• KIEAE Journal
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• 제15권4호
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• pp.105-110
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• 2015

Purpose: This study aimed at finding the optimal input variables of the artificial neural network-based predictive model for the optimal controls of the indoor temperature environment. By applying the optimal input variables to the predictive model, the required time for restoring the current indoor temperature during the setback period to the normal setpoint temperature can be more precisely calculated for the cooling season. The precise prediction results will support the advanced operation of the cooling system to condition the indoor temperature comfortably in a more energy-efficient manner. Method: Two major steps employing the numerical computer simulation method were conducted for developing an ANN model and finding the optimal input variables. In the first process, the initial ANN model was intuitively determined to have input neurons that seemed to have a relationship with the output neuron. The second process was conducted for finding the statistical relationship between the initial input variables and output variable. Result: Based on the statistical analysis, the optimal input variables were determined.

• 한국통신학회논문지
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• 제27권6A호
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• pp.562-567
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• 2002

잡음 예측 최대 유사도(noise predictive maximum likelihood, NPML) 검출기는 잡음 예측/백색화 과정을 비터비 검출기의 가지 메트릭 계산 과정에 삽입하여 데이터 검출의 신뢰성을 높이게 된다. 따라서 기존의 PRML 검출기에 잡음 예측기를 포함시킴으로써 그것의 실제 성능이 향상되고 복잡도가 줄어드는 이점이 있다. 본 논문에서는 선형 채널과 비선형 채널 하에서 랜덤 시퀀스와 런-길이 제한 (1,7) 시퀀스를 적용하여, 고밀도 수직 자기 기록 (1.7$\leq$K$_{p}$$\leq$3.0)에서 잡음 예측 PR-등화 신호에 의한 NP(1221)ML 검출 시스템이 보다 높은 타수의 PR(12321)ML 시스템보다 복잡도가 낮으면서 우월한 성능을 나타냄을 모의 실험을 통해 분석, 검증하였다.

• 한국지능시스템학회논문지
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• 제13권1호
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• pp.24-30
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• 2003

본 논문에서는 혼돈 시스템을 제어하기 위해 웨이블릿 신경 회로망을 예측기로 사용하여 일반형 예측 제어기를 설계하는 방법을 제안한다. 본 논문의 방법에서는 웨이블릿 신경 회로망의 각 파라미터에 대한 학습은 예측 오차를 이용한 경사 하강법에 의해 수행되며, 제어 신호는 웨이블릿 신경 회로망의 출력과 기준 신호 사이의 제어 오차를 최소화함으로써 생성된다. 한편, 모의 실험을 통해 본 논문에서 제안한 제어기를 각각 연속 시간 혼돈 시스템인 Doffing 시스템과 이산 시간 혼돈 시스템인 Henon 시스템에 적용하여 제어기의 효율성을 확인하고 아울러 신경 회로망을 이용한 예측 제어의 결과와 비교함으로써 제어기의 우수성을 검증한다

• 로봇학회논문지
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• 제15권3호
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• pp.277-285
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• 2020

A differential drive wheeled robot is a kind of mobile robot suitable for indoor navigation. Model predictive control is an optimal control technique with various advantages and can achieve excellent performance. One of the main advantages of model predictive control is that it can easily handle constraints. Therefore, it deals with realistic constraints of the mobile robot and achieves admirable performance for trajectory tracking. In addition, the intention of the robot can be properly realized by adjusting the weight of the cost function component. This control technique is applied to the local planner of the navigation component so that the mobile robot can operate in real environment. Using the Robot Operating System (ROS), which has transcendent advantages in robot development, we have ensured that the algorithm works in the simulation and real experiment.

• Journal of Power Electronics
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• 제15권1호
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• pp.202-215
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• 2015

This paper investigates the stability and performance of model predictive controlled active-front-end (AFE) rectifiers for energy storage systems, which has been increasingly applied in power distribution sectors and in renewable energy sources to ensure an uninterruptable power supply. The model predictive control (MPC) algorithm utilizes the discrete behavior of power converters to determine appropriate switching states by defining a cost function. The stability of the MPC algorithm is analyzed with the discrete z-domain response and the nonlinear simulation model. The results confirms that the control method of the active-front-end (AFE) rectifier is stable, and that is operates with an infinite gain margin and a very fast dynamic response. Moreover, the performance of the MPC controlled AFE rectifier is verified with a 3.0 kW experimental system. This shows that the MPC controlled AFE rectifier operates with a unity power factor, an acceptable THD (4.0 %) level for the input current and a very low DC voltage ripple. Finally, an efficiency comparison is performed between the MPC and the VOC-based PWM controllers for AFE rectifiers. This comparison demonstrates the effectiveness of the MPC controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.301-304
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• 1997

Two options arising during implementation of an advanced model-based control system on a process with low-level loops are discussed. Strengths and deficiencies of the options are examined and methods to overcome the deficiencies are proposed. Simulation results of a CSTR and distillation column are presented to demonstrate the performance improvements.

• 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.

• 한국산업안전학회:학술대회논문집
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• 한국안전학회 2001년도 공동학술대회
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• pp.31-35
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• 2001

Recent trends require that access to the device/equipment information be provided from several locations or anywhere in the enterprise. One example is virtual machine/manufacturing system (VMS) where predictive maintenance is performed both on factory floor and in remote site through internet ［1］. Internet access is increasingly available and affordable, and along with the "internet" is the backbone of modern enterprise data networks. Typical functions of such a system includes monitoring and control for diagnosis and remedy action in realizing preventive maintenance.(omitted)

• 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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 F
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• pp.2028-2032
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• 1997

When a high performance current control is desired, a computation time delay of a digital control system may deteriorate the control performance of a current controller. Such a non-negligible effect can be considerable in transient state. This paper deals with the modified predictive current control that compensates the time delay effects of a conventional predictive current control. The method is closely related to a local average current control and a symmetrical PWM pattern generation. Also some theoretical approaches are presented to describe the voltage saturation boundary of the power converter. For validation, the proposed method is applied to an active power filter system. The experimental results show considerable improvement in current tracking capability.