• Proceedings of the KIEE Conference
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• 2005.04a
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• pp.221-225
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• 2005

This paper proposes a gain scheduled control technique using time-delay for the nonlinear system with plant uncertainties and unexpected disturbances. The time delay-based gain scheduled control depends on a direct estimation of a function representing the effect of uncertainties. The information from the estimation is used to cancel the unknown dynamics and the unexpected disturbances simultaneously. The proposed estimation scheme with a finite convergence time is formulated in order to estimate the unborn scheduling variable variation. In other words, the time delay-based gain scheduled control uses the past observation of the system's response and the control input to directly modify the control actions rather than to adjust the controller gains or to identify system parameters. It has a simple structure so as to minimize the computational burden. The benefits of this proposed scheme are demonstrated in the simulation of an electromagnetic suspension system with plant uncertainties and external disturbances, and the proposed controller is compared with the conventional state feedback controller.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.03a
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• pp.1358-1365
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• 2010

Estimating condition of slope is difficult because of nonlinear time dependency and seasonal effects, which affect the displacements. Displacements and displacement patterns of landslides are highly variable in time and space, and a unique approach cannot be defined to model landslide movements. Characteristics of movements are obtained by using a statistical method called Principal Component Analysis(PCA). The PCA is a non-parametric method to separate unknown, statistically uncorrelated source processes from observed mixed processes. In the non-parametric approaches, no physical assumptions of target systems are required. Instead, since the "best" mathematical relationship is estimated for given data sets of the input and output measured from target systems. As a consequence, non-parametric approaches are advantageous in modeling systems whose geomechanical properties are unknown or difficult to be measured. Non-parametric approaches are consequently more flexible in modeling than parametric approaches. This method is expected to be a useful tool for the slope management of and alarm systems.

• Smart Media Journal
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• v.6 no.3
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• pp.49-56
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• 2017

Images and Videos that include the human face contain a lot of information. Therefore, accurately extracting human face is a very important issue in the field of computer vision. However, in real life, human faces have various shapes and textures. To adapt to these variations, A model-based approach is one of the best ways in which unknown data can be represented by the model in which it is built. However, the model-based approach has its weaknesses when the motion between two frames is big, it can be either a sudden change of pose or moving with fast speed. In this paper, we propose an enhanced human face-tracking model. This approach included human face detection and motion estimation using Cascaded Convolutional Neural Networks, and continuous human face tracking and modeling correction steps using the Active Appearance Model. A proposed system detects human face in the first input frame and initializes the models. On later frames, Cascaded CNN face detection is used to estimate the target motion such as location or pose before applying the old model and fit new target.

• Journal of Advanced Information Technology and Convergence
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• v.8 no.2
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• pp.101-110
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• 2018

This paper introduces feedback linearization (FL) based adaptive sliding mode control (ASMC) effective against ground effects of the quadrotor UAV. The proposed control has the capability of estimation and effective rejection of those effects by adaptive mechanism, which resulting stable attitude and positioning of the quadrotor. As output variables of quadrotor, x-y-z position and yaw angle are chosen. Dynamic extension of the quadrotor dynamics is obtained for terms of roll and pitch control input to be appeared explicitly in x-y-z dynamics, and then linear feedback control including a ground effect is designed. A sliding mode control (SMC) is designed with a class of FL including higher derivative terms, sliding surfaces for which is designed as a class of integral type of resulting closed loop dynamics. The asymptotic stability of the overall system was assured, based on Lyapunov stability methods. It was evaluated through some simulation that attitude control capability is stable under excessive estimation error for unknown ground effect and initial attitude of roll, pitch, and yaw angle of $30^{\circ}$ in all. Effectiveness of the proposed method was shown for quadrotor system with ground effects.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.299-302
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• 1996

A control algorithm is proposed for nonlinear multi-input multi-output(MIMO) batch processes by combining quadratic iterative learning control(Q-ILC) with model predictive control(MPC). Both controls are designed based on output feedback and Kalman filter is incorporated for state estimation. Novelty of the proposed algorithm lies in the facts that, unlike feedback-only control, unknown sustained disturbances which are repeated over batches can be completely rejected and asymptotically perfect tracking is possible for zero random disturbance case even with uncertain process model.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1423-1427
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• 1997

This paper deals with an algebraic approach to FDI observer design procedure. In general, FDI observer can be designed a sLuenbrger-type and equations for unknown input and actuator fault estimation include derivation of system outputs which is not available from the measurement directly. At this point, this paper presents STWS approach which can convert the derivation procedure to the recursive algebraic form by using its orthogonality and disjointess to alleviate such problems.

• Proceedings of the KIEE Conference
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• 1994.07a
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• pp.389-391
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• 1994

This paper proposes an approach to control the current amplitude and phase simultaneously. To do this, variable structure control and adaptive parameter estimation arc applied to the current control of a single-phase PWM inverter with unknown R-L series load. The load parameters, R and L, are estimated by using the recursive least square method and these parameters are used to adjust the feedback gains of control input. The inverter system is modelled in a 2nd-order system by treating load current variation caused by inductive component as a disturbance. Simulation and experiment based on the 2nd -order model are done and the results show good dynamic response and low THD.

• Journal of information and communication convergence engineering
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• v.6 no.4
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• pp.359-363
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• 2008

In this paper, the capacity of MIMO fading channel in the OFDM-based spatial multiplexing systems is analyzed when there is scattering at both transmitter and receiver. The employed MIMO channel model is spanning from the correlated low-rank case to uncorrelated high-rank case at both transmitter and receiver. The effects of spatial fading correlation on the capacity of MIMO channel is examined when the channel is known and unknown at the transmitter. We also evaluate the impacts of a channel estimation error at the transmitter on the MIMO channel capacity.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.4
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• pp.364-370
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• 1990

In this paper, we propose a self-tuning PID controller for unknown systems with time-varying delay. Using pole placement equations, we derive the controller that can be extended to the multi-step time delay case. The time-varying delays are estimated by a prediction error delay method using multiple predictors. Since the order of the estimation vector is not increased, the persistant exciting condition of control input is alleviated. Since the least square method gives biased parameter estimates for colored noise cases, the recursive instrumental variable method is used to estimate system parameters. The computational burden of the proposed method is less than the conventional adaptive methods. Computer simulations are performed to illustrate the efficiency of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.250-255
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• 1993

In this paper, for detection and isolation of instrument and process faults related with steam generator(S/G) in nuclear power plant, two types of observers are designed based on the linearized dynamic model of S/G : a bank of Dedicated Observers (DOS) for instrument faults detection and a bank of Unknown Input Observers(UIO) for process faults detection. And then, they are combined to decide which one between the above two faults occurs. In principle, the failure in ith instrument(process) can be isolated by monitoring the error between the ith output and its estimation obtained from the ith DOS(UIO). It is shown via computer simulations that the present scheme is feasible in finding out the source of a fault.