• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.421-424
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• 2008

The real time modeling of dynamic system on adaptive control system is very important for flying control system(FCS). Using traditional method, it is required much calculation load for integral/differential at control system. Therefore, It is very important theme of study in these days to find algorithms for integration/differential at FCS. These algorithms for integral/differential influence strongly stability/reliability to control flying object. In this paper, we present optimal predictive sampling time for reduce calculation load at FCS and optimal predictive time on general cost function by applying adaptive control method.

• ICROS
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• v.2 no.1
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• pp.59-71
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• 1996

In the last decade, the model predictive control methods have enjoyed many industrial applications with successful results. Although the general predictive control methods for nonlinear chemical processes are not yet formulated, the promising features of the model predictive control methods attract attentions of many researchers who are involved with difficult but important nonlinear process control problems. Recently, the class of bilinear model has been introduced as an useful tool for examining many nonlinear phenomena. Since their structural properties are similar to those of linear models, it is not difficult to develop a robust adaptive model predictive control method based on bilinear model. We expect that the model predictive control method based on bilinear model will expand its region in the world of nonlinear systems.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2003.04a
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• pp.14-17
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• 2003

Vibration control of a composite plate with a surface-bonded fiber Bragg grating (FBG) sensor and piezoceramic actuators has been performed using a neural network based adaptive predictive control algorithm. For the detection of Bragg wavelength changes, two cavity lengths in Fabry-Perot read-out interferometers are used in order to produce two quadrature phase shifted signals. The FBG sensor system and real-time neuro-adaptive control algorithm could be applicable to diverse dynamic systems.

• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.27-36
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• 2014

This paper presents an adaptive wide-area damping controller (WADC) based on generalized predictive control (GPC) and model identification for damping the inter-area low frequency oscillations in large-scale inter-connected power system. A recursive least-squares algorithm (RLSA) with a varying forgetting factor is applied to identify online the reduced-order linearlized model which contains dominant inter-area low frequency oscillations. Based on this linearlized model, the generalized predictive control scheme considering control output constraints is employed to obtain the optimal control signal in each sampling interval. Case studies are undertaken on a two-area four-machine power system and the New England 10-machine 39-bus power system, respectively. Simulation results show that the proposed adaptive WADC not only can damp the inter-area oscillations effectively under a wide range of operation conditions and different disturbances, but also has better robustness against to the time delay existing in the remote signals. The comparison studies with the conventional lead-lag WADC are also provided.

• Journal of the military operations research society of Korea
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• v.13 no.1
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• pp.1-18
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• 1987

This paper presents several adaptive linear predictive coding techniques based upon extension of recursive ladder filters. A 2-D recursive ladder filter is extended to a 3-D case which can adaptively track the variation of both spatial and temporal changes of moving images. Using the 2-D/3-D ladder filter and a previous farme predictor, two types of adaptive predictor-control schemes are proposed in which the prediction error at each pel can be obtained at or close to a minimum level. We also investigate several modifications of the basic encoding methods. Performance of the 2-D/3-D ladder filters, their adaptive control schemes, and variations in coding methods are evaluated by computer simulations on a real sequence and compared to the results of motion compensation and frame differential coders. As a validity test of the ladder filters developed, the error signals for the different predictors are compared and evaluated.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.734-740
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• 1987

Various kinds of predictive control design methods such as MAC(Model Algorithmic Control), DMC(Dynamic Matrix Control), MC(Extended Horizon Adaptive Control), GPC(Generalized Predictive Control), RHTC(Receding Horizon Tracking Controller), and PVC(PreView Controller) are surveyed and compared in this paper. In addition, stability properties of these control laws known to date are summarized and some new stability results are presented.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.20-23
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• 1997

Refuse incineration plant operations involve many kinds of uncertain factors, such as the variable physical properties of refuse as fuel and the complexity of the burning phenomenon. That makes it very difficult to apply conventional control methods to the combustion control of the refuse. In this paper, an adaptive fuzzy model predictive controller is proposed for the combustion control of the refuse. And computer simulation was carried out to evaluate performance of the proposed controller.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.2
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• pp.197-203
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• 1997

In this paper, we present a GP-PID(Generalized Predictive PID) controller which has the same structure as a generalized predictive control with steady-state weighting. The proposed controller can perform better than the conventional PID controller because it includes intrinsic delay-time compensator. The PID tuning parameters and delay-time compensator are calculated by equating the two degree of freedom PID to a linear form of GPC. The proposed controller is combined with a supervisor for safe start and self-tuning. GP-PID controller has been tested for various numerical models and an experimental stirred tank heater. As a result, it was observed that the proposed controller shows a satisfactory performance for variable delay as well as stochastic disturbance.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.99-104
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• 1991

An adaptive predictive control method for SISO and MIMO plants is proposed. In this method, future predictions of process output based on a bilinear CARIMA model are used to calculate the control input. Also, a classical recursive adaptation algorithm, equation error method, is used to decrease the uncertainty of the process model. As a result of the application on distillation process, the ability of the set-point tracking and the disturbance rejection is acceptable to apply to the industrial distillation processes.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.1
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• pp.165-170
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• 2017

This paper presents an event-triggered model predictive controller for adaptive cruise control system with sampled and quantized-data. Unlike existing works, a longitudinal continuous-time model is used for the predictive control of the system. To efficiently utilize network resources, event-trigger scheme is employed, which allows limited sensor and actuator signal satisfying the condition that the measurement of errors is over the ratio of a trigger level. The proposed control gain is obtained by solving a convex problem satisfying several linear matrix inequalities at every sampling times. Simulation results are given to show the effectiveness of the proposed design method.