• International Journal of Control, Automation, and Systems
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• v.3 no.spc2
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• pp.302-307
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• 2005

A novel neuro controller based simple neuro-structure with modified error function is introduced in this paper. This controller consists of two independent controllers, known as the voltage regulator and the angular controller. The voltage regulator is used to modify terminal voltage for the purpose of tracking a reference voltage. The angular controller is utilized to guarantee the stability of the system. In this structure each neuron uses a linear hard limit activation function that depends on the controlled variable and its derivatives. There is no need for parameter identification or any off-line training data. Two proposed controllers are merged by a smooth switch to build a complete controller. The effectiveness of the proposed novel control action is demonstrated through some computer simulations on a Single-Machine Infinite-Bus (SMIB) power system.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.1
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• pp.111-121
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• 1995

A fuzzy control algorithm of bell-type membership functions and 9 rules is constructed for narrow range level control of steam generators in nuclear power plants. It is implemented at a field digital distributed controller, a Westinghouse-made controller called Westinghouse Distributed Processing Family(WDPF). Performance for level control of the developed fuzzy controller is compared with that of conventional controller, both at the field controller. For these comparisons, both the fuzzy control algorithm and the conventional PI control algorithm were carefully tuned. Also the sampling time for optimal performance was investigated. The results show that the fuzzy control algorithm is not only better in performance than the conventional algorithm but also much easier to be tuned by operators in the field.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.1
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• pp.88-94
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• 2001

In the position control system, the output of a controller is generally used as the input of a plant but the undesired noise is included in the output of a controller. Therefore, there is a need to use a precompensator for rejecting the undesired noise. In this paper, the expanded PID controller with a precompensator is constructed. The precompensator and PID controller are designed by a neural network with two-hidden layer and these coefficients are changed automatically to be a desired response of system when the response characteristic is changed under a condition.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.2
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• pp.178-184
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• 2004

In this paper, we designed an image processing system for the high speed line-scan camera which adopts the new memory model we proposed. As a resolution and a data rate of the line-scan camera are becoming higher, the faster image processing systems are needed. But many conventional systems are not sufficient to process the image data from the line-scan camera during a very short time. We designed the memory controller which eliminates the time for transferring image data from the line-scan camera to the main memory with high-speed SRAM and has a dual-port configuration therefore the DSP can access the main memory even though the memory controller are writing the image data. The memory controller is implemented by VHDL and Xilinx SPARTAN-IIE FPGA.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.1
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• pp.54-60
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• 2002

In this paper, we proposed a hybrid neural network-fuzzy controller which compensate a output of neural network controller. Even if learn by neural network controller, it can occur an bad results from disturbance or load variations. So in order to adjust above case, we used the fuzzy compensator to get an expected results. And the weight of main neural network can be changed with the result of loaming a inverse model neural network of Plant, so a expected dynamic characteristics of plant can be got. As the results of simulation through the second order plant, we confirmed that the proposed speed controller get a good response compare with a neural network controller. We implemented the controller using the DSP processor and applied in a hydraulic servo system. And then we observed an experimental results.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2006.06a
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• pp.85-88
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• 2006

Many control techniques have been proposed in order to improve the control performance of the discrete-time domain control system. In the position control system, the output of a controller is generally used as the input of a plant but the undesired noise is include in the output of a controller. In this paper, the neuro-network 2-DOF PID Controller is designed by a neural network and the gains of this controller are adjusted automatically by the back-propagation algorithm of the neural network when the response characteristic of system is changed under a condition.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.205-208
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• 2003

In this paper, we realized radio controller with Convolution code and CRC code to solve the wired and wireless controller's problem that is present industry spot. We used microprocessor as a controller, and analyzed testing data with and without Convolution code. Convolution code of constraint length k=3, symbols rate 1/2 dramatically improves the radio controller's fidelity, and the number of CRC bit is 16bit(2byte) and the polynomial of /Χ$^{15}$ ＋Χ$^{2}$＋1 is used.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.2
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• pp.146-150
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• 2009

An Intelligent active roll angle controller design algorithm is discussed. The detailed mathematical formulation and analysis are discussed, and then modeling and design method for active roll angle controller are presented. This paper proposes a design method based upon intelligent robust controller design algorithm to control actively roll angle for improving cornering performance problems. The intelligent robust controller is designed for steady speed driving vehicle system model with representation of steering angle and yaw angular velocity parameters for cornering stability. And the detailed formulation and analysis for the objective vehicle system are investigated.

• Journal of Biosystems Engineering
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• v.25 no.4
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• pp.301-310
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• 2000

An autonomous tractor system was developed and its performance was evaluated. The system consisted of a tractor system of and a remote control station. The tractor and the remote control station communicated each other via wireless modems. The tractor had a DGPS(differential global positioning system), sensors, a controller and a modem. The DGPS collected position data and the tractor status was estimated. The information of tractor status and sensors was transferred to the remote control station. Then, the control station determined the control data such as steering angles using a fuzzy controller. The fuzzy controller used the information from the DGPS, sensors, and GIS(geographic information system) data. The control data were obtained by remote signal processing at the control station The control data for autonomous operation were transferred to the tractor controller. The performances of an autonomous tractor were evaluated for various speeds, different initial positions and different initial headings. About 1.3 seconds of time lag was occurred in transferring the tractor status data and the control data. Compensation the time lag, about 27cm deviation was observed at the speed of 0.5m/s and 37cm at the speed of 1m/s. Error caused mainly by the time lag and it would be reduced by developing a full-duplex radio module for controlling the remote tractor.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.31 no.3
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• pp.264-271
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• 1995

This paper presents the data parallel processing method between a PC and a micro-controller. To implement the method a dual port RAM for a real time data processing is used. In general an A/D & D/AC card is used to send or receive the data into or from the external plant and the PC does only the computation of the A/D and the D/A data because the A/D & D/AC card does not have the ability of computation. In this study, a data parallel processing method in which the PC and micro-controller own a common dual port RAM, is introduced, so that the PC can compute the A/D and D/A data and control the plant simultaneously. The PC system with a micro-controller and the common dual port RAM is designed and its effectiveness is investigated experimentally considering the performance of both the computation of data and the controlling and monitoring the external plant.