• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1292-1295
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• 1996

This paper proposes an adaptive control technique for the autopilot design of STT missile. Dynamics of the missile is highly nonlinear and the equilibrium point is vulnerable to change due to fast maneuvering. Therefore nonlinear control techniques are desirable for the autopilot design of the missile. The nonlinear controller requires the exact model to obtain satisfactory performance. Generally a look-up table is used for the dynamic coefficients of a missile, so there must be coefficients error during actual flight, and the performance of the nonlinear controller using these data can be degraded. The proposed adaptive control technique compensates the nonlinear controller with modeling error resulting from the error of aerodynamic data and disturbance. To investigate the usefulness, the proposed method is applied to autopilot design of STT missile through simulations.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.135-142
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• 2005

This paper presents an adaptive repetitive control scheme for optical disk drives to track a variable periodic reference signal. Periodic disturbances can be adequately attenuated using the concept of repetitive control, provided the period is known. Because optical disk drives support various speeds, they have the varying periodic disturbances. Based on repetitive control to change sampling frequency to follow the change of reference period, an adaptive repetitive control is proposed in order to deal with such disturbances. The proposed control consists of the repetitive controller and the frequency generator. The former uses a varying sampler operating at fixed multiple times of the disturbance frequency and the latter generates the changeable sampling frequency based on the disturbance frequency. The experimental results on the control of an optical disk drive demonstrate the effectiveness of the proposed schemes and the improvement of random access time as well.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.1
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• pp.1155-1161
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• 2001

We propose an adaptive nonlinear control algorithm for high precision tracking and stabilization of LOS(Line-of-Sight). The friction parameters of the LOS gimbal are estimated by off-line evolutionary strategy and the friction is compensated by estimated friction compensator. Especially, as the nonlinear control input in a small tracking error zone is enlarged by the nonlinear function, the steady state error is significantly reduced. The proposed algorithm is a direct adaptive control method based on the Lyapunov stability theory, and its convergence is guaranteed under the limited modeling error or torque disturbance. The performance of the pro-posed algorithm is verified by computer simulation on the LOS gimbal model of a moving vehicle.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.2
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• pp.74-82
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• 2004

In this paper, a disturbance feedforward compensator design technique is proposed for an active magnetic bearing system subject to base motion for attenuating disturbance responses. In the consideration of the requirements on the model accuracy in the model based compensator designs, an experimental feedforward compensator design based on adaptive estimation by means of the Multiple Filtered-x least mean square(MFXLMS) algorithm is proposed. The performance and the effectiveness of the proposed technique will be presented in the succeeding paper in which the proposed technique is applied to a 2-DOF active magnetic bearing system subject to base motion.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.812-814
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• 1999

In this paper, we propose a new control algorithm based on the neural network(NN) feedback compensation with a desired trajectory modification. The proposed algorithm decreases trajectory errors by a feed-forward desired torque combined with a neural network feedback torque component. And, to robustly control the tracking error, we modified the desired trajectory by variable structure concept smoothed by a fuzzy logic. For the numerical simulation, a 2-link robot manipulator model was assumed. To simulate the disturbance due to the modelling uncertainty. As a result of this simulation, the proposed method shows better trajectory tracking performance compared with the CTM and decreases the chattering in control inputs.

• Journal of Power Electronics
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• v.14 no.1
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• pp.105-114
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• 2014

The sliding mode control (SMC) strategy is applied to a permanent magnet synchronous machine vector control system in this study to improve system robustness amid parameter changes and disturbances. In view of the intrinsic chattering of SMC, a current sliding mode control method with a load sliding mode observer is proposed. In this method, a current sliding mode control law based on variable exponent reaching law is deduced to overcome the disadvantage of the regular exponent reaching law being incapable of approaching the origin. A load torque-sliding mode observer with an adaptive switching gain is introduced to observe load disturbance and increase the minimum switching gain with the increase in the range of load disturbance, which intensifies system chattering. The load disturbance observed value is then applied to the output side of the current sliding mode controller as feed-forward compensation. Simulation and experimental results show that the designed method enhances system robustness amid load disturbance and effectively alleviates system chattering.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.540-543
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• 1997

In this paper, a precise trajectory tracking method for mobile robot using a vision system is presented. In solving the problem of precise trajectory tracking, a hierarchical control structure is used which is composed of the path planer, vision system, and dynamic controller. When designing the dynamic controller, non-ideal conditions such as parameter variation, frictional force, and external disturbance are considered. The proposed controller can learn bounded control input for repetitive or periodic dynamics compensation which provides robust and adaptive learning capability. Moreover, the usage of vision system makes mobile robot compensate the cumulative location error which exists when relative sensor like encoder is used to locate the position of mobile robot. The effectiveness of the proposed control scheme is shown through computer simulation.

• Journal of the Korean Society for Precision Engineering
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• v.34 no.2
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• pp.125-131
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• 2017

2-Axis Pan and Tilt Motion Platform, a complex multivariate non-linear system, may incur any disturbance, thus requiring system controller with robustness against various disturbances. In this study, we designed an adaptive backstepping compensated controller by estimating the disturbance and error using the Radial Basis Function Neural Network (RBF NN). In this process, Uniformly Ultimately Bounded (UUB) was demonstrated via Lyapunov and stability was confirmed. By generating progressive disturbance to the irregular frequency and amplitude changes, it was verified for various environmental disturbances. In addition, by setting the RBF NN input vector to the minimum, the estimated disturbance compensation process was analyzed. Only two input vectors facilitated compensatory function of RBF NN via estimating the modeling and control error values as well as irregular disturbance; the application of the process resulted in improved backstepping controller performance that was confirmed through simulation.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.18 no.1
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• pp.50-58
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• 2009

For precise tracking control of a servo system with nonlinear friction, a robust friction compensation scheme is presented in this paper. The nonlinear friction is difficult to identify the friction parameters exactly through experiments. Friction parameters can be also varied according to contact conditions such as the variation of temperature and lubrication. Thus, in order to overcome these problems and obtain the desired position tracking performance, a robust adaptive back-stepping control scheme with a dual friction observer is developed. In addition, to estimate lumped friction uncertainty due to modeling errors, a DEKF recurrent neural network and adaptive reconstructed error estimator are also developed. The feasibility of the proposed control scheme is verified through the experiment fur a ball-screw system.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.7
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• pp.997-1004
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• 1990

In this paper, a design method of a robust adaptive regulator with feedfoward path based on the explicit criterion minimization is proposed. The convergence speed of parameter estimation is improved by using the stochastic Newton minimization method in the criterion minimization algorithm, and sensitivity derivatives are used in the regulator calculation for improving the robustness of the control system. Trh proposed adaptive regulator is applied to the stable minimum-phase and nonminimum-phase system, the results are shown that control performance and disturbance compensation ability of the regulator are improved. And the choosing method of input penalty is proposed.