• Journal of the Korean Society of Safety
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• 제21권4호
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• pp.25-32
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• 2006

LonWorks over IP(LonWorks-IP) virtual device network(VDN) is an integrated form of LonWorks device network and IP data network. In especially real-time distributed servo applications on the factory floor, timely response is essential for predictive and preventive maintenance. The time delay in servo control on LonWorks-IP based VDN has highly stochastic nature. LonWorks-IP based VDN induced transmission delay deteriorates the performance and stability of the real-time distributed control system and can't give an effective preventive and predictive maintenance. In order to guarantee the stability and performance of the system, and give an effective preventive and predictive maintenance, LonWorks-IP based VDN induced time-varying uncertain time delay needs to be predicted and compensated. In this paper new Pill control scheme based on Smith predictor, disturbance observer and band pass filter is proposed and tested through computer simulation about position control of DC servo motor. It is shown that how can the proposed control scheme be designed to minimize the effects of uncertain varying time delay and model uncertainties. The validity of the proposed control scheme is compared and demonstrated with the comparison of internal model controllers(IMC) based on Smith predictor with and without disturbance observer.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2503-2508
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• 2005

In this paper, we propose a new discrete-time predictive current controller for a PMSM(Permanent Magnet Synchronous Motor). The main objectives of the current controllers are to ensure that the measured stator currents tract the command values accurately and to shorten the transient interval as much as possible, in order to obtain high-performance of ac drive system. The conventional predictive current controller is hard to implement in full digital current controller since a finite calculation time causes a delay between the current sensing time and the time that it takes to apply the voltage to motor. A new control strategy in this paper is seen the scheme that gets the fast adaptation of transient current change, the fast transient response tracking. Moreover, the validity of the proposed method is demonstrated by numerical simulations and the simulation results will present the improvements of predictive controller and accuracy of the current controller.

• The Transactions of the Korean Institute of Power Electronics
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• 제23권5호
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• pp.359-365
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• 2018

This study introduces a model predictive control method for controlling a cascaded flying capacitor multilevel rectifier used as an AC-DC rectifier of a solid-state transformer for DC distribution systems. The proposed method reduces the number of states that need to be considered in model predictive control by separately controlling input current, output DC link voltage, and flying capacitor voltage. Thus, calculation time is shortened to facilitate the level expansion of the cascaded flying capacitor multilevel rectifier. The selection of weighting factors did not present difficulties because the weighting factors in the cost function of the conventional model predictive control are not used. The effectiveness of the proposed method is verified through computer simulation using powersim and experiment.

• Ocean Systems Engineering
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• 제14권1호
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• pp.17-52
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• 2024

In this paper, the authors explore the modeling and control of a point absorber wave energy converter, which is connected to the electric grid via a power converter that is based on a linear permanent magnet synchronous generator (LPMSG). The device utilizes a buoyant mechanism to convert the energy of ocean waves into electrical power, and the LPMSG-based power converter is utilized to change the variable frequency and voltage output from the wave energy converter to a fixed frequency and voltage suitable for the electric grid. The article concentrates on the creation of a predictive control system that regulates the speed, voltage, and current of the LPMSG, and the modeling of the system to simulate its behavior and optimize its design. The predictive model control is created to guarantee maximum energy output and stable grid connection, using Matlab Simulink to validate the proposed strategy, including control side generator and predictive current grid-side converter loops.

• Journal of Electrical Engineering and Technology
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• 제10권1호
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• pp.227-242
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• 2015

This paper proposes a weighting factor optimization method in predictive control algorithm for torque ripple reduction in an induction motor fed by an indirect matrix converter (IMC). In this paper, the torque ripple behavior is analyzed to validate the proposed weighting factor optimization method in the predictive control platform and shows the effectiveness of the system. Therefore, an optimization method is adopted here to calculate the optimum weighting factor corresponds to minimum torque ripple and is compared with the results of conventional weighting factor based predictive control algorithm. The predictive control algorithm selects the optimum switching state that minimizes a cost function based on optimized weighting factor to actuate the indirect matrix converter. The conventional and introduced weighting factor optimization method in predictive control algorithm are validated through simulations and experimental validation in DS1104 R&D controller platform and show the potential control, tracking of variables with their respective references and consequently reduces the torque ripple.

• Journal of Institute of Control, Robotics and Systems
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• 제10권1호
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• pp.10-14
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• 2004

We present a predictive control algorithm combined with the robust robot control that is constructed on the Lyapunov min-max approach. Since the control design of a real manipulator system may often be made on the basis of the imperfect knowledge about the model, it is an important trend to design a robust control law that guarantees the desired properties of the manipulator under uncertain elements. In the preceding robust control work, we need to tune several control parameters in the admissible set where the desired stability can be achieved. By introducing an optimal predictive control technique in robust control we can find out much more deterministic controller for both the stability and the performance of manipulators. A new class of robust control combined with an optimal predictive control is constructed. We apply it to a simple type of 2-link robot manipulator and show that a desired performance can be achieved through the computer simulation.

