• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.7
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• pp.69-77
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• 1998

In this paper, a controller is designed for efficient controlling of video data with object-oriented feature. The need of controlling video data in an object unit is on the rise for the reason of rapidly growing demand for high-quality video services. We propose a programmable architecture with stack buffers which can minimize a scheduling overhead by having separate buffes for genral data and return addresses. The buffers are veyr useful for move and copy operations for multitasking and task switching. The controller offers extended instructions that process several data types including 32bit integrer type. Operation speed of the controller is from 77MHz to 44MHz.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.6
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• pp.269-279
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• 2020

This paper presents the design and implementation of embedded systems and autonomous path generation for autonomous speed sprayer. Autonomous Orchard Systems can be divided into embedded controller and path generation module. Embedded controller receives analog sensor data, on/off switch data and control linear actuator, break, clutch and steering module. In path generation part, we get 3D cloud point using Velodyne VLP16 LIDAR sensor and process the point cloud to generate maps, do localization, generate driving path. Then, it finally generates velocity and rotation angle in real time, and sends the data to embedded controller. Embedded controller controls steering wheel based on the received data. The developed autonomous speed sprayer is verified in test-bed with apple tree-shaped artworks.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1168-1172
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• 2004

This paper presents a speed controller based on an adaptive fuzzy algorithm for high performance permanent magnet synchronous motor (PMSM) drives under parameter and load variations. In many speed tracking control systems PI controller has been used due to its simple structure and easy of design. PI controller, however, suffers from the electrical machine parameter variations and disturbances. In order to improve the tracking control performance under load variations, the PI controller parameters are modified during operation by adaptive fuzzy method. This method based on optimal fuzzy logic system has simple structure and computational simplicity. It needs only sample data which is obtained by optimal controller off-line. As the sample data implemented in the adaptive fuzzy system can be modified or extended, a flexible control system can be obtained. Simulation results show the usefulness of the proposed controller.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.1142-1144
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• 2003

This Paper presents a speed controller based on the adaptive fuzzy tuning method for brushless DC(BLDC) motor drives under load variations. Generally, the speed tracking control systems use PI controller due to its simple structure and easy of design. PI controller, however, suffers from the electrical machine parameter variations and disturbances. In order to improve the tracking control performance under load variations, PI controller of which the parameters are modified during operation by adaptive fuzzy tuning method. This method based on optimal fuzzy logic system has simple structure and computational simplicity. It needs only sample data which is obtained by optimal controller off-line. As the sample data implemented in the adaptive fuzzy system can be modified or extended, a flexible control system can be obtained. Simulation results show the usefulness of the proposed controller.

• 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.

• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.61-65
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• 2000

In this paper We have developed the high-speed controller for haptic control. The proposed controller is based on the PCI/FPGA technology which can calculate the real position and transmit the force data to device rapidly. The haptic system is composed of 6DOF force display device high-speed controller. The developed system will be used on constructing the dynamical virtual environment. To show the efficiency of our system we designed simulation program of force-reflecting. As the result of the experiment we found that the controller has much higher resolution than some other controller It is so efficient in a 1 PC-based system with 1[kHz] haptic interrupt cycle.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1129-1132
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• 1993

This paper presents the idea of a neural fuzzy controller with application to the control of an industrial machining process. The structure of such a controller, which links the idea of a fuzzy controller and a neural network, is suggested. Results of comparative simulations indicate that the proposed neural fuzzy controller performs equally well as a fuzzy logic controller; moreover, it is more flexible and allows faster data processing.

• International journal of advanced smart convergence
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• v.12 no.1
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• pp.31-40
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• 2023

This asymed drone controller is indispensable for two components: Guidance and Controller. In which the Ministry of Guidance will receive waypoints from which to form an orbit then combine the data with the current location of the vessel, thereby calculating and also supplying the controller to drive the vehicle to follow the outlined trajectory. This article will use the Line Of Sight (LOS) algorithm to design the Guidance and Controller sets. The result as well as the effectiveness of the controller will be shown through matlab/SIMULINK simulation.

• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.3
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• pp.235-249
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• 2018

The Artificial Neural Network (ANN) model has been known as one of the most effective theories for automatic ship berthing, as it has learning ability and mimics the actions of the human brain when performing the stages of ship berthing. However, existing ANN controllers can only bring a ship into a berth in a certain port, where the inputs of the ANN are the same as those of the teaching data. This means that those ANN controllers must be retrained when the ship arrives to a new port, which is time-consuming and costly. In this research, by using the head-up coordinate system, which includes the relative bearing and distance from the ship to the berth, a novel ANN controller is proposed to automatically control the ship into the berth in different ports without retraining the ANN structure. Numerical simulations were performed to verify the effectiveness of the proposed controller. First, teaching data were created in the original port to train the neural network; then, the controller was tested for automatic berthing in other ports, where the initial conditions of the inputs in the head-up coordinate system were similar to those of the teaching data in the original port. The results showed that the proposed controller has good performance for ship berthing in ports.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.731-736
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• 1994

Experiment on a lab-scale pH process is carried out to evaluate the control performance of the neural linearizing control scheme(NLCS) using a radial basis function(RBF) network which was previously proposed by Kim and Park. NLCS was developed to overcome the difficulties of the conventional neural controllers which occur when they are applied to chemical processes. Since NLCS is applicable for the processes which are already controlled by a linear controller and of which the past operating data are enough, we first control the pH process with PI controller. Using the operating data with PI controller, the linear reference model is determined by optimization. Then, a IMC controller replaces the PI controller as a feedback controller. NLCS consists of the IMC controller and a RBF network. After the learning of the neural network is fully achieved, the dynamics of the process combined with the neural network becomes linear and close to that of the linear reference model and the control performance of the linear control improves. During the training, NLCS maintains the stability and the control performance of the closed loop system. Experimental results show that the NLCS performs better than PI controller and IMC for both the servo and the regulator problems.