• 조명전기설비학회논문지
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• 제25권7호
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• pp.15-25
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• 2011

This proposes an online loss minimization algorithm for series PI(SPI) based interior permanent magnet synchronous motor(IPMSM) drive to yield high efficiency and high dynamic performance over wide speed range. The loss minimization algorithm is developed based on the motor model. In order to minimize the controllable electrical losses of the motor and thereby maximize the operating efficiency, the d-axis armature current is controlled optimally according to the operating speed and load conditions. For vector control purpose, a SPI is used as a speed controller which enables the utilization of the reluctance torque to achieve high dynamic performance as well as to operate the motor over a wide speed range. Also, this paper proposes current control of model reference adaptive fuzzy controller(MFC), and estimation of speed using artificial neural network(ANN) controller. The proposed efficiency optimization control, SPI, MFC, ANN in this paper is applied to IPMSM drive system, the validity of this paper is proved by analyzing response characteristics in variety operating conditions.

• 한국지능시스템학회논문지
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• 제8권6호
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• pp.12-20
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• 1998

제어 환경의 변화에 강건하게 대처할 수 있는 제어 시스템을 개발하기 위해서, 본 논문에서는 자연계의 면역 시스템과 다층 신경망을 결합한 제어 시스템을 제안한다. 제안한 제어 시스템은 면역 알고리즘을 이용하여 다층 신경망의 가중치를 조절한다. 면역 알고리즘은 초기 방어 단계인 선천성 면역 알고리즘과 적응 단계인 적응 면역 알고리즘으로 구성되어 있다. 과거에 학습한 경험이 있는 환경과 유사한 환경에 대해서 선천성 면역 알고리즘이 동작하고, 학습한 경험이 없는 새로운 제어 환경의 변하에 대해서는 적응 면역 알고리즘이 동작한다. 면역 알고리즘을 이용한 제어 시스템을 로봇 매니퓰레이터의 궤적 추종 제어에 적용하였으며, 컴퓨터 모의 실험을 통해 제어 시스템의 성능을 평가한다.

• 융합신호처리학회논문지
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• 제23권4호
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• pp.185-193
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• 2022

본 논문은 쿼드로터 무인기의 위치 및 자세 추적 제어 성능을 향상시키기 위해 RBFNN 방식을 이용한 적응형 슬라이딩 모드 제어를 제안한다. RBFNN은 UAV 동적 모델에서 비선형 함수의 근사화에 활용되며, RBFNN의 가중치는 슬라이딩 표면에 부딪혀 미끄러지는 상태를 보장하기 위해 Lyapunov 안정성 분석의 적응 법칙에 따라 온라인으로 조정된다. 네트워크 근사 오류를 보상하고 기존 채터링 문제를 제거하기 위해 슬라이딩 모드 제어 항은 적응 법칙에 의해 조정되어 시스템의 강력한 성능을 향상시킨다. 제안된 제어 방법의 시뮬레이션 결과는 비선형 쿼드로터 무인 항공기에 적용된 제안된 제어기의 효율성을 확인하였다. 그 결과, 제안된 제어 시스템이 만족스러운 제어 성능과 견고성을 달성함을 알 수 있었다.

• Journal of Power Electronics
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• 제12권5호
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• pp.800-812
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• 2012

This paper analyses the mathematical model and control strategies of a Hybrid Active Power Filter with Injection Circuit (IHAPF). The control strategy based on the load harmonic current detection is selected. A novel control method for a IHAPF, which is based on the analyzed control mathematical model, is proposed. It consists of two closed-control loops. The upper closed-control loop consists of a single fuzzy logic controller and the IHAPF model, while the lower closed-control loop is composed of an Adaptive Network based Fuzzy Inference System (ANFIS) controller, a Neural Generalized Predictive (NGP) regulator and the IHAPF model. The purpose of the lower closed-control loop is to improve the performance of the upper closed-control loop. When compared to other control methods, the simulation and experimental results show that the proposed control method has the advantages of a shorter response time, good online control and very effective harmonics reduction.

