• Nuclear Engineering and Technology
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• v.38 no.1
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• pp.81-92
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• 2006

In this study, the core dynamics of a PWR reactor is identified online by a recursive least-squares method. Based on the identified reactor model consisting of the control rod position and the core average coolant temperature, the future average coolant temperature is predicted. A model predictive control method is applied to designing an automatic controller for the thermal power control of PWR reactors. The basic concept of the model predictive control is to solve an optimization problem for a finite future at current time and to implement as the current control input only the first optimal control input among the solutions of the finite time steps. At the next time step, this procedure for solving the optimization problem is repeated. The objectives of the proposed model predictive controller are to minimize both the difference between the predicted core coolant temperature and the desired temperature, as well as minimizing the variation of the control rod positions. In addition, the objectives are subject to the maximum and minimum control rod positions as well as the maximum control rod speed. Therefore, a genetic algorithm that is appropriate for the accomplishment of multiple objectives is utilized in order to optimize the model predictive controller. A three-dimensional nuclear reactor analysis code, MASTER that was developed by the Korea Atomic Energy Research Institute (KAERI) , is used to verify the proposed controller for a nuclear reactor. From the results of a numerical simulation that was carried out in order to verify the performance of the proposed controller with a $5\%/min$ ramp increase or decrease of a desired load and a $10\%$ step increase or decrease (which were design requirements), it was found that the nuclear power level controlled by the proposed controller could track the desired power level very well.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.104-106
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• 2005

In this work, a PWR reactor core dynamics is identified online by a recursive least squares method. Based on this identified reactor model consisting of the control rod position and the core average coolant temperature, the future average coolant temperature is predicted. A model predictive control method is applied to design an automatic controller for thermal power control in PWRs. The basic concept of the model predictive control is to solve an optimization problem for a finite future at current time and to implement as the current control input only the first optimal control input among the solutions of the finite time steps. At the next time step, the procedure to solve the optimization problem is then repeated. The objectives of the proposed model predictive controller are to minimize both the difference between the predicted core coolant temperature and the desired one, and the variation of the control rod positions. Also, the objectives are subject to maximum and minimum control rod positions and maximum control rod speed. Therefore, the genetic algorithm that is appropriate to accomplish multiple objectives is used to optimize the model predictive controller. A 3-dimensional nuclear reactor analysis code, MASTER that was developed by Korea Atomic Energy Research Institute (KAERI), is used to verify the proposed controller for a nuclear reactor. From results of numerical simulation to check the performance of the proposed controller at the 5%/min ramp increase or decrease of a desired load and its 10% step increase or decrease which are design requirements, it was found that the nuclear power level controlled by the proposed controller could track the desired power level very well.

• Journal of Power Electronics
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• v.15 no.5
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• pp.1168-1177
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• 2015

This paper presents a scheme to improve the line current distortion of power factor corrector (PFC) topology at the zero crossing point using a predictive control algorithm in both the continuous conduction mode (CCM) and discontinuous conduction mode (DCM). The line current in single-phase PFC topology is distorted at the zero crossing point of the input AC voltage because of the characteristic of the general proportional integral (PI) current controller. This distortion degrades the line current quality, such as the total harmonic distortion (THD) and the power factor (PF). Given the optimal duty cycle calculated by estimating the next state current in both the CCM and DCM, the proposed predictive control algorithm has a fast dynamic response and accuracy unlike the conventional PI current control method. These advantages of the proposed algorithm lower the line current distortion of PFC topology. The proposed method is verified through PSIM simulations and experimental results with 1.5 kW bridgeless PFC (BLPFC) topology.

