• International Journal of Aeronautical and Space Sciences
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• v.12 no.1
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• pp.78-83
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• 2011

Traditional autopilot design requires an accurate aerodynamic model and relies on a gain schedule to account for system nonlinearities. This paper presents the control architecture applied to a dynamic model inversion at a single flight condition with an on-line neural network (NN) in order to regulate errors caused by approximate inversion. This eliminates the need for an extensive design process and accurate aerodynamic data. The simulation results using a developed full nonlinear 6 degree of freedom model are presented. This paper also presents the stability evaluation for control systems to which NNs were applied. Although feedback can accommodate uncertainty to meet system performance specifications, uncertainty can also affect the stability of the control system. The importance of robustness has long been recognized and stability margins were developed to quantify it. However, the traditional stability margin techniques based on linear control theory can not be applied to control systems upon which a representative non-linear control method, such as NNs, has been applied. This paper presents an alternative stability margin technique for NNs applied to control systems based on the system responses to an inserted gain multiplier or time delay element.

• The Journal of Korean Association of Computer Education
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• v.9 no.5
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• pp.77-84
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• 2006

In this paper, we propose an adaptive image watermarking algorithm in DWT domain by using HVS(human Visual system) and SOM(Self-Organizing Map) among neural networks. HVS can be described in terms of two properties of HVS: brightness and texture sensitivity. The SOM is used to obtain the local characteristics of image, Therefore, the suitable strength and length of embedded watermark is determined by using HVS and SOM. The experimental results show that proposed method provides a suitable strength and length of watermark and has good perceptual invisibility and robustness for various attacks.

• Journal of information and communication convergence engineering
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• v.7 no.2
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• pp.209-214
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• 2009

The employment of the induction generator is preferable in the natural energy utilization by the minimum maintenance and the mechanical robustness, Another merit is also expected when it is connected to the power network system, because constant-voltage and constant frequency (CVCF) power generation is easily realized in spite of the variation of the rotor speed. However the induction generator needs much amount of the reactive power that reduces power factor in the primary side. The improvement of power factor in the primary side requires large VAR compensator, this point is solved, the merit of the induction machine as a main generator will become more established. This paper proposes a novel approach where the secondary is controlled by a PWM inverter not only to get CVCF power but also to improve the primary power factor. Basically the inverter is controlled so that the field current is supplied from the secondary side in this approach. The required capacity of the inverter is small, because only the slip power is controlled in the secondary side. In the experimental system where the sea wave torque simulator is used, the power factor is well improved by the microcomputer controlled PWM inverter.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.10 s.181
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• pp.2589-2596
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• 2000

As current manufacturing processes require high spindle speed and precise machining, increasing accuracy by reducing volumetric errors of the machine itself, particularly thermal errors, is very important. Thermal errors can be estimated by many empirical models, for example, an FEM model, a neural network model, a linear regression model, an engineering judgment model, etc. This paper discusses to make a modeling of thermal errors efficiently through backward elimination and fuzzy logic strategy. The model of a thermal error using fuzzy logic strategy overcomes limitation of accuracy in the linear regression model or the engineering judgment model. It shows that the fuzzy model has more better performance than linear regression model, though it has less number of thermal variables than the other. The fuzzy model does not need to have complex procedure such like multi-regression and to know the characteristics of the plant, and the parameters of the model can be mathematically calculated. Also, the fuzzy model can be applied to any machine, but it delivers greater accuracy and robustness.

• Journal of the Korea Society of Computer and Information
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• v.8 no.4
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• pp.126-131
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• 2003

While the advantages of multicast delivery over multiple unicast deliveries is undeniable, the deployment of the IP multicast protocol has been limited to network domains under single administrative control. Deployment of inter-domain multicast delivery has been slow due to both technical and administrative reasons. For this reasons overlay multicasting technologies are recently proposed. We propose a End-Host Multicast Tree Protocol (EMTP) that searches two levels of the tree at a time until reaching to a leaf node and can select the nearest node that a new node try to join in the tree. Even if there is no available degree of the desirable node that a new node want to join, selecting the node as a potential parent by EMTP can reduce the number of tree switching with robustness of the tree and bring to ruduce the data delivery time.

