• Journal of Institute of Control, Robotics and Systems
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• v.3 no.3
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• pp.272-279
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• 1997

In this paper, a fuzzy generalized predictive control (FGPC) for non-linear plants is proposed. In the proposed method, the receding horizon control is applied to the control part, while fuzzy systems are used for the predictor part. It is suggested that the fuzzy predictor is time-varying affine with respect to input variables for easy computation of control inputs. Since the receding horizon control can be obtained only with a predictor instead of a plant model, the fuzzy predictor is obtained directly from input-output data without identifying a plant model. A parameter estimation algorithm is used for identifying the fuzzy predictor. The control inputs of the FGPC are computed by minimizing a receding horizon cost function with predicted plant outputs. The proposed controller has a similar architecture to the generalized predictive control (GPC) except for the predictor synthesis method, and thus may possess inherent good properties of the GPC. Computer simulations show that the performance of the FGPC is satisfactory.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.35 no.4
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• pp.48-56
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• 2003

In this work an integrated model for paper plants combining wet-end and dry section is developed and a model predictive control scheme based on the plant model is proposed. Closed-loop process identification method is employed to produce a state-space model. Thick stock, filler flow, machine speed and steam pressure are selected as input variables and basis weight, ash content and moisture content are considered as output variables. The desired output trajectory is constructed in the form of 1st-order dynamics. Results of simulations for control of grade change operations are compared with plant operation data collected during the grade change operations under the same conditions as in simulations. From the comparison, we can see that the proposed model predictive control scheme reduces the grade change time and achieves stable steady-state.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1443-1448
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• 2003

Model Predictive Control (MPC) has recently found wide acceptance in industrial applications, but its potential has been much impounded by linear models due to the lack of a similarly accepted nonlinear modelling or data based technique. The authors have recently developed a new method for obtaining Volterra kernels of up to third order by use of pseudorandom M-sequence. By use of this method, nonparametric NMPC is derived in discrete-time using multi-dimensional convolution between plant data and Volterra kernel measurements. This approach is applied to an industrial polymerisation process using Volterra kernels of up to the third order. Results show that the nonparametric approach is very efficient and effective and considerably outperforms existing methods, while retaining the original data-based spirit and characteristics of linear MPC.

• Proceedings of the KIEE Conference
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• 1997.07f
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• pp.2028-2032
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• 1997

When a high performance current control is desired, a computation time delay of a digital control system may deteriorate the control performance of a current controller. Such a non-negligible effect can be considerable in transient state. This paper deals with the modified predictive current control that compensates the time delay effects of a conventional predictive current control. The method is closely related to a local average current control and a symmetrical PWM pattern generation. Also some theoretical approaches are presented to describe the voltage saturation boundary of the power converter. For validation, the proposed method is applied to an active power filter system. The experimental results show considerable improvement in current tracking capability.

• 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.

• The Transactions of the Korea Information Processing Society
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• v.7 no.7
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• pp.2254-2263
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• 2000

This paper proposes an efficient predictive image-compression technique based on vector quantization of blocks of pels. In the proposed method edge contents of blocks control the selection of predictors and block shapes as well. The maximum number of bits assigned to quantizers has been in creased to 3bits/pel from 1/5bits/pel, the setting employed by forerunners in predictive vector quantization of images. This increase prevents the saturation in SNR observed in their results in high bit rates. The variable block shape is instrumental in eh reconstruction of edges. The adaptive procedure is controlled by means of he standard deviation ofp rediction errors generated by a default predictor; the standard deviation address a decision table which can be set up beforehand. eh proposed method is characterized by overall improvements in image quality over A-VQ-PE and A-DCT VQ, both of which are known for their efficient use of vector quantizers.

• Research in Community and Public Health Nursing
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• v.18 no.1
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• pp.136-145
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• 2007

Purpose: This study was attempted to illuminate danger signals through an extensive analysis of factors influencing adolescents' illicit drug use. On this basis, it built predictive factors of adolescents' illicit drug use. Method: A questionnaire was distributed to 1,238 subjects living in Seoul, and of them 1,082 answers were analyzed using the SAS 8.2 program. Also logistic regression analysis was conducted based on the stepwise selection method for constructing the predictive factors. Results: The findings of this study are as follows. Individual-related factors were psycho-somatic symptoms, self-esteem, fortune delinquent experience, and sexual-violence delinquent experience. Home-related factors were insincerity, threatening and the assessment of the parent (rearer)-adolescent communication type. Society-related factors were affection of friends and friends' attitude toward delinquency. Conclusion: These findings of this study suggest that a broad intervention program should be provided to nurture wholesome youth culture related to illicit drug use. It is also recommended that a variety of individual, home and society-related programs should be developed for drug users.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.4
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• pp.289-295
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• 2002

In this paper, a linear matrix inequality(LMI)-based robust control method, which combines model predictive control(MPC) with the feedback linearization(FL), is presented for constrained nonlinear systems with parameter uncertainty. The design procedures consist of the following 3 steps: Polytopic description of nonlinear system with a parameter uncertainty via FL, Mapping of actual input constraint by FL into constraint on new input of linearized system, Optimization of the constrained MPC problem based on LMI. To verify the performance and usefulness of the control method proposed in this paper, some simulations with application to a flexible single link manipulator are performed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.2
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• pp.383-388
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• 2011

In this paper, we consider Hammerstein-Wiener nonlinear model for solid oxide fuel cell (SOFC). A nonlinear model predictive control (MPC) is proposed to trace the constant stack terminal power by Hydrogen flow as control input. After the stability of the closed-loop system with static output feedback controller is analysed by Lyapunov method, a nonlinear model predictive control based on the Hammerstein-Wiener model is developed to control the stack terminal power of the SOFC system. Simulation results verify the effectiveness of the proposed control method based on the Hammerstein-Wiener model for SOFC system.

• Proceedings of the KIEE Conference
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• 1993.07b
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• pp.711-714
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• 1993

A predictive current controller for the Battery Energy Stroage System(BESS) based on space vector PWM of transformer coupled inverters is presented. The control method have many advantages such as accurate control, reduced harmonics, good dynamics, improved stability, wide control range, etc,. The simulation results show that the predictive control method with space vector PWM is suitable for the transformer coupled inverters applied to the battery energy storage system.