• International Journal of Safety
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• 제5권2호
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• pp.6-11
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• 2006

The time delay in servo control on LonWorks/IP Virtual Device Network (VDN) is highly stochastic in nature. LonWorks/IP VDN induced time delay deteriorates the performance and stability of the real-time distributed control system and hinders an effective preventive and predictive maintenance. Especially in real-time distributed servo applications on the factory floor, timely response is essential for predictive and preventive maintenance. In order to guarantee the stability and performance of the system for effective preventive and predictive maintenance, LonWorks/IP VDN induced time delay needs to be predicted and compensated for. In this paper position control simulation of DC servo motor using Zero Phase Error Tracking Controller (ZPETC) as a feedforward controller, and Internal Model Controllers (IMC) based on Smith predictor with disturbance observer as a feedback controller is performed. The validity of the proposed control scheme is demonstrated by comparing the IMC based on Smith predictor with disturbance observer.

• 한국항해항만학회지
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• 제31권7호
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• pp.597-603
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• 2007

A predictive controller can solve a control problem related to a disturbance-dominant system such as roll stabilization of a ship in waves. In this paper, a predictive controller is developed for a fin stabilizer. Future wave-induced moment is modeled simply using two typical regular wave components for which six parameters are identified by the recursive Fourier transform and the least squares method using the past time series of the roll motion. After predicting the future wave-induced moment, optimal control theory is applied to discover the most effective command fin angle that will stabilize the roll motion. In the results, wave prediction performance is investigated, and the effectiveness of the predictive controller is compared to a conventional PD controller.

• Journal of Power Electronics
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• 제13권6호
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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 Preventive Medicine and Public Health
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• 제16권1호
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• pp.31-34
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• 1983

For the study of the applicability of predictive equation of subjective symptoms of workers using organic solvents, 67 male workers using organic solvents were selected. The predictive equation was quotated from previous Cheon's study. All the datas of necessary variables were gained. The predictive values and observed values were compared. The results were summarized as below; 1. The difference between predictive values and observed values were characteristically large. The coefficient of determination between the two values was 0.0024. 2. The $R^2$ value of multiple stepwise regression equation derived from present study was 0.2827.

• 지구물리
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• 제9권3호
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• pp.171-179
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• 2006

Predictive equations of ground motions are one of the most important factors in the seismic hazard analysis. Unfortunately, studies on predictive equations of ground motions in Korea had been hampered due to the lack of seismic data. To overcome the lack of data, seismologists adopted the stochastic method based on the seismological model. Korean predictive equations developed by the stochastic method show large differences in their predictions. It was turned out through the analysis of the existing studies that the main sources of the differences are the uncertainties in the (Brune) stress drop and spectral decay rate . Therefore, it is necessary to focus the future research on the reduction of the uncertainties in the two parameters.

• International journal of advanced smart convergence
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• 제7권4호
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• pp.75-83
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• 2018

Predictive IoT Sensor Algorithm is a technique of data science that helps computers learn from existing data to predict future behaviors, outcomes, and trends. This algorithm is a cloud predictive analytics service that makes it possible to quickly create and deploy predictive models as analytics solutions. Sensors and computers collect and analyze data. Using the time series prediction algorithm helps to predict future temperature. The application of this IoT in industrial environments like power plants and factories will allow organizations to process much larger data sets much faster and precisely. This rich source of sensor data can be networked, gathered and analyzed by super smart software which will help to detect problems, work more productively. Using predictive IoT technology - sensors and real-time monitoring - can help organizations exactly where and when equipment needs to be adjusted, replaced or how to act in a given situation.

• Journal of Power Electronics
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• 제19권2호
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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.

• 한국압력기기공학회 논문집
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• 제19권1호
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• pp.6-10
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• 2023

Only about 10% of selected equipment in nuclear power plants are monitored by wiring to address failures or problems caused by vibration. The purpose is primarily for preventive maintenance, not for predictive maintenance. This paper shows that vibration monitoring and diagnosis using Industrial 4.0 enables the complete predictive maintenance for all vibrating equipments in nuclear power plants with the convergence of internet of things; wireless technology, big data through periodic collection and artificial intelligence. Predictive maintenance using wireless technology is possible in all areas of nuclear power plants and in all systems, but it should satisfy regulatory guides on electromagnetic interference and cyber security.

• International Journal of Air-Conditioning and Refrigeration
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• 제15권3호
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• pp.129-136
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• 2007

In this paper, we suggest PI control with the Smith predictive controller to improve transient response of a variable speed refrigeration system (VSRS). As the refrigeration system has long dead time inherently, it is difficult to get fast responses of super-heat and reference temperature. We incorporated the Smith predictive controller into PI to compensate the effect of the long dead time of the system. At first, we introduced the decoupling model of the system to control capacity and superheat simultaneously and independently. Next, we designed the predictive controller of the superheat based on PI control law. Finally, the control performance by the proposed method was investigated through some numerical simulations and experiments. The results of the simulations and experiments showed that the proposed PI control with the predictive controller could obtain acceptable transient behaviour for the system.

• Nuclear Engineering and Technology
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• 제35권5호
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• pp.399-411
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• 2003

A model predictive control method is applied to design an automatic controller for thermal power control in a reactor core. 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 second optimal control input is not implemented and the procedure to solve the optimization problem is then repeated. The objectives of the proposed model predictive controller are to minimize the difference between the output and the desired output and the variation of the control rod position. The nonlinear PWR plant model (a nonlinear point kinetics equation with six delayed neutron groups and the lumped thermal-hydraulic balance equations) is used to verify the proposed controller of reactor power. And a controller design model used for designing the model predictive controller is obtained by applying a parameter estimation algorithm at an initial stage. From results of numerical simulation to check the controllability 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, the performances of this controller are proved to be excellent.