• International journal of advanced smart convergence
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• 제10권2호
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• pp.175-186
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• 2021

We have studied the speed regulation of the permanent magnet synchronous motor (PMSM) servo system in this paper. To optimize the PMSM servo system's speed-control performance with disturbances, a non-linear speed-control technique using a back-propagation neural network (BP-NN) algorithm forthe controller design of the PMSM speed loop is introduced. To solve the slow convergence speed and easy to fall into the local minimum problem of BP-NN, we develope an improved BP-NN control algorithm by limiting the range of neural network outputs of the proportional coefficient Kp, integral coefficient Ki of the controller, and add adaptive gain factor β, that is the internal gain correction ratio. Compared with the conventional PI control method, our improved BP-NN control algorithm makes the settling time faster without static error, overshoot or oscillation. Simulation comparisons have been made for our improved BP-NN control method and the conventional PI control method to verify the proposed method's effectiveness.

• Journal of Mechanical Science and Technology
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• 제18권3호
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• pp.379-387
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• 2004

A novel flatness sensing system which is called the Flatness Sensing Inter-stand Looper(FlatSIL) system is suggested and a self-tuning PI control system using the FlatSIL is designed for improving the flatness of hot strip in finishing mill processes. The FlatSIL system measures the tension along the direction of the strip width by using segmented rolls, and the tension profile is approximated through the tension of each segmented roll. The flatness control system is operated by using the tension profile. The proposed flatness control system as far as the tension profile-measuring device works for the full strip length during the strip rolling in finishing mills. The generalized minimum variance self-tuning (GMV S-T) PI control method is applied to control the flatness of hot strip which has a design parameter as weighting factor for updating the PI gains. Optimizing the design parameter in the GMV S-T PI controller, the Robbins-Monro algorithm is used. It is shown by the computer simulation and experiment that the proposed GMV S-T PI flatness control system has better performance than the fixed PI flatness control system.

• 디지털산업정보학회논문지
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• 제11권3호
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• pp.1-9
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• 2015

In this paper, we implemented the computer vision platform design with MEAN Stack through Raspberry PI 2 model which is an open source platform. we experimented the face recognition, temperature and humidity sensor data logging with WiFi communication under Raspberry Pi 2 model. Especially we directly made the shape of platform with 3D printing design. In this paper, we used the face recognition algorithm with OpenCV software through haarcascade feature extraction machine learning algorithm, and extended the functionality of wireless communication function ability with Bluetooth technology for the purpose of making Android Mobile devices interface. And therefore we implemented the functions of the vision platform for identifying the face recognition characteristics of scanning with PI camera with gathering the temperature and humidity sensor data under IoT environment. and made the vision platform with 3D printing technology. Especially we used MongoDB for developing the performance of vision platform because the MongoDB is more akin to working with objects in a programming language than what we know of as a database. Afterwards, we would enhance the performance of vision platform for clouding functionalities.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 전문대학교육위원
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• pp.136-138
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• 2005

The conventional self-tuning methods have the speed control problem of nonlinear BLDC motor which can't adapt against any kinds of noise or operation circumstances. In this paper, supposed to solve these problem to PI parameters controller algorithm using ANN. In the proposed algorithm, the parameters of the controller were adjusted to reduce by on-line system the error of the speed of BLDC motor. In this process, EBPA NN was constituted to an output error value of a BLDC motor and conspired an input and output. The performance of the self-tuning controller is compared with that of the PI controller tuned by conventional method(Z&N). The effectiveness of the proposed control method IS verified thought the Matlab Simulink.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.238-242
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• 1991

This paper presents an approach to self-tuning PI control of dynamic plants, based on fuzzy logic application. A fuzzy logic composed of linguistic conditional statements is employed by defining the relations of input-output variables of the controller. In the synthesis of a fuzzy logic controller, one of the most difficult problem is the selection of linguistic control rules and parameters. To overcome this difficulty, self-tuning fuzzy PI controller (STFPIC) with a hierarchical structure in which the fuzzy PI controller is assigned as the lower level and the rule modification and parameter adjustment as the higher level. The rules and parameters are generated by the adjustment of membership function through performance index(PE). In this paper, the algorithm for of the controller performance is estimated by means of computer simulation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 제39회 하계학술대회
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• pp.956-957
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• 2008

The paper is proposed maximum torque control of SynRM drive using Multi-PI controller. The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current ids for maximum torque operation is derived. The proposed control algorithm is applied to SynRM drive system controlled Multi-PI controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the analysis results to verify the effectiveness of the Multi-PI controller.

• Journal of Advanced Marine Engineering and Technology
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• 제24권5호
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• pp.97-102
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• 2000

In this paper, a methodology for designing a controller based on inverse dynamics for speed control of DC motors is presented. The proposed controller consists of a prefilter, the inverse dynamic model of a system and the PI controller. The prefilter prevents high frequency effects from the inverse dynamic model. The model of the system in characterized by a nonlinear equation with coulomb friction. The PI controller regulates the error between the set-point and the system output which may be caused by modeling error, variations of parameters and disturbances. The output which may be caused by modeling error, variations of parameters and disturbances. The parameters of the model and the PI controller are adjusted offlinely by a genetic algorithm. An experimental work on a DC motor system is carried out to illustrate the performance of the proposed controller.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1994년도 추계학술대회 논문집 학회본부
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• pp.165-168
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• 1994

The paper deals with the fuzzy PI control of a switched reluctance motor drive. Fuzzy algorithm based on linguistic rules describing the operator's control strategy is applied to speed control of the SRM. Simulation and experimental results show that performance of the furry PI controller is superior to that of conventional PI controller. In particular the robustness of the system is improved.

• Journal of Power Electronics
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• 제10권5호
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• pp.491-497
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• 2010

This paper proposes an estimation algorithm for the electrical parameters of synchronous reluctance motors (SynRMs) by using a synchronous PI current regulator at standstill. In reality, the electrical parameters are only measured or estimated in limited conditions without fully considering the effects of the switching devices, connecting wires, and magnetic saturation. As a result, the acquired electrical parameters are different from the real parameters of the motor drive system. In this paper, the effects of switching devices, connecting wires, and the magnetic saturation are considered by simultaneously using the short pulse and closed loop equations of resistance and synchronous inductances. Therefore, the proposed algorithm can be easily and safely implemented with a reduced measuring time. In addition, it does not need any external or additional measurement equipment, information on the motor's dimensions, and material characteristics as in the case of FEM. Several experimental results verify the effectiveness of the proposed algorithm.

• 전기전자학회논문지
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• 제24권1호
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• pp.154-160
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• 2020

본 논문에서는 계통연계인버터용 정지좌표기반 전류제어알고리즘을 제안한다. PI 제어기는 계통 연결 인버터의 전류 제어기로 사용되고 있다. 정지좌표기반 PI 제어기를 사용할 경우, AC 신호 제어로 인하여 정상 상태 오류와 위상지연현상이 발생한다. 본 논문에서는 전향보상기를 추가하여 명령 추적 성능을 높이고 과도 응답을 개선하는 방법을 제안한다. 또한 계통 전압을 외란으로 사용하여 계통 오류 발생 시 시스템을 보호하기 위해 외란을 측정 및 제거하는 제어 방법을 제안한다. 제안된 제어 방법은 수학적으로 유도하고 전달 함수로 표현하였으며 시뮬레이션을 통하여 검증하였다.