and EMI. The operation principles are described along with a design example and a comparative evaluation. Experimental results on a 1.5kW prototype are provided to validate the proposed concept.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.2
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• pp.112-119
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• 2003

Generally, PID controller is not suitable to control multi variable system because it is very difficult to tune the PID gains. However, this paper shows that it is not hard to tune the PID gains if we can find a Jacobian matrix of the system. The Jacobian matrix expresses the ratio of output variations according to input variations. It is possible to adjust the input values in order to reduce the output error using the Jacobian. When the colt function is composed of error related terms, the gradient approach can tune the PID gains to minimize the function. In simulation, a hydrofoil catamaran with two inputs and two outputs is applied as a multi variable system. We can easily get the multi variable PID controller by the proposed teaming method. When the controller is compared with LQR controller, the performance is as good as that of LQR controller with a modeling equation.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.5
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• pp.505-508
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• 2006

This paper presents a new analytical approach for designing multiloop PI controllers for disturbance rejection in multivariable processes with time delay. The proposed method is based on IMC-PID design approach. To overcome a sluggish load response by dominant pole in the process, the IMC filter is modified to compensate the dominant pole effect. Based on the modified IMC filter, an analytical tuning rule for multiloop PI controller is driven by extending the generalized IMC-PID method for single input/single output (SISO) systems [1] to multi input/multi output (MIMO) systems. Simulation results show that the proposed method gives a satisfactory load performance as well as servo performance in the multiloop system.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.06a
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• pp.525-526
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• 2008

For measuring nonlinear Vehicle Modeling based on 7-Depth Sensor, the neural networks are proposed m adaptive and in realtime. The structure of it is similar to recurrent neural networks; a delayed output as the input and a delayed error between the output of plant and neural networks as a bias input. In addition, we compute the desired value of hidden layer by an optimal method instead of transfering desired values by backpropagation and each weights are updated by RLS(Recursive Least Square). Consequently, this neural networks are not sensitive to initial weights and a learning rate, and have a faster convergence rate than conventional neural networks. This new neural networks is Error Estimated Neural Networks. We can estimate nonlinear models in realtime by the proposed networks and control nonlinear models.

• Proceedings of the KIPE Conference
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• 2013.07a
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• pp.275-276
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• 2013

In this paper, we proposed the Z-source four-switch three-phase rectifier. As we know, the conventional Four-Switch Three-Phase Rectifier(FSTPR) has advantages of the lower cost and less complex switching control. However, The conventional FSTPR can only either perform buck or boost operation, it can only attain the buck-boost operation by adding another DC-DC converter. In addition, besides its narrow output voltage region, distortion of the input current is serious either. Thus, we proposed the Z-source FSTPR which has buck-boost function and better input current waveform by applying the Z-impedance network to the conventional FSTPR. The validity of the proposed system was confirmed by experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.6
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• pp.608-613
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• 2006

Any input acceleration that bends RLG dithering axis causes flexure error, which is a source of the noncommutative error that can not be compensated by simply using integrated gyro sensor output. This paper introduces noncommutative error equations that define attitude errors caused by flexure errors. In this paper, flexure error is classified as sensor level error if the sensing axis coincides with the dithering axis and as system level error if the two axes do not coincide. The relationship between gyro output and the rotation vector is introduced and is used to define the coordinate transformation matrix and angular motion. Equations are derived for both sensor level and system level flexure error analysis. These equations show that RLG based INS attitude error caused by flexure is directly proportional to time, amount of input acceleration and the dynamic frequency of the vehicle.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.3
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• pp.406-412
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• 1998

This paper describes a contact position detection method of a capacitive touch screen panel. The proposed method is composed of a circuited compensating algorithm generating an output signal having phase difference to an input signal associated with contact position, converts both input and output signals into digital waveform (5V logic), and calculates the phase difference. Finally, position information with the phase difference is obtained by using a low-cost microprocessor, which is convenient to compensate non-linearity error. The proposed method, that computes phase difference directly, has advantages in feasibility and cost because it minimizes the use of analog devices; rather, it utilizes, cost effective digital circuit. Analytical results are also given.

• Proceedings of the KIPE Conference
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• 2011.07a
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• pp.314-315
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• 2011

This paper introduces the design and control method of braking chopper circuit which can supply input power to ventilation inverter of traction control system. The DC input voltage from auxiliary block (static inverter) is normally used as an input of ventilation inverter. It converts DC input to AC output voltage to drive cooling fans for traction control system and traction motors. The electrical braking force is very important for high speed train to guarantee safety even though the train is running in the dead section where the pantograph voltage is not supplied. When the high speed train decelerate speed in dead section, the regenerative energy is dissipated by braking resistor. This paper proposed the braking chopper control method to implement rheostatic braking function and the appropriate chopper circuit for supplying voltage source to ventilation inverter during rheostatic braking mode. The proposed chopper circuit makes it possible for traction control system to regenerate power continuously regardless of the existence of pantograph voltage. The feasibility of proposed braking chopper control and circuit were proven by inertia load test and actual train field test.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.5
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• pp.550-557
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• 1999

This paper describes a road-following controller using the proposed neural network for autonomous vehicle. Road-following with visual sensor like camera requires intelligent control algorithm because analysis of relation from road image to steering control is complex. The proposed neural network, relative similarity modular network(RSMN), is composed of some learning networks and a partitioniing network. The partitioning network divides input space into multiple sections by similarity of input data. Because divided section has simlar input patterns, RSMN can learn nonlinear relation such as road-following with visual control easily. Visual control uses two criteria on road image from camera; one is position of vanishing point of road, the other is slope of vanishing line of road. The controller using neural network has input of two criteria and output of steering angle. To confirm performance of the proposed neural network controller, a software is developed to simulate vehicle dynamics, camera image generation, visual control, and road-following. Also, prototype autonomous electric vehicle is developed, and usefulness of the controller is verified by physical driving test.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.2
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• pp.77-82
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• 2001

This paper deals with a fault detection algorithm for linear descriptor systems via unknown input PI observer. An unknown input PI observer is presented and its realization conditions is proposed by using the rank condition of system matrices. From the characteristics of unknown input PI observer, the states of system with unknown inputs are estimated and the occurrences of fault are detected, and its magnitudes are estimated easily by using integrated output estimation error under the step faults. Finally, a numerical example is given to verify the effectiveness of the proposed fault detection algorithm.