• Journal of Power Electronics
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• v.14 no.6
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• pp.1178-1188
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• 2014

This study proposes a finite-state model predictive controller to regulate the load current and balance the DC-link capacitor voltages of a four-leg neutral-point-clamped converter. The discrete-time model of the converter, DC-link, inductive filter, and load is used to predict the future behavior of the load currents and the DC-link capacitor voltages for all possible switching states. The switching state that minimizes the cost function is selected and directly applied to the converter. The cost function is defined to minimize the error between the predicted load currents and their references, as well as to balance the DC-link capacitor voltages. Moreover, the current regulation performance is improved by using a two-step prediction horizon. The feasibility of the proposed predictive control scheme for different references and loads is verified through real-time implementation on the basis of dSPACEDS1103.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.45-48
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• 1999

Model predictive control algorithm requires a relevant model of the system to be controlled. Unfortunately, the first principle model describing a polymerization reaction system has a large number of parameters to be estimated. Thus there is a need for the identification and control of a polymerization reactor system by using available input-output data. In this work, the polynomial auto-regressive moving average (ARMA) models are employed as the input-output model and combined into the nonlinear model predictive control algorithm based on the successive linearization method. Simulations are conducted to identify the continuous styrene polymerization reactor system. The input variables are the jacket inlet temperature and the feed flow rate whereas the output variables are the monomer conversion and the weight-average molecular weight. The polynomial ARMA models obtained by the system identification are used to control the monomer conversion and the weight-average molecular weight in a continuous styrene polymerization reactor It is demonstrated that the nonlinear model predictive controller based on the polynomial ARMA model tracks the step changes in the setpoint satisfactorily. In conclusion, the polynomial ARMA model is proven effective in controlling the continuous styrene polymerization reactor.

• The Journal of Korea Robotics Society
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• v.15 no.3
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• pp.277-285
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• 2020

A differential drive wheeled robot is a kind of mobile robot suitable for indoor navigation. Model predictive control is an optimal control technique with various advantages and can achieve excellent performance. One of the main advantages of model predictive control is that it can easily handle constraints. Therefore, it deals with realistic constraints of the mobile robot and achieves admirable performance for trajectory tracking. In addition, the intention of the robot can be properly realized by adjusting the weight of the cost function component. This control technique is applied to the local planner of the navigation component so that the mobile robot can operate in real environment. Using the Robot Operating System (ROS), which has transcendent advantages in robot development, we have ensured that the algorithm works in the simulation and real experiment.

• Journal of Power Electronics
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• v.17 no.3
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• pp.610-620
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• 2017

The Finite Control Set-Model Predictive Controller (FCS-MPC) for quasi Z-Source Inverters (qZSIs) is designed to reduce the number of sensors by proposing a current observer for the inductor current. Unlike the traditional FCS-MPC algorithm, the proposed model removes the inductor current sensor and observes the inductor current value based on the deposited prior optimized state as well as the capacitor voltage during this state. The proposed observer has been validated versus a typical MPC. Then, a comparative study between the proposed Modified Finite Control Set-Model Predictive Controller (MFCS-MPC) and a linear PID controller is provided under the same operating conditions. This study demonstrates that the dynamic response of the control objectives by MFCS-MPC is faster than that of the PID. On the other hand, the PID controller has a lower Total Harmonic Distortion (THD) when compared to the MFCS-MPC at the same average switching. Experimental results validate both methods using a DSP F28335.

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.11
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• pp.1180-1188
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• 2008

As many systems depend on electronics, concern for fault tolerance is growing rapidly in the safety critical system such as intelligent vehicle. In order to make system fault tolerant, there has been a body of research mainly from aerospace field including predictive hybrid redundancy by Lee. Although the predictive hybrid redundancy has the fault tolerant mechanism to satisfy the fault tolerant requirement of safety crucial system such as x-by-wire system, it suffers form the variability of prediction performance according to the input feature of system. As an alternative to the prediction method of predictive hybrid redundancy for robust fault tolerant, Kalman prediction has attracted some attention because of its well-known and often-used with its structure called Kalman hybrid redundancy. In addition, several numerical simulation results are given where the Kalman hybrid redundancy outperforms with predictive smoothing voter.

• Journal of Korean Academy of Nursing
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• v.27 no.4
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• pp.796-806
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• 1997

The majority of studies on breastfeeding consists of descriptive correlational studies identifying the incidence and correlates of breastfeeding. The theory of planned behavior has been shown to yield great predictive power for behavioral goals over which individuals have only limited control such as improving school grades and weight loss. The purpose of this study was to test the "theory of planned behavior" in the prediction of breastfeeding of mothers who delivered vaginally, One hundred mothers who delivered vaginally in one general hospital in Seoul and one general hospital and three private hospitals in Taejeon participated in this study. The instruments used for data collection in this study were developed by the researchers following the guidelines suggested by Ajzen & Fishbein(1980) and Ajzen & Madden(1986). The instruments included measurement of attitude, subjective norm, perceived behavioral control and intention. The collected data were analyzed using descriptive statistics, Pearson product moment correlation, hierachical multiple regression and logistic regression. The results are as follows ; 1. Intention to breastfeed correlated significantly with attitude, subjective norm and perceived behavioral control. Both attitude and subjective norm did not make a significant contribution to the prediction of intention, but the addition of perceived behavioral control to the regression equation greatly improved the model's predictive power, increasing the R²from .05 to .52. 2. Intention to breastfeed alone had a significant predictive effect on actual breastfeeding, resulting in a regression coefficient of .16(X²=8 60, p<.01), but when perceived behavioral control was added to the equation, intention was not a significant predictive variable and only perceived behavioral control showed significant predictive power on actual breastfeeding, resulting in a regression coefficient of .12(X²=4.69, p<.05). In sum, breastfeeding behavior lent only partial support to the second version of the theory of planned behavior, and because perceived behavioral control had a strong effect on intention to breastfeed and actual breastfeeding, It would be desirable to develop nursing intervention programs which focus on strengthening the perceived behavioral control for the promotion of breastfeeding.

• The Transactions of the Korean Institute of Power Electronics
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• v.15 no.2
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• pp.159-166
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• 2010

For a grid-connected inverter in distributed generation systems, the current control is essential, and recently, the predictive current control based on a high performance digital signal processors (DSP) to satisfy a fast dynamic response has been widely investigated. However, the performance of predictive current control is degraded by the time delay due to digital implementation, the parameter and measured value errors and the interference of noise, and also theses make system even unstable. Therefore, this paper proposes the predictive current control using grid voltage observer for grid-connected inverter applications. To determine the relevant voltage observer gain, the low-order harmonics of grid voltage are considered, and the effect of filter parameter errors is analyzed. The proposed method has a fast current response capability, the robustness to noise and simple implementation due to voltage sensorless control and the robust current control performance to low-order grid harmonics. The feasibility of the proposed method is verified by simulation and experimental results.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.801-806
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• 1987

The receding horizon tracking control for the discrete time invariant systems is presented in this paper. This control law is derived with the receding horizon concept from the standard tracking problems. Stability properties of this control law are analyzed. It is shown that there exists a finite horizon index for which the closed loop systems are always asymptotically stable. The receding horizon tracking control is a kind of predictive control and will add a new clan to many existing predictive controls, with which some comparisons are made.