• 로봇학회논문지
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• 제19권1호
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• pp.8-15
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• 2024

This paper proposes a linear model predictive control of 6-DOF remotely operated underwater vehicles using nonlinear robust internal-loop compensator (NRIC). First, we design a integrator embedded linear model prediction controller for a linear nominal model, and then let the real model follow the values calculated through forward dynamics. This work is carried out through an NRIC and in this process, modeling errors and external disturbance are compensated. This concept is similar to disturbance observer-based control, but it has the difference that H_∞ optimality is guaranteed. Finally, tracking results at trajectory containing the velocity discontinuity point and the position tracking performance in the disturbance environment is confirmed through the comparative study with a traditional inverse dynamics PD controller.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 심포지엄 논문집 정보 및 제어부문
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• pp.236-238
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• 2005

In this paper, we propose a new discrete-time predictive current controller for a PMLSM(permanent magnet linear synchronous motor). The main objectives of the current controllers are that the measured stator current is tracked the command current value accurately and the transient interval is shorten 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 take to apply the voltage to motor. A new control strategy is the schema that gets the fast adaptation of transient current change, the fast transient response tracking. Moreover, the simulation results will be verified the improvements of Predictive controller and accuracy of the current controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.292-295
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• 2003

In this paper, we present static output feedback model predictive tracking control for linear system with uncertainty. The proposed control law is based on integral action form to provide zero o��set for constant command signals and the closed loop stability is guaranteed under linear matrix inequality conditions on the terminal weighting matrix using the decreasing monotonicity property of the performance index. Through simulation examples, we illustrate that the proposed schemes can be appropriate tracking controllers for uncertain system.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2008년도 추계종합학술대회 B
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• pp.379-382
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• 2008

잡음환경 하의 회화에서 잡음량을 줄이고 신호처리 시스템의 성능을 향상시키기 위해서는 잡음량에 따라서 적응적으로 처리되는 신호처리 시스템이 필요하다. 따라서 본 논문에서는 선형예측계수를 사용하여 잡음량을 인식하는 방법을 제안하며, 본 잡음량 인식은 다양한 배경잡음에 의하여 열화된 3종류의 음성이 신경회로망에 의하여 학습되어진다. 본 실험에서는 Aurora2 데이터베이스를 사용하여 여러 잡음에 대하여 평균적으로 약 97.6% 이상의 양호한 인식결과를 확인할 수 있었다.

• 전기학회논문지
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• 제61권7호
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• pp.1019-1023
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• 2012

This paper considers a model predictive control problem of discrete-time constrained systems with time-varying delay. For this problem, a delay dependent state feedback control approach is used to achieve asymptotic stabilization of systems with input constraints. Based on Lyapunov stability theory, a new stability condition is obtained via linear matrix inequality formulation to find cost monotonicity condition of the model predictive control algorithm which guarantee the closed loop stability. Finally, the proposed method is applied to a numerical example in order to show the effectiveness of our results.

• Advances in Computational Design
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• 제7권2호
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• pp.113-128
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• 2022

Water consumption is strongly affected by numerous factors, such as population, climatic, geographic, and socio-economic factors. Therefore, the implementation of a reliable predictive model of water consumption pattern is challenging task. This study investigates the performance of predictive models based on multi-layer perceptron (MLP), multiple linear regression (MLR), and support vector regression (SVR). To understand the significant factors affecting water consumption, the stepwise regression (SW) procedure is used in MLR to obtain suitable variables. Then, this study also implements three predictive models based on these significant variables (e.g., SWMLR, SWMLP, and SWSVR). Annual data of water consumption in Thailand during 2006 - 2015 were compiled and categorized by provinces and distributors. By comparing the predictive performance of models with all variables, the results demonstrate that the MLP models outperformed the MLR and SVR models. As compared to the models with selected variables, the predictive capability of SWMLP was superior to SWMLR and SWSVR. Therefore, the SWMLP still provided satisfactory results with the minimum number of explanatory variables which in turn reduced the computation time and other resources required while performing the predictive task. It can be concluded that the MLP exhibited the best result and can be utilized as a reliable water demand predictive model for both of all variables and selected variables cases. These findings support important implications and serve as a feasible water consumption predictive model and can be used for water resources management to produce sufficient tap water to meet the demand in each province of Thailand.

• 대한토목학회논문집
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• 제26권1D호
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• pp.59-66
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• 2006

이 연구는 도시고속도로의 진입연결로 접속부내 선형의 밀도예측모형 구축에 관한 연구로서 실시간 교통특성분석과 선형의 밀도예측모형 구축 및 검증을 통해 밀도예측모형 구축에 있어서 결정계수($R^2$)값이 대체적으로 0.7이상으로 나타나 선형회귀모형구축에 상당히 높은 설명력을 보이는 것으로 나타났고, 선형모형검증에 있어서 상관계수(r)값도 대체적으로 0.8 이상으로 상당히 높은 상관성을 보이는 것으로 나타났다. 따라서 향후 선형의 밀도예측모형을 이용하여 도시고속도로의 진입연결로 접속부내 차량의 밀도추정 및 지체분석에 상당히 유효할 것으로 판단된다.

• 드라이브 ㆍ 컨트롤
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• 제16권2호
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• pp.22-29
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• 2019

This study presented a model predictive tracking control algorithm of autonomous truck based on object state estimation using extended Kalman filter. To design the model, the 1-layer laser scanner was used to estimate position and velocity of the object using extended Kalman filter. Based on these estimations, the desired linear path for object tracking was computed. The lateral and yaw angle errors were computed using the computed linear path and relative positions of the truck. The computed errors were used in the model predictive control algorithm to compute the optimal steering angle for object tracking. The performance evaluation was conducted on Matlab/Simulink environments using planar truck model and actual point data obtained from laser scanner. The evaluation results showed that the tracking control algorithm developed in this study can track the object reasonably based on the model predictive control algorithm based on the estimated states.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.344-344
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• 2000

Recently, the demand for high precision and large stroke in linear positioning systems is increasing in industry. A coarse-fine position control system composed of a linear motor and a piezoelectric actuator has such characteristics. Many optimal control laws have been applied to the position control of coarse-fine actuators but most of them did not take account into constraints. In this study, model predictive control (MPC) method with constraints is applied to the position control of the coarse-fine actuator and the performance of MPC is compared with those of conventional control laws.

• 제어로봇시스템학회논문지
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• 제2권4호
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• pp.344-350
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• 1996

An adaptive predictive level control of waste heat steam boiler was studied by using mathematical models considering the inverse response. The simulation experiments of the model identification were performed by using linear and bilinear models. From the results of simulations it was found that the bilinear model represented the actual dynamic behavior of steam boiler very well. ARMA model was used in the model identification and the adaptive predictive controller. To verify the performance and effectiveness of the adaptive predictive controller used in this study the simulation results of the adaptive predictive level control for waste heat steam boiler based on bilinear model were compared to those of P, PI and PID controller. The results of simulations showed that the adaptive predictive controller provides the fast arrival to setpoint of liquid level.