• 전기학회논문지
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• 제66권7호
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• pp.1149-1154
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• 2017

In this paper, we propose a sensorless multi-function controller applicable for deep well water pumps using current detection method. The proposed system overcomes various drawbacks of existing sensored system and additional features like Over current protection function due to overload, Under current protection function for idling at low water level and Relay function for starting single phase motors and acts as a level indicator to detect water lever in real time by the current detection method. A prototype of the multi-function controller system is designed and all of its functions are tested in the laboratory. The application of the proposed controller ensures reduction in the power consumption and maintenance cost in the facilities like water and septic tanks, drainage and waste water system, oil and chemical tanks where deep well pumps are used.

• 한국정밀공학회지
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• 제20권2호
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• pp.112-119
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• 2003

Generally, PID controller is not suitable to control multi variable system because it is very difficult to tune the PID gains. However, this paper shows that it is not hard to tune the PID gains if we can find a Jacobian matrix of the system. The Jacobian matrix expresses the ratio of output variations according to input variations. It is possible to adjust the input values in order to reduce the output error using the Jacobian. When the colt function is composed of error related terms, the gradient approach can tune the PID gains to minimize the function. In simulation, a hydrofoil catamaran with two inputs and two outputs is applied as a multi variable system. We can easily get the multi variable PID controller by the proposed teaming method. When the controller is compared with LQR controller, the performance is as good as that of LQR controller with a modeling equation.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2009년도 정보 및 제어 심포지움 논문집
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• pp.320-322
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• 2009

Support vector learning attracts great interests in the areas of pattern classification, function approximation, and abnormality detection. In this pater, we design the controller using support vector regression which has good properties in comparison with multi-layer perceptron or radial basis function. The applicability of the presented method is illustrated via an example simulation.

• 한국정밀공학회지
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• 제22권8호
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• pp.34-41
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• 2005

Generally, it is not easy to get a suitable controller for multi variable systems. If the modeling equation of the system can be found, it is possible to get LQR control as an optimal solution. This paper suggests an LQR learning method to design LQR controller without the modeling equation. The proposed algorithm uses the same cost function with error and input energy as LQR is used, and the LQR controller is trained to reduce the function. In this training process, the Jacobian matrix that informs the converging direction of the controller Is used. Jacobian means the relationship of output variations for input variations and can be approximately found by the simple experiments. In the simulations of a hydrofoil catamaran with multi variables, it can be confirmed that the training of LQR controller is possible by using the approximate Jacobian matrix instead of the modeling equation and this controller is not worse than the traditional LQR controller.

• 한국정보전자통신기술학회논문지
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• 제14권5호
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• pp.385-393
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• 2021

본 논문에서는 차량 멀티코어 프로세서를 통한 ESC(Electronic Stability Control) 시스템을 위한 멀티코어 기반 제어기를 제시한다. 차량용 멀티코어 프로세서와 ESC 시스템의 아키텍처를 고려할 때 ESC 소프트웨어의 전체 수행 시간은 멀티코어에 최적화되어 있다. 일반적으로 차량용 멀티코어 시스템에서는 코어 간 동기화, 멀티코어에 대한 테스크 할당, 코어 종속 변수에 대한 메모리 할당을 고려해야 한다. 본 논문에 사용된 ESC 시스템은 초기화, SlipRatio 계산, YawRate 계산, ABS, 통신으로 구성된다. 제안된 설계 방법을 기반으로 싱글코어 프로세서는 멀티코어 프로세서로 확장된다. ESC 시스템은 기능 모듈 할당, 세마포어, 인터럽트, 코어 별 변수 할당과 같은 멀티코어 최적화 방법을 사용하여 멀티코어 제어기로 재설계된다. 실험 결과로 멀티코어 프로세서의 수행 시간이 싱글코어 프로세서에 비해 59.7% 단축되었다.

