• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.881-886
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• 1993

Fuzzy logic rule-based controller has many desirable advantages, which are simple to implement on the real time and need not the information of structure and dynamic characteristics of the system. Thus, nowadays, the scope of the application of the fuzzy logic controller becomes enlarged. But, if the controlled plant is a time-varying and nonlinear system, it is not easy to construct the fuzzy logic rules which usually need the knowledge of an expert. In this paper, an approach in which the logic control rules can be self-organized using genetic algorithm will be proposed and the effectiveness of the proposed method will be verified by computer simulation of the 2 d.o.f. planar robot manipulator.

• Journal of Ocean Engineering and Technology
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• v.38 no.3
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• pp.115-123
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• 2024

USBL systems are essential for providing accurate positions of autonomous underwater vehicles (AUVs). On the other hand, the accuracy can be degraded by outliers because of the environmental conditions. A failure to address these outliers can significantly impact the reliability of underwater localization and navigation systems. This paper proposes a novel outlier rejection algorithm for AUV localization using Voronoi diagrams and query point calculation. The Voronoi diagram divides data space into Voronoi cells that center on ultra-short baseline (USBL) data, and the calculated query point determines if the corresponding USBL data is an inlier. This study conducted experiments acquiring GPS and USBL data simultaneously and optimized the algorithm empirically based on the acquired data. In addition, the proposed method was applied to a sensor fusion algorithm to verify its effectiveness, resulting in improved pose estimations. The proposed method can be applied to various sensor fusion algorithms as a preprocess and could be used for outlier rejection for other 2D-based location sensors.

• Journal of international Conference on Electrical Machines and Systems
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• v.3 no.2
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• pp.176-183
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• 2014

Three-phase four-wire distribution systems are used for both three-phase three-wire loads and single-phase two-wire consumer appliances in South Korea, Myanmar and other countries. Unbalanced load conditions frequently occur in these distribution systems. These unbalanced load conditions cause unbalanced voltages for three-phase and single-phase loads, and increase the loss in the distribution transformer. In this paper, we propose constant DC capacitor voltage control based strategy for the active load balancer (ALB) in the three-phase four-wire distribution systems. Constant DC capacitor voltage control is always used in active power line conditioners. The proposed control strategy does not require any computation blocks of the active and reactive currents on the distribution systems. Balanced source-side currents with a unity power factor are obtained without any calculation block of the unbalanced active and reactive components on the load side. The basic principle of the constant DC capacitor voltage control based strategy for the ALB is discussed in detail and then confirmed by both digital computer simulations using PSIM software and prototype experimental model. Simulation and experimental results demonstrate that the proposed control strategy for the ALB can balance the source currents with a unity power factor in the three-phase four-wire distribution systems.

• Science of Emotion and Sensibility
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• v.15 no.4
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• pp.503-516
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• 2012

According to the researches of robot and software agent until now, computational emotion model is dependent on system, so it is hard task that emotion models is separated from existing systems and then recycled into new systems. Therefore, I introduce the Engine of computational Emotion model (shall hereafter appear as EE) to integrate with any robots or agents. This is the engine, ie a software for independent form from inputs and outputs, so the EE is Emotion Generation to control only generation and processing of emotions without both phases of Inputs(Perception) and Outputs(Expression). The EE can be interfaced with any inputs and outputs, and produce emotions from not only emotion itself but also personality and emotions of person. In addition, the EE can be existed in any robot or agent by a kind of software library, or be used as a separate system to communicate. In EE, emotions is the Primary Emotions, ie Joy, Surprise, Disgust, Fear, Sadness, and Anger. It is vector that consist of string and coefficient about emotion, and EE receives this vectors from input interface and then sends its to output interface. In EE, each emotions are connected to lists of emotional experiences, and the lists consisted of string and coefficient of each emotional experiences are used to generate and process emotional states. The emotional experiences are consisted of emotion vocabulary understanding various emotional experiences of human. This study EE is available to use to make interaction products to response the appropriate reaction of human emotions. The significance of the study is on development of a system to induce that person feel that product has your sympathy. Therefore, the EE can help give an efficient service of emotional sympathy to products of HRI, HCI area.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.562-567
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• 2009

As a key mechanism of the human emotion interaction, Facial Expression is a powerful tools in HRI(Human Robot Interface) such as Human Computer Interface. By using a facial expression, we can bring out various reaction correspond to emotional state of user in HCI(Human Computer Interaction). Also it can infer that suitable services to supply user from service agents such as intelligent robot. In this article, We addresses the issue of expressive face modeling using an advanced active appearance model for facial emotion recognition. We consider the six universal emotional categories that are defined by Ekman. In human face, emotions are most widely represented with eyes and mouth expression. If we want to recognize the human's emotion from this facial image, we need to extract feature points such as Action Unit(AU) of Ekman. Active Appearance Model (AAM) is one of the commonly used methods for facial feature extraction and it can be applied to construct AU. Regarding the traditional AAM depends on the setting of the initial parameters of the model and this paper introduces a facial emotion recognizing method based on which is combined Advanced AAM with Bayesian Network. Firstly, we obtain the reconstructive parameters of the new gray-scale image by sample-based learning and use them to reconstruct the shape and texture of the new image and calculate the initial parameters of the AAM by the reconstructed facial model. Then reduce the distance error between the model and the target contour by adjusting the parameters of the model. Finally get the model which is matched with the facial feature outline after several iterations and use them to recognize the facial emotion by using Bayesian Network.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.363-368
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• 2021

