• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 추계학술대회 논문집 전력기술부문
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• pp.144-147
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• 2006

A proportional intergral (PI) control strategy is commonly used for constant current and extinction angle control in a HVDC (High Voltage Direct Current) system. A PI control strategy is based on a stactic design where the gains of a PI controller are fixed. Since the response of a HVDC plant dynamically changes with variations in the operation point a PI controller performance is far from optimum. The contribution of this paper is the presentation of the design of a rough set based, fuzzy adaptive control scheme. Experimental results that compare the performance of the adaptive control and PI control schemes are also given.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1168-1172
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• 2004

This paper presents a speed controller based on an adaptive fuzzy algorithm for high performance permanent magnet synchronous motor (PMSM) drives under parameter and load variations. In many speed tracking control systems PI controller has been used due to its simple structure and easy of design. PI controller, however, suffers from the electrical machine parameter variations and disturbances. In order to improve the tracking control performance under load variations, the PI controller parameters are modified during operation by adaptive fuzzy method. This method based on optimal fuzzy logic system has simple structure and computational simplicity. It needs only sample data which is obtained by optimal controller off-line. As the sample data implemented in the adaptive fuzzy system can be modified or extended, a flexible control system can be obtained. Simulation results show the usefulness of the proposed controller.

• 제어로봇시스템학회논문지
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• 제14권10호
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• pp.969-976
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• 2008

A position control problem is studied for UEV(Unmanned Expedition Vehicles), which is to follow pre-determined paths via fixed way-points. Hybrid control systems are used for position control of UEV depending on the operating condition. Speed control consists of three controllers: PID control, adaptive PI control, and neural network. Heading control consists of two controllers, PID and adaptive PID control. The controllers are selected based on the changes of road conditions. We suggest an adaptive PI control algorithm for speed control and an transition management algorithm among the controllers. The algorithm adapts the road conditions and variation of vehicle dynamical characteristics and selects a suitable controller.

• 대한기계학회논문집
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• 제17권1호
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• pp.69-77
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• 1993

본 연구에서는 Koren과 Masory가 개발하여 적분제어기에 적용한 제어알고리즘 을, 제어기 반응속도를 향상시키기 위하여 비례적분제어기에 적용하는 방법을 제시하 고자 한다. 실험을 통하여 제어시스템을 모델링하고, 근궤적법을 이용하여 시스템을 안정하게 유지하기 위한 개회로 이득을 선정하며, 기존의 보통선반을 적응제어시스템 으로 개발하여 고정이득 비례적분제어기와 가변이득 비례적분제어기의 성능을 실험을 통하여 비교하고자 한다.

• Journal of Power Electronics
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• 제14권3호
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• pp.421-431
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• 2014

A DSP-based self-adaptive proportional-integral (PI) controller to control a DC-DC converter is proposed in this paper. The full-bridge topology is adopted here to obtain higher power output capability and higher conversion efficiency. The converter adopts the zero-voltage-switching (ZVS) technique to reduce the conduction losses. A parallel secondary active clamp circuit is added to deal with the voltage overshoot and ringing effect on the transformer's secondary side. A self-adaptive PI controller is proposed to replace the traditional PI controller. Moreover, the designed converter adopts the constant-current and constant-voltage (CC-CV) output control strategy. The secondary active clamp mechanism is discussed in detail. The effectiveness of the proposed converter was experimentally verified by an IGBT-based 10kW prototype.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.514-518
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• 2005

In this paper an adaptive fuzzy PI controller with feedback linearizing meth od is implemented to controlling flux and torque separately in induction motor. In this paper first decoupling of torque and flux which are outputs to be controlled, is achieved by using feedback linearization methodology. Then for reducing the effect of noise and rejection of disturbance, main part of controller which is adaptive PI fuzzy controller, is designed. Coefficients of PI controller are determined by defined fuzzy rules due to error dynamic. Inputs of fuzzy system are defined sliding surfaces which consist of torque and flux errors. The main contribution of this paper is effect reduction of noise and disturbance on torque and flux which is based on fuzzy logic and nonlinear control. At last the effectiveness of the proposed control scheme in presence of noise and load disturbance is simulated and comprised to applying sliding method. The results verify better effectiveness of the proposed method for effect reduction of noise and disturbance.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 B
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• pp.1142-1144
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• 2003

This Paper presents a speed controller based on the adaptive fuzzy tuning method for brushless DC(BLDC) motor drives under load variations. Generally, the speed tracking control systems use PI controller due to its simple structure and easy of design. PI controller, however, suffers from the electrical machine parameter variations and disturbances. In order to improve the tracking control performance under load variations, PI controller of which the parameters are modified during operation by adaptive fuzzy tuning method. This method based on optimal fuzzy logic system has simple structure and computational simplicity. It needs only sample data which is obtained by optimal controller off-line. As the sample data implemented in the adaptive fuzzy system can be modified or extended, a flexible control system can be obtained. Simulation results show the usefulness of the proposed controller.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 B
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• pp.1114-1116
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• 2000

A direct model reference adaptive control (DMRAC) is applied to the speed control of brushless do(BLDC) motor. The main objective is to achieve precise speed control in the face of varying motor parameters and load. The control is described as an outer loop speed control and an inner current loop control which has raster dynamics than the speed loop. The adaptive control is applied to the outer speed control loop. DMRAC is compared to an indirect adaptive controller(IMRAC) and a PI controller. Simulation results show that the two adaptive controllers give similar respose and are superior to the PI controller. However, the DMRAC algorithm is simpler to implement.

• 조명전기설비학회논문지
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• 제23권2호
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• pp.115-124
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• 2009

본 논문은 컨테이너 크레인의 속도 및 위치의 고성능 제어를 위하여 적응 퍼지제어를 제안하였다. 컨테이너 크레인의 전동기는 에너지 및 환경문제에 대한 강인성을 갖는 가변속 드라이브인 SynRM으로 설정하였다. 종래의 PI 제어기는 파라미터 변동 및 외부환경에 의하여 트롤리의 정확한 위치, 속도와 sway 각을 제어하는데 어려움이 있다. 이러한 문제점을 해결하기 위해 본 논문에서는 적응 퍼지제어를 설계하여 크레인에 적용된 SynRM 드라이브의 성능을 분석하였다. 본 논문에서는 종래의 PI 제어와 적응 퍼지제어의 위치 및 속도 응답특성을 분석하고 비교함으로써, 논문의 타당성을 입증하였다.

• 제어로봇시스템학회논문지
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• 제14권12호
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• pp.1218-1225
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• 2008

This paper presents the design of a neural network based adaptive control for missile is presented. The application model is Exocet MM40, which is derived from missile DATCOM database. Acceleration of missile by tail Fin control cannot be controllable by DMI (Dynamic Model Inversion) directly because it is non-minimum phase system. So, the inner loop consists of DMI and NN (Neural Network) and the outer loop consists of PI controller. In order to satisfy the performances only with PI controller, it is necessary to do some additional process such as gain tuning and scheduling. In this paper, all flight area would be covered by just one PI gains without tuning and scheduling by applying mixture control technique of conventional controller and NN to the outer loop. Also, the simulation model is designed by considering non-minimum phase system and compared the performances to distinguish the validity of control law with conventional PI controller.