• Current Optics and Photonics
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• v.5 no.2
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• pp.101-113
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• 2021

Adaptive optics (AO) systems are becoming more complex to improve their optical performance and enlarge their field of view, so it is a hard and time consuming process to set up and optimize the components of AO systems with actual implementation. However, simulations allow AO scientists and engineers to experiment with different optical layouts and components without needing to obtain and prepare them physically. In this paper, we introduce a new AO simulation named the Korea Adaptive Optics Simulation (KAOS), independently developed by LIG Nex1. We verified the performance of KAOS by comparing with other AO simulation tools. In the comparison simulation, we confirmed the results from KAOS and other AO simulation tools were very similar. Also, we proposed a laser tomography AO system with five Rayleigh laser guide stars (LGSs) optimized by using KAOS to overcome the disadvantages of the AO system with a single sodium LGS for the satellite imaging system. We verified the performance of the proposed AO system using KAOS, and the simulation result showed averaged Strehl ratio of 0.37.

• The Journal of Korea Robotics Society
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• v.9 no.4
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• pp.258-263
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• 2014

An adaptive robot hand (AR-Hand) has a stable grasp of different objects in unstructured environments. In this study, we propose an AR-Hand based on a tendon-driven mechanism which consists of 4 fingers and 12 DOFs. It weighs 0.5 kg and can grasp an object up to 1 kg. This hand based on the adaptive grasp mechanism is able to provide a stable grasp without a complex control algorithm or sensor system. The fingers are driven by simple tendon structures with each finger capable of adaptively grasping the objects. This paper presents a method to decide the joint stiffness. The adaptive grasping is verified by various grasping experiments involving objects with different shapes and sizes.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.243-246
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• 1994

In this paper, a self-learning fuzzy controller is designed with a fuzzy approximation of an inverse model. The aim of an identification is to find an input command which is control of a system output. It is intuitional and easy to use a classical adaptive inverse modeling method for the identification, but it is difficult and complex to implement it. This problem can be solved with a fuzzy approximation of an inverse modeling. The fuzzy logic effectively represents the complex phenomena of the real world. Also fuzzy system could be represented by the neural network that is useful for a learning structure. The rule of a fuzzy inverse model is modified by the gradient descent method. The goal is to be obtained that makes the design of fuzzy controller less complex, and then this self-learning fuzz controller can be used for nonlinear dynamic system. We have applied this scheme to a nonlinear Ball and Beam system.

• Journal of Power Electronics
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• v.14 no.3
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• pp.549-563
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• 2014

In this paper, the speed regulation problem of permanent synchronous motor (PMSM) systems under the vector control framework is studied. A model reference adaptive controller (MRAC) based on the Lyapunov stability theory is first designed. Since the standard MRAC method provides poor disturbance rejection performance in the case of strong disturbances, a composite control method which combines the MRAC method and the disturbance estimation method, called the MRAC+ESO method, is proposed. An extended state observer (ESO) is introduced to estimate the lumped disturbances. The obtained estimated value acts as a feedforward compensation term to the MRAC controller. A stability analysis of the composite control method is given. Simulation and experimental results are presented and compared to show the effectiveness of the proposed control method.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.191-196
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• 1993

Since the welding process is complex and highly nonlinear, it is very difficult to accurately model the process for real-time control. In this paper, a discrete-time transfer function matrix model for gas metal arc welding process is proposed. Although this linearized model is valid only around the operating point of interest, the adaptation mechanism employed in the control system render this model useful over a wide operating range. A multivariable one-step-ahead adaptive control strategy combined with a recursive least-squares method for on-line parameter estimation is implemented in order to achieve the desired weld bead geometries. Command following and disturbance rejection properties of the adaptive control system for both SISO and MIMO cases are investigated by simulation and experiment.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.148-153
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• 1999