• 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 Power Electronics
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• v.19 no.1
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• pp.179-189
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• 2019

Four-quadrant converters (4QCs) are widely used as AC-DC power conversion interfaces in many areas. A control delay commonly exists in the digital implementation process of 4QCs, especially for high power 4QCs with a low switching frequency. This usually results in alternating current distortion, increased current harmonic content and system instability. In this paper, the control delay is divided into a computation delay and a PWM delay. The impact of the control delay on the performance of a 4QC is briefly analyzed. To obtain a fundamental value of AC current that is as accurately as possible, a specific sampling method considering the PWM pattern is introduced. Then a current predictive control based on a modified z-transform is proposed, which is effective in reducing the control delay and easy in terms of digital implementation. In addition, it does not depend on object models and parameters. The feasibility and effectiveness of the proposed predictive current control method is verified by simulation and experimental results.

• Nuclear Engineering and Technology
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• v.37 no.2
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• pp.177-184
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• 2005

The Multivariate State Estimation Technique (MSET) is being used in Nuclear Power Plants for sensor and equipment condition monitoring. This paper presents the use of regularization methods for optimizing MSET's predictive performance. The techniques are applied to a simulated data set and a data set obtained from a nuclear power plant currently implementing empirical, on-line, equipment condition monitoring techniques. The results show that regularization greatly enhances the predictive performance. Additionally, the selection of prototype vectors is investigated and a local modeling method is presented that can be applied when computational speed is desired.

• The Transactions of the Korean Institute of Power Electronics
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• v.19 no.5
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• pp.415-421
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• 2014

This study proposes a model-based predictive control for interleaved multi-phase DC/DC converters. The power values necessary to adjust the output voltage in the succeeding are predicted using a converter model. The output power is controlled by selecting the optimal duty cycle. The proposed method does not require controller loops and modulators for converter switching. This method can control the converter by calculating the optimal duty cycle, which minimizes the error between the reference and actual output voltage. The effectiveness of the proposed method is verified through simulations and experiments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.12
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• pp.2285-2290
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• 2008

Even though efficiency of coal-fired power plant is proportional to operating temperature, increasement of operating temperature is limited by a technological level of each power plant component. It is an alternative plan to increase operating pressure up to ultra super critical point for efficiency enhancement. It is difficult to control process of power plant in ultra super critical point because that point has highly nonlinear characteristics. In this paper, new control logic, Unit Response Optimizer Controller(URO Controller) which is based on Fuzzy logic and Model Predictive Controller, is introduced for better performance. Then its performance is tested and analyzed with design guideline.

• Journal of Power Electronics
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• v.13 no.6
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• pp.1016-1023
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• 2013

Predictive current control offers the potential for achieving more precise current control with a minimum of distortion and harmonic noise. However, the predictive method is difficult to implement and has a greater computational burden. This paper introduces a theoretical analysis and experimental verification for an improved predictive current control technique applied to single phase grid connected voltage source inverters (VSI). The proposed technique has simple calculations. An ATmega1280 microcontroller board is used to implement the proposed technique for a simpler and cheaper control system. To enhance the current performance and to obtain a minimum of current THD, an improved tri-level PWM switching strategy is proposed. The proposed switching strategy uses six operation modes instead of four as in the traditional strategy. Simulation results are presented to demonstrate the system performance with the improved switching strategy and its effect on current performance. The presented experimental results verify that the proposed technique can be implemented using fixed point 8-bit microcontroller to obtain excellent results.

• Journal of Power Electronics
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• v.19 no.2
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• pp.497-508
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• 2019

The predictive speed control (PSC) strategy can realize the simultaneous control of speed and current by using one cost function. As a model-based control method, the performance of the PSC is vulnerable to model mismatches such as load torque disturbances and parameter uncertainties. To solve this problem, this paper presents a robust predictive speed control (RPSC) strategy for surface-mounted permanent magnet synchronous motor (SPMSM) drives. The proposed RPSC uses extended state observers (ESOs) to estimate the lumped disturbances caused by load torque changes and parameter mismatches. The observer-based prediction model is then compensated by using the estimated disturbances. The introduction of ESOs can achieve robustness against predictive model uncertainties. In addition, a modified cost function is designed to further suppress load torque disturbances. The performance of the proposed RPSC scheme has been corroborated by experimental results under the condition of load torque changes and parameter mismatches.