Ship engine rooms have improved automation systems owing to the advancement of technology. However, there are many variables at sea, such as wind, waves, vibration, and equipment aging, which cause loosening, cutting, and leakage, which are not measured by automated systems. There are cases in which only one engineer is available for patrolling. This entails many risk factors in the engine room, where rotating equipment is operating at high temperature and high pressure. When the engineer patrols, he uses his five senses, with particular high dependence on vision. We hereby present a preliminary study to implement an engine-room patrol robot that detects and informs the machine room while a robot patrols the engine room. Images of ship engine-room equipment were classified using a convolutional neural network (CNN). After constructing the image dataset of the ship engine room, the network was trained with a pre-trained CNN model. Classification performance of the trained model showed high reproducibility. Images were visualized with a class activation map. Although it cannot be generalized because the amount of data was limited, it is thought that if the data of each ship were learned through transfer learning, a model suitable for the characteristics of each ship could be constructed with little time and cost expenditure.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.486-494
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• 2014

Intelligent homes consist of ubiquitous sensors, home networks, and a context-aware computing system. These homes are expected to offer many services such as intelligent air-conditioning, lighting control, health monitoring, and home security. In order to realize these services, many researchers have worked on various research topics including smart sensors with low power consumption, home network protocols, resident and location detection, context-awareness, and scenario and service control. This paper presents the real-time metabolic rate estimation method that is based on measured heart rate for human adaptive appliance (air-conditioner, lighting etc.). This estimation results can provide valuable information to control smart appliances so that they can adjust themselves according to the status of residents. The heart rate based method has been experimentally compared with the location-based method on a test bed.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2045-2050
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• 2003

This paper describes the development of service robotic systems with the Tripodal schematic control architecture. We show practical advantages of the proposed architecture by giving examples of our experience. First, we explain how to add new task using Tripodal architecture approach. The Tripodal architecture provides some crucial organizing principles and core components that are used to build the basis for the system. Thus, the newly developed behaviors, motion algorithm, knowledge, and planning schemes are arranged so as to guarantee the efficiency of the performance of components. Second, we describe the reusability and scaleability of our architecture by introducing the implementation process of the guide robot Jinny. Most of modules developed for former robots like PSR-1 and PSR-2 systems are used directly to the Jinny system without significant modification. Experimental results clearly showed that the developed strategy is useful, even if the hardware configurations as well as software algorithms are more complex and more accumulating.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.281-292
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• 2016

The proposed scheme is based on the modified perturb and observe (P&O) algorithm combined with the sliding mode technique. A modified P&O algorithm based sliding mode controller is developed to study the effects of partial shade, temperature, and insolation on the performance of maximum power point tracking (MPPT) used in photovoltaic (PV) systems. Under partially shaded conditions and temperature, the energy conversion efficiency of a PV array is very low, leading to significant power losses. Consequently, increasing efficiency by means of MPPT is particularly important. Conventional techniques are easy to implement but produce oscillations at MPP. The proposed method is applied to a model to simulate the performance of the PV system for solar energy usage, which is compared to the conventional methods under non-uniform insolation improving the PV system utilization efficiency and allowing optimization of the system performance. The modified perturb and observe sliding mode controller successfully overcomes the issues presented by non-uniform conditions and tracks the global MPP. Compared to MPPT techniques, the proposed technique is more efficient; it produces less oscillation at MPP in the steady state, and provides more precise tracking.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.2
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• pp.176-182
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• 2011

Industrial network, often referred to as fieldbus, becomes an indispensable component for intelligent manufacturing systems. Thus, in order to satisfy the real-time requirements of field devices such as sensors, actuators, and controllers, numerous fieldbus protocols have been developed. But, the application of fieldbus has been limited due to the high cost of hardware and the difficulty in interfacing with multi-vendor products. As an alternative to fieldbus, the Ethernet (IEEE 802.3) technology is being adapted to the industrial environment. However, the crucial technical obstacle of Ethernet is its non-deterministic behavior that cannot satisfy the real-time requirements. Recently, the EtherCAT protocol becomes a very promising alternative for real-time industrial application due to the elimination of uncertainties in Ethernet. This paper focuses on the implementation of the IEC 61800 based real-time EtherCAT network for multi-axis smart driver. To demonstrate the feasibility of the implemented EtherCAT slave module, its synchronization performance is evaluated on the experimental EtherCAT testbed with a single axis smart driver.