• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2011.11a
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• pp.618-623
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• 2011

A pressure control law to regulate pressure of gas generator is suggested. To design a model based control law, the governing equation which is consisted of Robert and conservation equation is built and verified through the ground burning test. PID and nonlinear adaptive control laws are designed to evaluate the loop response characteristics under the system which has varying eigen properties as combustor volume is increased. It is suggested that new approach, gain scheduling design, is required to overcome the defects identified from numerical simulation results of the two control laws. The newly suggested scheme showed good control performance even under disturbances and measurement noise.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.5
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• pp.46-55
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• 2000

This paper presents a direct adaptive control of robot system using chaotic neural networks and PD controller. The chaotic neural networks have robust nonlinear dynamic characteristics because of the sufficient nonlinearity in neuron itself, and the additional self-feedback and inter-connecting weights between neurons in same layer. Since the structure and the learning method are not appropriate for applying in control system, this neural networks have not been applied. In this paper, a modified chaotic neural networks is presented for dynamic control system. To evaluate the performance of the proposed neural networks, these networks are applied to the trajectory control of the three-axis PUMA robot. The structure of controller consists of PD controller and chaotic neural networks in parallel for conforming the stability in initial learning phase. Therefore, the chaotic neural network controller acts as a compensating controller of PD controller.

• 전기의세계
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• v.33 no.1
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• pp.14-25
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• 1984

전자공업은 방위산업발달에 획기적인 역활을 담당하고 있으며, 특히 전략적 $C^{3}$I (Command, Control, Communication and Intelligence) 개념을 도입하여, 국가방위를 위한 연구가 미국의 여러 대학들과 국방성 산하 연구기관에서 활발히 진행되고 있다. 이 글에서는 $C^{3}$I 에 대한 개략적인 개념을 소개하고, 추계학적 (Stochastic) 관점에서 $C^{3}$I 가 실전을 위하여 어떻게 응용되고 있는 가를 고찰하기 위하여 최근에 발표되고 있는 비선형필터링(Nonliner Filtering), 적응형필터링(Adaptive Filtering), 최적제어 문제들을 소개하고자 한다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.8
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• pp.1332-1338
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• 1997

In the case of the transfer function for the secondary path is dependent on time, the on-line method which can model it is continuously must be applied to the active noise control technique. And the adaptive random noise technique among the on-line methods is effective in the narrow-band control. In this method, the signal to noise ratio between random noise for modeling and primary noise is low. Therefore, the estimations of transfer function will be prone to inaccuracies and the convergence time will be too long. Such imperfections will have an influence upon the performance of an active noise controller. In this study, t enhance the signal to noise ratio, the on-line method that is combined the conventional adaptive random noise technique and the adaptive line enhancer, is proposed. By using proposed on-line method, a rigorous system identification and control of primary noise have been implemented.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.12
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• pp.6034-6039
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• 2012

In this paper, this may appear to exacerbate it met slopes of the mobile robot moves to overcome this by driving can occur if the mobile robot system has its own sleep problems driving progress in until you hit the target and solvedriving straight driving safer model for adaptive fuzzy control method of mobile robot based control algorithm is proposed. First, we propose a model based adaptive fuzzy controller, if possible, the dynamics model of the mobile robot, including model-based controller is designed to determine if you can check the condition of the mobile robot climbing and driving the mobile robot to overcome the slope and the to overcome driving control. Enough considering the ground friction forces and ensure the stability of the mobile robot system and the disturbance compensation, etc. In this case, the controller design will be possible. In addition, the nonlinear model, the dynamic characteristics of the mobile robot control method of adaptive fuzzy control techniques in the design that you want to fully reflect Non-holonomic system of mobile robots and solve sleep problems, and will be useful enough, it was verified through computer simulations.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.5
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• pp.944-957
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• 2007

In general mechanical servo systems, friction deteriorates the performance of controllers by its nonlinear characteristics. Especially, friction phenomenon causes steady-state tracking errors and limit cycles in position and velocity control systems, even though gains of controllers are tuned well in linear system model. Even if sensor is used higher accuracy level, it is difficult to improve tracking performance of the position to the same level with a general control method such as PID type. Therefore, many friction models were proposed and compensation methods have been researched actively. In this paper, we consider that the variation of mover's mass is various by loading and unloading. The normal force variation occurs by it and other parameters. Therefore, the proposed control system is composed of main position controller and a friction compensator. A parameter estimator for a nonlinear friction model is designed by adaptive control law and adaptive backstopping control method.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.8
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• pp.42-47
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• 2006

In this paper, we propose a sliding mode control with the bound estimation for robot manipulators without requiring exact knowledge of the robot dynamics. For the bound estimation, the upper bound of the uncertain nonlinearities of robot dynamics is represented as a Fredholm integral equation of the first kind and we propose an adaptive scheme which is only dependent on the sliding surface function. Also, we prove the asymptotic stability for the robot systems using two important properties in the robot dynamics: skew-symmetry and positive-definiteness of robot parameters.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.69-71
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• 1997

The direct drive motor is directly coupled by load. So, it is directly affected by load and disturbances. To control the direct drive motor, a robust controller is need. The main feature of variable structure system is that system trajectories are robust and insensitive to parameter variations and disturbances in the sliding mode. In this paper, adaptive variable structure controller, is used for the BLDD SM(Brushless Direct Drive Servo Motor) control. The chattering problem is reduced by using the saturation function.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.210-212
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• 1995

Its is proposed that a stable adaptive control system composed of a fuzzy and a compensating controller, is designed to control nonlinear systems. In fuzzy and proposed compensating controller, parameters of membership functions characterizing the linguistic terms change according to some adaptive law. The adaptive law are based on the Lyapunov systhesis approach. the closed-loop system using the adaptive control structure proposed in this paper is globally stable in the sense that the Lyapunov function decreases as time goes. the following simulation shows the results.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.10
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• pp.563-571
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• 2000

In this paper, a nonlinear adaptive control method for an EMS(Electro-Magnetic Suspension) system with mass uncertainty is proposed. Using the coordinate transformation and feedback linearizing control, EMS system has been transformed into the form of parametric strict-feedback system with unknown virtual control coefficients. With this transformed system, tuning functions approach, which is an advanced from of adaptive backstepping, has been applied in order to stabilize the system against mass uncertainty. Computer simulation is also carried out in order to compare the performance of the proposed controller with that of feedback linerizing controller.