• Journal of Advanced Marine Engineering and Technology
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• 제39권10호
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• pp.1031-1036
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• 2015

Proportional-integral-derivative (PID) controllers are widely used in industrial sites. Most tuning methods for PID controllers use an empirical and experimental approach; thus, the experience and intuition of a designer greatly affect the tuning of the controller. The representative methods include the closed-loop tuning method of Ziegler-Nichols (Z-N), the C-C tuning method, and the Internal Model Control tuning method. There has been considerable research on the tuning of PID controllers for single-input single-output systems but very little for multi-input multi-output systems. It is more difficult to design PID controllers for multi-input multi-output systems than for single-input single-output systems because there are interactive control loops that affect each other. This paper presents a tuning method for the PID controller for a two-input two-output system. The proposed method uses a real-coded genetic algorithm (RCGA) as an optimization tool, which optimizes the PID controller parameters for minimizing the given objective function. Three types of objective functions are selected for the RCGA, and each PID controller parameter is determined accordingly. The performance of the proposed method is compared with that of the Z-N method, and the validity of the proposed method is examined.

• 제어로봇시스템학회논문지
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• 제2권4호
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• pp.297-305
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• 1996

In this paper a novel robust adaptive fuzzy controller for the nonlinear system with state-dependent uncertainty is proposed. The conventional adaptive fuzzy controller determines the function of state variable bounding the state-dependent uncertain term in the system dynamics on the local state space by off-line calculation. Whereas the proposed method determines that function by the fuzzy inference so that it guarantees the stability of the closed loop system globally on the whole state space. In addition, the method is applicable to the multi-input system. We applied the proposed method to the Burn Control of the Tokamak fusion reactor whose dynamics contains the state-dependent uncertainty and proved the effectiveness of the scheme by using the simulation results.

• Journal of information and communication convergence engineering
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• 제21권1호
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• pp.45-53
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• 2023

This study constructs various scenarios required for landscape lighting; furthermore, a large-capacity general-purpose multifunctional controller is designed and implemented to validate the operation of the various scenarios. The multi-functional controller is a large-capacity general-purpose controller composed of a drive and control unit that controls the scenarios and colors of LED modules and an LED display unit. In addition, we conduct a computer simulation by designing a control system to represent the most appropriate color according to the input values of the temperature, illuminance, and humidity, using the neuro-control system. Consequently, when examining the result and output color according to neuro-control, unlike existing crisp logic, neuro-control does not require the storage of many data inputs because of the characteristics of artificial intelligence; the desired value can be controlled by learning with learning data.

• 반도체디스플레이기술학회지
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• 제13권4호
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• pp.37-42
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• 2014

Stable running is a very important factor when we are building a control system. But, sometimes malfunction of the system controller is caused by several reasons. To solve these problems, some systems have prepared a backup controller. In the generality of cases, making a backup controller is no easy work. Especially, it becomes more difficult when many backup controllers have to be embodied in one system. In this paper, the multi-backup function controller which was implemented in the form of the network type distributed control system will be suggested. Also, using Arago Disk System that has a structure for inner loop control, the validity of the proposed methods will be verified.

• International Journal of Control, Automation, and Systems
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• 제3권2호
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• pp.217-224
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• 2005

Generally, the underwater flight vehicle (UFV) depth control system operates with the following problems: it is a multi-input multi-output (MIMO) system because the UFV contains both pitch and depth angle variables as well as multiple control planes, it requires robustness because of the possibility that it may encounter uncertainties such as parameter variations and disturbances, it requires a continuous control input because the system that has reduced power consumption and acoustic noise is more practical, and further, it has the speed dependency of controller parameters because the control forces of control planes depend on the operating speed. To solve these problems, an adaptive fuzzy sliding mode controller (AFSMC), which is based on the decomposition method using expert knowledge in the UFV depth control and utilizes a fuzzy basis function expansion (FBFE) and a proportional integral augmented sliding signal, is proposed. To verify the performance of the AFSMC, UFV depth control is performed. Simulation results show that the AFSMC solves all problems experienced in the UFV depth control system online.