• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.1
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• pp.9-16
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• 2018

Predictive control is a very practical method that obtain the current input that minimizes the future errors of the reference command and state by use of the predictive model of the controlled object, and can also consider the constraints of the state and input. Although there have been studies in which predictive control is applied to mobile robots, performance has not been optimized as various control parameters for determining control performance have been arbitrarily specified. In this paper, we apply the genetic algorithm to the trajectory tracking control of a mobile robot with input constraints in order to minimize the trajectory tracking errors through control parameter tuning, and apply the quadratic programming Hildreth method to reflect the input constraints. Through the computer simulation, the superiority of the proposed method is confirmed by comparing with the existing method.

• Korean Chemical Engineering Research
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• v.51 no.1
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• pp.87-92
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• 2013

Microalgae have been suggested as a promising feedstock for producing biofuel because of their potential of lipid production. In this study, a first principles ODE model for microalgae growth and neutral lipid synthesis proposed by Surisetty et al. (2010) is investigated for the purpose of maximizing the rate of microalgae growth and the amount of neutral lipid. The model has 6 states and 12 parameters and follows the assumption of Droop model which explains the growth as a two-step phenomenon; the uptake of nutrients is first occurred in the cell, and then use of intra-cellular nutrient to support cells growth. In this study, optimal input design using D-optimality criterion is performed to compute the system input profile and sensitivity analysis is also performed to determine which parameters have a negligible effect on the model predictions. Furthermore, model predictive control based on successive linearization is implemented to maximize the amount of neutral lipid contents.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.95-100
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• 2021

This paper introduces model-based meta reinforcement learning as a control for the manipulator of an underwater construction robot. Model-based meta reinforcement learning updates the model fast using recent experience in a real application and transfers the model to model predictive control which computes control inputs of the manipulator to reach the target position. The simulation environment for model-based meta reinforcement learning is established using MuJoCo and Gazebo. The real environment of manipulator control for underwater construction robot is set to deal with model uncertainties.

• 유체기계공업학회:학술대회논문집
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• 1999.12a
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• pp.46-51
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• 1999

This paper describes the control charcteristics of thermal/flow systems. In thermal/flow systems, the transport lag plays as a dead time causing a deterioration of the controllability. Besides this, such many parameters including the temperature, pressure, and flow rate affect the system response that a control scheme which can deal with multi-input is required. Particularly in a refrigerant compressor test facility, the evaporator and condenser interact each other so that the change in the evaporator pressure cause the condenser pressure to change or vice versa. Therefore, to control the evaporator pressure, not only the cooling water flow rate in the evaporator but also the coolant flow rate in the condenser is considered. Meanwhile, the conventional PID controllers, which is suitable for a single input system, shows a large overshoot for a disturbance input. In this work, the predictive control scheme is introduced and its applicability is discussed for thermal/flow systems.

• Journal of Power Electronics
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• v.11 no.4
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• pp.583-590
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• 2011

Three-level NPC inverters have been put into practical use for years especially in high voltage high power grids. This paper researches three-level active power filters (APFs). In this paper a mathematical model in the d-q coordinates is presented for 3-phase 3-wire NPC APFs. The deadbeat control scheme is obtained by using state equations. Canceling the delay of one sampling period and providing the predictive value of the harmonic current is a key problem of the deadbeat control. Based on this deadbeat control, the predictive output current value is obtained by the state observer. The delay of one sampling period is remedied in this digital control system by the state observer. The predictive harmonic command current value is obtained by the repetitive predictor synchronously. The repetitive predictor can achieve a better prediction of the harmonic current with the same sampling frequency, thus improving the overall performance of the system. The experiment results indicate that the steady-state accuracy and the dynamic response are both satisfying when the proposed control scheme is implemented.

• Journal of Power Electronics
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• v.19 no.1
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• pp.244-253
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• 2019

Finite control set model-predictive control (FCS-MPC) has received increasing attentions due to its outstanding dynamic performance. It is being widely used in power converters and multilevel inverters. However, FCS-MPC requires a lot of calculations, especially for multilevel-cascaded H-bridge (CHB) static synchronous compensators (STATCOMs), since it has to take account of all the feasible voltage vectors of inverters. Hence, an improved five-segment space vector pulse width modulation (SVPWM) method based on the non-orthogonal static reference frames is proposed. The proposed SVPWM method has a lower number of switching states and requires fewer computations than the conventional method. As a result, it makes FCS-MPC more efficient for multilevel cascaded H-bridge STATCOMs. The partial cost function is adopted to sequentially solve for the reference current and capacitor voltage. The proposed FCS-MPC method can reduce the calculation burden of the FCS-MPC strategy, and reduce both the switching frequency and power losses. Simulation and experimental results validate the excellent performance of the proposed method when compared with the conventional approach.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1838-1842
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• 2004

Gain and phase margins of a first order plus delayed time (FOPDT) process controlled by generalized predictive controller (GPC) are related to the control parameters ${\lambda}$ (control move suppression parameter) and ${\alpha}$ (smoothing filter coefficient) and the normalized delay of the process. Variation ranges of gain and phase margins are determined. It is shown that the margins cannot be assigned independently for a wide range of variation and the range is narrowing by increase of the normalized delay of the process. And finally curves are given to use for adjustment of the controller parameters in order to obtain a specific pair of gain and phase margins.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.172.4-172
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• 2001

In this paper, the Generalized Predictive Control(GPC) method based on Fuzzy Neural Networks(FNNs) is presented for the control of chaotic nonlinear systems without precise mathematical models. In our method, FNNs is used as the predictor whose parameters are tuned by the error between the actual output of nonlinear chaotic system and that of FNNs model. The parameters of GPC controller are adjusted via the gradient descent method where the difference between the actual output and the reference signal is used as a control error. Finally, computer simulation on the representative continuous-time chaotic system(Duffing system) is presented to demonstrate the effectiveness of our chaos control method.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.20 no.1
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• pp.6-17
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• 2013

Purpose: The purpose of this study was propose and test a predictive model that could explain and predict factors influencing the sexual satisfaction of women with diabetes mellitus. Method: The conceptual frame for this study was formed as a hypothesized model based on Roy's adaptation model. Participants for this study were 240 out-patient women from P university hospital in Y city. The data were analyzed using SPSS 18.0 and AMOS 19.0 program. Results: The paths that had direct effects on sexual satisfaction, and were statistically significant were showing intimacy with spouse, and sexual function. The explanatory power of these variables for sexual satisfaction was 64%. Conclusion: The results of the study suggest that it is necessary for enhancement of sexual satisfaction for women with diabetes to increase intimacy with husband, and that sexual function, frequency of exercise, adequate glycemic control be maintained, and depression decreased.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.392-395
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• 2003

In the maritime container terminal, LMTT (Linear Motor-based Transfer Technology) is horizontal transfer system for the yard automation, which has been proposed to take the place of AGV (Automated Guided Vehicle). The system is based on PMLSM (Permanent Magnetic Linear Synchronous Motor) that is consists of stator modules on the rail and shuttle car (mover). Because of large variant of mover's weight by loading and unloading containers, the difference of each characteristic of stator modules, and a stator module's trouble etc., LMCPS (Linear Motor Conveyance Positioning System) is considered as that the system is changed its model suddenly and variously. In this paper, we will introduce the soft-computing method of a multi-step prediction control for LMCPS using DR-FNN (Dynamically-constructed Recurrent Fuzzy Neural Network). The proposed control system is used two networks for multi-step prediction. Consequently, the system has an ability to adapt for external disturbance, cogging force, force ripple, and sudden changes of itself.