• Journal of Navigation and Port Research
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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 Korean Academy of Oral and Maxillofacial Radiology
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• 제29권1호
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• pp.149-159
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• 1999

Purpose: The purpose of this study was to evaluate cervical lymph node metastasis of oral squamous cell carcinoma patients by MRI film and neural network system. Materials and Methods: The oral squamous cell carcinoma patients(21 patients. 59 lymph nodes) who have visited SNU hospital and been taken by MRI. were included in this study. Neck dissection operations were done and all of the cervical lymph nodes were confirmed with biopsy. In MR images. each lymph node were evaluated by using 6 MR imaging criteria(size. roundness. heterogeneity. rim enhancement. central necrosis, grouping) respectively. Positive predictive value. negative predictive value. and accuracy of each MR imaging criteria were calculated. At neural network system. the layers of neural network system consisted of 10 input layer units. 10 hidden layer units and 1 output layer unit. 6 MR imaging criteria previously described and 4 MR imaging criteria (site I-node level II and submandibular area. site II-other node level. shape I-oval. shape II-bean) were included for input layer units. The training files were made of 39 lymph nodes(24 metastatic lymph nodes. 10 non-metastatic lymph nodes) and the testing files were made of other 20 lymph nodes(10 metastatic lymph nodes. 10 non-metastatic lymph nodes). The neural network system was trained with training files and the output level (metastatic index) of testing files were acquired. Diagnosis was decided according to 4 different standard metastatic index-68. 78. 88. 98 respectively and positive predictive values. negative predictive values and accuracy of each standard metastatic index were calculated. Results: In the diagnosis of using single MR imaging criteria. the rim enhancement criteria had highest positive predictive value (0.95) and the size criteria had highest negative predictive value (0.77). In the diagnosis of using single MR imaging criteria. the highest accurate criteria was heterogeneity (accuracy: 0.81) and the lowest one was central necrosis (accuracy: 0.59). In the diagnosis of using neural network systems. the highest accurate standard metastatic index was 78. and that time. the accuracy was 0.90. Neural network system was more accurate than any other single MR imaging criteria in evaluating cervical lymph node metastasis. Conclusion: Neural network system has been shown to be more useful than any other single MR imaging criteria. In future. Neural network system will be powerful aiding tool in evaluating cervical node metastasis.

• Journal of Power Electronics
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• 제11권2호
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• pp.156-162
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• 2011

The control loop time delay caused by sampling, the zero-order-holder effect and calculations is inevitable in the digital control of dc-dc switching converters. The time delay will limit the bandwidth of the control loop and therefore degrade the transient performance of digital systems. In this paper, the quantization time delay effects with different time delay values based on a generic second-order system are analyzed. The conclusion that the bandwidth of digital control is reduced by about 20% with a one cycle delay and by 50% with two cycles of delay in comparison with no time delay is obtained. To compensate the time delay and to increase the control loop bandwidth, a duty ratio predictive control scheme based on linear extrapolation is proposed. The compensation effect and a comparison of the load variation transient response characteristics with analogy control, conventional digital control and duty ratio predictive control with different time delay values are performed on a point-of-load Buck converter by simulations and experiments. It is shown that, using the proposed technique, the control loop bandwidth can be increased by 50% for a one cycle delay and 48.2% for two cycles of delay when compared to conventional digital control. Simulations and experimental results prove the validity of the conclusion of the quantization effects of the time delay and the proposed control scheme.

• Structural Engineering and Mechanics
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• 제40권2호
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• pp.233-243
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• 2011

This paper presents a theoretical study of a model predictive control (MPC) strategy employed in semi-active control system with magnetorheological (MR) dampers to reduce the responses of seismically excited structures. The MPC scheme is based on a prediction model of the system response to obtain the control actions by minimizing an objective function, which can compensate for the effect of time delay that occurred in real application. As an example, a 5-story building frame equipped with two 20 kN MR dampers is presented to demonstrate the performance of the proposed MPC scheme for addressing time delay and reducing the structural responses under different earthquakes, in which the predictive length l = 5 and the delayed time step d = 10, 20, 40, 60, 100 are considered. Comparison with passive-off, passive-on, and linear quadratic Gaussian (LQG) control strategy indicates that MPC scheme exhibits good control performance similar to the LQG control strategy, both have better control effectiveness than two passive control methods for most cases, and the MPC scheme used in semi-active control system show more effectiveness and robustness for addressing time delay and protecting structures during earthquakes.