• 전기학회논문지P
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• 제59권3호
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• pp.279-287
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• 2010

Interior permanent magnet synchronous motor(IPMSM) adjustable speed drives offer significant advantages over induction motor drives in a wide variety of industrial applications such as high power density, high efficiency, improved dynamic performance and reliability. This paper proposes efficiency optimization control of IPMSM drive using adaptive fuzzy learning controller(AFLC). In order to optimize the efficiency the loss minimization algorithm is developed based on motor model and operating condition. The d-axis armature current is utilized to minimize the losses of the IPMSM in a closed loop vector control environment. The design of the current based on adaptive fuzzy control using model reference and the estimation of the speed based on neural network using ANN controller. The controllable electrical loss which consists of the copper loss and the iron loss can be minimized by the optimal control of the armature current. The minimization of loss is possible to realize efficiency optimization control for the proposed IPMSM. The optimal current can be decided according to the operating speed and the load conditions. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using AFLC. Also, this paper proposes speed control of IPMSM using AFLC1, current control of AFLC2 and AFLC3, and estimation of speed using ANN controller. The proposed control algorithm is applied to IPMSM drive system controlled AFLC, the operating characteristics controlled by efficiency optimization control are examined in detail.

• 전자공학회논문지B
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• 제29B권8호
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• pp.15-23
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• 1992

Neural network control has many innovative potentials for fast, accurate and intelligent adaptive control. In this paper, two kinds of neurocontrol architectures for the dynamic control of robot manipulators are developed. One is based on a System Identification and Control scheme and the other is based on the Feedback-Error leaming scheme. Both of the proposed architectures use an inverse dynamic neurocontroller in parallel with a linear neurocontroller. The difference is that the first architecture uses the system identifier to get the signals used for training neurocontrollers, while the second architecture uses a properly defined energy function. Compared with the previous types of neurocontrollers which are using an inverse dynamic neurocontroller and a fixed PD gain controller, the proposed architectures not only eliminate the painful process of the fixed gain tuning but also exhibit superior peformances because the linear neurocontroller can adapt its gains according to the applied task. This superior performance is tested and verified through computer simulation of the dynamic control of the PUMA 560 arm.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2004년도 전력전자학술대회 논문집(2)
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• pp.944-948
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• 2004

This paper presents a simple torque estimation method and switching angle control of Switched Reluctance Motor (SRM) using Neural Network (NN). SRM has gaining much interest as industrial applications due to the simple structure and high efficiency. Adaptive switching angle control is essential for the optimal driving of SRM because of the driving characteristic varies with the load and speed. The proper switching angle which can increase the efficiency was investigated in this paper. NN was adapted to regulate the switching angle and nonlinear inductance modelling. Experimental result shows the validity of the switching angle controller.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 학술대회 논문집 전문대학교육위원
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• pp.115-121
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• 2000

본 논문에서는 진화연산 중에서 해의 다양성과 수렴속도면에서 좋은 성능을 나타내는 실수형 유전알고리즘과 신경회로망을 이용한 적응 퍼지제어기를 설계하였다. 실수형 유전알고리즘을 이용하여 퍼지제어기의 입 출력 이득과 실시간으로 퍼지제어기의 입 출력이득을 적응적으로 변경하는 신경회로망의 가중치를 튜닝하였다. 제안한 방법의 유용성을 평가하기 위해 시지연을 갖는 제어시스템[14]에 적용하였다. 컴퓨터 시뮬레이션 결과, 제안한 적응 퍼지제어기가 기존의 퍼지제어기보다 오버슈트, 정정시간, 상승시간면에서 더 우수한 제어성능을 나타내었다.

• 전기학회논문지
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• 제64권9호
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• pp.1356-1362
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• 2015

Modular snake-like robots are robust for failure and have flexible locomotions for obstacle environment than of walking robot. This requires an adaptation capability which is obtained from a learning approach, but has not been analysed as well. In order to investigate the property of adaptation of locomotion for different terrains, NEAT controllers are trained for a flat terrain and tested for obstacle terrains. The input and output characteristics of the adaptation for the neural network controller are analyzed for different terrains in frequency domain.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.43.6-43
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• 2001

In this paper, we describe an actor-critic method as a kind of temporal difference (TD) algorithms. The value function is regarded as a current estimator, in which two value functions have different inputs: one is an actual experience; the other is a simulated experience obtained through a predictive model. Thus, the parameter´s updating for the actor and critic parts is based on actual and simulated experiences, where the critic is constructed by a radial-basis function neural network (RBFNN) and the actor is composed of a kinematic-based controller. As an example application of the present method, a tracking control problem for the position coordinates and azimuth of a nonholonomic mobile robot is considered. The effectiveness is illustrated by a simulation.