In this paper, it is proposed the adaptive-sliding mode control technique which is new approach to implement the robust control of industrial robot manipulator with external disturbances and parameter uncertainties. Over the past decade, the design of advanced control systems for industrial robotic manipulators has been a very active area of research and two major design categories have emerged. Sliding mode control is a well-known technique for robust control of uncertain nonlinear systems. The robustness of sliding model controllers can be shown in continuous time, but digital implementation may not preserve robustness properties because the sampling process limits the existence of a true sliding mode. Adaptive control algorithm is designed by using the principle of the model reference adaptive control method based upon the hyperstability theory. The proposed control scheme has a simple structure is computationally fast and does not require knowledge of the complex dynamic model or the parameter values of the manipulator or the payload. Simulation results how that the proposed method not only improves the performance of the system but also reduces the chattering problem of sliding mode control. Consequently, it is expected that the new adaptive sliding mode control algorithm will be suited for various practical applications of industrial robot control system.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.5
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• pp.346-352
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• 2016

This paper proposes an adaptive robust control method for an acrobot system in the presence of input disturbance. The acrobot system is a typical example of the underactuated system with complex nonlinearity and strong dynamic coupling. Also, disturbance can cause limit cycle phenomenon which appears in the acrobot system around the desired unstable equilibrium point. To minimize the effect of the disturbance, we apply a fuzzy disturbance estimation method for the swing-up and balancing control of the acrobot system. In this paper, both disturbance observer and controller for the acrobot system are designed and verified through mathematical proof and simulations.

• The Journal of Korean Association of Computer Education
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• v.9 no.1
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• pp.41-48
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• 2006

The latest several studies show that Wiki is a very efficient tools for collaborative learning in the distributed environments. Even though Wiki supports efficient knowledge sharing between group members, there are still some problems to be solved for collaborative learning. Since the structure of group contents becomes more complex and the links between pages are dynamically changed, each member of group has difficulties to perceive the changed contents and links on group pages. We designed the adaptive navigation system to guide individual browsing paths of each member through the calculating of friendship and the state of pages. At first we developed the relation model between member and each pages by the historical log that stored the change of pages and the activity of members, and then we implemented the adaptive navigation system using the model. Experimental results show that this adaptive system is very effective to share the group knowledge and to promote collaborative learning activities.

• Proceedings of the KIPE Conference
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• 1999.07a
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• pp.4-9
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• 1999

A new control method for precision robust position control of a brushless DC (BLDC) motor using asymptotically stable adaptive load torque observer is presented in the paper. Precision position control is obtained for the BLDC motor system approximately linearized using the field-orientation method Recently, many of these drive systems use BLDC motors to avoid backlashe. However, the disadvantages of the motor are high cost and complex control because of nonlinear characteristics. Also, the load torque disturbance directly affects the motor shaft. The application of the load torque observer is published in [1] using fixed gain. However, the motor flux linkage is not exactly known for a load torque observer. There is the problem of uncertainty to obtain very high precision position control. Therefore a model reference adaptive observer is considered to overcome the problem of unknown parameter and torque disturbance in this paper. The system stability analysis is carried out using Lyapunov stability theorem. As a result, asymptotically stable observe gain can be obtained without affecting the overall system response. The load disturbance detected by the asymptotically stable adaptive observer is compensated by feedforwarding the equivalent current which gives fast response. The experimenta results are presented in the paper.

• Clinical and Experimental Pediatrics
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• v.52 no.6
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• pp.649-654
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• 2009

The immune system is comprised of cells and molecules whose collective and coordinated response to the introduction of foreign substance is referred to as the immune response. Defense against microbes is mediated by the early reaction (innate immunity) and the late response (adaptive immunity). Innate immunity consists of the epithelial barrier, phagocytes, complement and natural killer cells. Adaptive immunity, a more complex defense reaction, consists of activation of later-developed lymphocytes that, when stimulated by exposure to infectious agents, increase in magnitude and defensive capabilities with each successive exposure. In this review we discuss recent advances in important primary immune deficiency disorders of innate immunity (chronic granulomatous disease, leukocyte adhesion deficiency) and adaptive immunity (severe combined immune deficiency, Wiskott- Aldrich syndrome).