• Journal of Institute of Control, Robotics and Systems
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• v.11 no.9
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• pp.755-760
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• 2005

This paper proposes an improved implementation algorithm for the continuous-time receding horizon control (RHC). The proposed algorithm has a feature that it has better control performance than the existing algorithm. Main idea of the proposed algorithm is that we can approximate the original RHC problem better by assuming the predicted input trajectory on the prediction horizon has a continuous form, which is constructed from linear interpolation of finite number of vectors. This, in turn, leads to improved control performance. We derive a predictor such that it takes linear interpolation into account and proposes the method by which we can express the cost exactly. Through simulation study fur an inverted pendulum, we illustrate that the proposed algorithm has the better control performance than the existing one.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.2
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• pp.131-138
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• 2004

Automatic flight control system (AFCS) for a low-cost unmanned aerial vehicle is described in this paper. Development process and block diagram of the AFCS are introduced. The flight control law for longitudinal and lateral channel autopilot is designed using optimization process. In this procedure, the performance index is composed of desired location of closed loop system poles and H$_2$norm of the resultant flight control system. This procedure is applied to the autopilot design of an unmanned target vehicle. Performance of the AFCS is evaluated by processor-in-the-loop simulation test and flight test. These results show that the AFCS has acceptable performance fur low cost UAV.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.348-353
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• 2003

This paper considers the optimal control problem in real-time control systems with random time-delays. It proposes an algorithm which uses the linear quadratic (LQ) control method and a dedicated technique to compensate for the time-delay effects. Since it is assumed that the time-delays are unknown but the probability distribution of the delays are known a priori, the algorithm considers the mean value of the time-delays as a nominal value for random delay compensation. An example is given to show the performance of the proposed algorithm, where an inverted pendulum system is controlled over a controller-area network (CAN). Simulation results show that the proposed algorithm provides good performance results. It is shown that our algorithm is comparable to existing algorithms in both computation cost and performance.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.241-246
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• 2004

This paper proposed trajectory tracking control of mobile robot. Trajectory tracking control scheme are real coding genetic-algorithm and back-propergation algorithm. Control scheme ability experience proposed simulation. Stable tracking control problem of mobile robots have been studied in recent years. These studios have guaranteed stability of controller, but the performance of transient state has not been guaranteed. In some situations, constant gain controller shows overshoots and oscillations. So we introduce better control scheme using Real coding Genetic Algorithm(RCGA) and neural network. Using RCGA, we can find proper gains in several situations and these gains are generalized by neural network. The generalization power of neural network will give proper gain in untrained situation. Performance of proposed controller will verify numerical simulations and the results show better performance than constant gain controller.

• Journal of the Korea Institute of Military Science and Technology
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• v.4 no.2
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• pp.30-41
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• 2001

In Underwater Flight Vehicle depth control system, the followings must be required. First, It needs a robust performance which can get over the nonlinear characteristics due to hull shape. Second, It needs an accurate performance which has the small overshoot phenomenon and steady state error to avoid colliding with ground surface and obstacles. Third, It needs a continuous control input to reduce the acoustic noise. Finally, It needs an effective interpolation method which can reduce the dependency of control parameters on speed. To solve these problems, we propose a Intelligence depth control method using Fuzzy Sliding Mode Controller and Neural Network Interpolator. Simulation results show the proposed control scheme has robust and accurate performance by continuous control input and has no speed dependency problem.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.54 no.1
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• pp.8-14
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• 2005

This paper is proposed hybrid artificial intelligent(HAI) controller for speed control of surface permanent magnet synchronous motor(SPMSM) drive. The design of this algorithm based on HAI controller that is implemented using fuzzy control and neural network. This controller uses fuzzy rule as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights between the neurons of neural network in order to minimize the error between the command output and actual output. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the HAI controller is evaluated by analysis for various operating conditions. The results of analysis prove that the proposed control system has strong high performance and robustness to parameter variation, and steady-state accuracy and transient response.

• 한국정보디스플레이학회:학술대회논문집
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• 2006.08a
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• pp.1166-1169
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• 2006

In this study, the effects of SAMs on the performance of OTFTs have been investigated. ALD technique was applied for the deposition of SAMs, which is an ultra-thin film deposition technique based on sequences of self-limiting surface reactions enabling thickness control on atomic scale. According to our investigation results, it is observed that the surface properties of the gate insulator was changed by SAMs, which allow pentacene molecules to be deposited in the upright direction on the gate insulator and hence the performance of OTFTs could be improved. These results will be discussed

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.12
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• pp.1041-1047
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• 1989

In recent years, a.c servomotors have been gradually replacing d.c servomotors in various high-performance applications such as machine tools and industrial robots. Inparticular, the high performance slip-frequency control of an induction motor, which is often called the vector control, is considered ane of th ebest a.c drives. In this paper, the transient state equations and vector control algorithms of an induction type servomotor are described mathematically by using the two- axis theory (d-q coordinates). According to the result of these algorithms, we scheme the speed control system for the motor in which the vector control is adopted to give high performance. Motor drive through a PWM inverter with power MOSFET is controlled so that the actual input current to the motor may track the current reference obtained from a micro-computer (8086 CPU). Driving experiments are performed in the range of 0 to 3000 rpm, and it is verified that high speed response is obtained for this system.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.176.2-176
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• 2001

In Underwater Flight Vehicle depth control system, the followings must be required. First, it needs robust performance which can get over nonlinear characteristics. Second, it needs accurate performance which have small overshoot phenomenon and steady state error. Third, it needs continuous control input. Finally, it needs interpolation method which can solve the speed dependency problem of controller parameters. To solve these problems, we propose adepth control method using Fuzzy Sliding Mode Controller and Neural Network Interpolator. Simulation results show the proposed method has robust and accurate control performance by the continuous control input and has no speed dependency problem.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.111.1-111
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• 2001

In this paper, a robust speed control is proposed for Permanent Magnet Synchronous Motor system. PMSM without reduction gear has been widely used in high performance application such as robots and machine tools. It is well known that the control performance of the PMSM is very sensitive to load disturbance and system parameter variation. The idea of the proposed speed controller based on combination of sliding mode control with fuzzy gain scheduling. The sliding mode controller leads to fast system dynamics of slight sensitivity to the load disturbance and system parameter variations, the fuzzy gain scheduling mechanism reduces the chattering phenomenon. The simulation results have proved that the proposed control scheme provides a robust control performance under load disturbance and system parameter variation.