• Journal of Power Electronics
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• v.16 no.5
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• pp.1821-1832
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• 2016

This study presents a strategy using the synchronized output regulation method (SOR) for controlling inverters operating in stand-alone and grid-connected modes. From the view point of networked dynamic systems, SOR involves nodes with outputs that are synchronized but also display a desirable wave shape. Under the SOR strategy, the inverter and grid are treated as two nodes that comprise a simple network. These two nodes work independently under the stand-alone mode. An intermediate mode, here is named the synchronization mode, is emphasized because the transition from the stand-alone mode to the grid-connected mode can be dealt as a standard SOR problem. In the grid-connected mode, the inverter operates in an independent way, in which the voltage reference changes for generalized synchronization where its output current satisfies the required power injection. Such a relatively independent design leads to a seamless transfer between operation modes. The closed-loop system is analyzed in the state space on the basis of the output regulation theory, which improves the robustness of the design. Simulations and experiments are performed to verify the proposed control strategy.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.372-372
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• 2000

In this paper, we propose Neuro Fuzzy Polynomial Networks(NFPN) based on Polynomial Neural Network(PNN) and Neuro-Fuzzy(NF) for model identification of complex and nonlinear systems. The proposed NFPN is generated from the mutually combined structure of both NF and PNN. The one and the other are considered as the premise part and consequence part of NFPN structure respectively. As the premise part of NFPN, NF uses both the simplified fuzzy inference as fuzzy inference method and error back-propagation algorithm as learning rule. The parameters such as parameters of membership functions, learning rates and momentum coefficients are adjusted using genetic algorithms. As the consequence part of NFPN, PNN is based on Group Method of Data Handling(GMDH) method and its structure is similar to Neural Networks. But the structure of PNN is not fixed like in conventional Neural Networks and self-organizing networks that can be generated. NFPN is available effectively for multi-input variables and high-order polynomial according to the combination of NF with PNN. Accordingly it is possible to consider the nonlinearity characteristics of process and to get better output performance with superb predictive ability. In order to evaluate the performance of proposed models, we use the nonlinear function. The results show that the proposed FPNN can produce the model with higher accuracy and more robustness than any other method presented previously.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.6C
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• pp.594-601
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• 2003

High-speed WLAN(Wireless Local Area Network) systems operating in 5GHz band use OFDM transmission technique. OFDM technique transmits data in parallel and has many advantage compared with the serial transmission system-for example, robustness to time variance of channel. OFDM technique use the orthogonal multicarriers. The ICI(InterChannel Interference) caused by the orthogonality destruction between subcarriers. hamper the BER performance. In this paper, we propose the synchronization techniques for high-speed WLAN system designed to support user data rates up to 54Mbps at 5GHz. The proposed synchronization techniques are the reduced complexity structure having the similar performance compared with the conventional synchronization techniques.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.3
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• pp.181-187
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• 2003

For the moving objects with environmental sensors such as object tracking moving robot with audio and video sensors, environmental information acquired from sensors keep changing according to movements of objects. In such case, due to lack of adaptability and system complexity, conventional control schemes show limitations on control performance, and therefore, sensory-motor systems, which can intuitively respond to various types of environmental information, are desirable. And also, to improve the system robustness, it is desirable to fuse more than two types of sensory information simultaneously. In this paper, based on Braitenberg's model, we propose a sensory-motor based fusion system, which can trace the moving objects adaptively to environmental changes. With the nature of direct connecting structure, sensory-motor based fusion system can control each motor simultaneously, and the neural networks are used to fuse information from various types of sensors. And also, even if the system receives noisy information from one sensor, the system still robustly works with information from other sensors which compensates the noisy information through sensor fusion. In order to examine the performance, sensory-motor based fusion model is applied to object-tracking four-foot robot equipped with audio and video sensors. The experimental results show that the sensory-motor based fusion system can tract moving objects robustly with simpler control mechanism than model-based control approaches.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.10
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• pp.902-911
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• 2012

This paper proposes a robust adaptive fuzzy backstepping control scheme for trajectory tracking of an electrically driven nonholonomic mobile robot with uncertainties and actuator dynamics. A complete model of an electrically driven nonholonomic mobile robot described in this work includes all models of the uncertain robot kinematics with a nonholonomic constraint, the uncertain robot body dynamics with uncertain frictions and unmodeled disturbances, and the uncertain actuator dynamics with disturbances. The proposed control scheme uses the backstepping control approach through a kinematic controller and a robust adaptive fuzzy velocity tracking controller. The presented control scheme has a voltage control input with an auxiliary current control input rather than a torque control input. It has two FBFNs(Fuzzy Basis Function Networks) to approximate two unknown nonlinear robot dynamic functions and a robust adaptive control input with the proposed adaptive laws to overcome the uncertainties such as parameter uncertainties and external disturbances. The proposed control scheme does not a priori require the accurate knowledge of all parameters in the robot kinematics, robot dynamics and actuator dynamics. It can also alleviate the chattering of the control input. Using the Lyapunov stability theory, the stability of the closed-loop robot control system is guaranteed. Simulation results show the validity and robustness of the proposed control scheme.