• Journal of Power Electronics
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• 제18권5호
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• pp.1409-1423
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• 2018

Compared with classical linear controllers, a nonlinear controller can result in better control performance for the nonlinear uncertainties of continuously variable transmission (CVT) systems that are driven by a synchronous reluctance motor (SynRM). Improved control performance can be seen in the nonlinear uncertainties behavior of CVT systems by using the proposed mingled revised recurrent Hermite polynomial neural network (MRRHPNN) control with mend ant colony optimization (ACO). The MRRHPNN control with mend ACO can carry out the overlooker control system, reformed recurrent Hermite polynomial neural network (RRHPNN) control with an adaptive law, and reimbursed control with an appraised law. Additionally, in accordance with the Lyapunov stability theorem, the adaptive law in the RRHPNN and the appraised law of the reimbursed control are established. Furthermore, to help improve convergence and to obtain better learning performance, the mend ACO is utilized for adjusting the two varied learning rates of the two parameters in the RRHPNN. Finally, comparative examples are illustrated by experimental results to confirm that the proposed control system can achieve better control performance.

• 전기학회논문지P
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• 제58권3호
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• pp.249-256
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• 2009

The widely used control theory based design of PI family controllers fails to perform satisfactorily under parameter variation, nonlinear or load disturbance. In high performance applications, it is useful to automatically extract the complex relation that represent the drive behaviour. The use of learning through example algorithms can be a powerful tool for automatic modelling variable speed drives. They can automatically extract a functional relationship representative of the drive behavior. These methods present some advantages over the classical ones since they do not rely on the precise knowledge of mathematical models and parameters. The paper proposes high performance speed and current control of synchronous reluctance motor(SynRM) drive using adaptive learning mechanism-fuzzy neural network (ALM-FNN) and fuzzy logic control (FLC) controller. The proposed controller is developed to ensure accurate speed and current control of SynRM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. Also, this paper proposes the analysis results to verify the effectiveness of the ALM-FNN, FLC and ANN controller.

• 전기학회논문지P
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• 제51권2호
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• pp.68-76
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• 2002

This paper presents an implementation of high-dynamic performance control system of Reluctance Synchronous Motor (RSM) drives for an industrial servo system with direct torque control (DTC). The problems of DTC for high-dynamic performance and maximum efficiency RSM drives are the nonlinear variable flux and inductance due to a saturated stator linkage flux and nonlinear inductance curve with various load currents. The accurate estimation of the stator flux and torque are obtained using stator flux observer of which a saturated inductance Ld and Lq can be compensated by using the adapted neural network from measuring the modulus and angle of the stator current. To obtain fast torque response and maximum torque/current with varying load current, the reference command flux is ensured by imposing Ids=Iqs. This control strategy is proposed to fast response and optimal efficiency for RSM drive. In order to prove rightness of the suggested control algorithm, we have some actual experimental system using 6000 pulse/rev encoder at ${\pm}10$ and ${\pm}1500rpm$. The developed digitally high-performance control system are shown some good response characteristics of control results and high performance features using 1.0kW RSM of which has 2.57 Ld/Lq salient ratio.

• 전자공학회논문지SC
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• 제39권6호
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• pp.59-70
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• 2002

본 논문에서는 최적 효율과 고성능으로 동작하는 SynRM(Synchronous Reluctance Motor)을 위한 위치 및 속도 센서리스 벡터제어를 제시한다. 제시한 제어 방법은 고정자 전압과 전류의 자속 추정에 기초한다. 그리고 동손과 철손을 최소화하는 효율 최적화의 전류각 조건은 SynRM의 등가회로를 기초로 유도한다. 폐루프 위치 및 속도 제어의 연구결과는 최적화 제어의 입증하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 학술대회 논문집 전문대학교육위원
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• pp.135-141
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• 2002

This paper presents an implementation of high-dynamic performance of position sensorless motion control system of Reluctance Synchronous Motor(RSM) drives for an industrial servo system with direct torque control(DTC), The problems of DTC for high-dynamic performance and maximum efficiency RSM drive due to a saturated stator linkage flux and nonlinear inductance curve with various load currents, The accurate estimation of the stator flux and torque are obtained using stator flux observer of which a saturated inductance Ld and Lq can be compensated by adapting from measurable the modulus and angle of the stator current space vector. To obtain fast torque response and maximum torque/current with varying load current, the reference command flux is ensured by imposing Ids=Iqs. This control strategy is proposed to fast response and optimal efficiency for RSM drive. In order to prove rightness of the suggested control algorithm, the actual experiment carried out at ${\pm}$20 and ${\pm}$1500 rpm. The developed digitally high-performance control system are shown some good response characteristic of control results and high performance features using 1.0kW RSM of which has 2.57 Ld/Lq salient ratio.

• 조명전기설비학회논문지
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• 제12권4호
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• pp.128-135
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• 1998

돌극형 동기 릴럭턴스 전동기의 고속회전 영역에서, 철손의 영향은 무시할 수 없게 된다. 본 논문에서는 돌 극형 동기 릴럭턴스 전동기에 대하여 고정자 철손이 고정자 내의 둥가 와전류에 의해서 발생한다는 가정 하에서, 둥가 인덕턴스에 직렬로 등가 철손저항이 삽입된 모델을 이용하여 철손을 고려한 전압방정식을 유도하였다. 또, 동작 주파수의 증가에 따른 철손의 변동은 벡터제어계의 제어성능을 악화시키고,d 축과 q 축의 쇄교자속에 서로 간섭하여 벡터제어의 적용을 어렵게 한다. 따라서, d 축과 q 축을 비간섭화 하여 철손저항의 영향을 제거해서 비간섭 토크제어가 가능한 벡터제어법올 제안하였으며, 시뮬레이션올 통하여 이를 확인하였다.

• Journal of Magnetics
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• 제16권1호
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• pp.74-76
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• 2011

Interior permanent-magnet synchronous motors (IPMSMs) produce both magnetic and reluctance torques. The reluctance torque is due to the difference between the d- and q-axis inductances based on the geometric rotor structure. The steady-state performance analysis and precise control of the IPMSMs greatly depend on the accurate determination of the parameters. The three essential parameters of the IPMSMs are the armature flux linkage of the permanent magnet, the d-axis inductance, and the q-axis inductance. In the basic design step of an IPMSM, the inductance parameters are very important for determining the motor characteristics, such as the input voltage, torque, and efficiency. Thus, it is very important to accurately estimate the values of the motor inductances. The inductance parameters of IPMSMs have nonlinear characteristics along the magnet size because the iron core is saturated by the magnet and armature reaction fluxes. In this study, the inductance parameters were calculated using both the magnetic-equivalent-circuit method and the finite-element method (FEM). Then the calculated parameters were compensated by the saturation coefficient function, which was also calculated via the magnetic-equivalent-circuit method and FEM.

• Journal of Power Electronics
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• 제19권3호
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• pp.771-783
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• 2019

Due to nonlinear-synthetic uncertainty including the total unknown nonlinear load torque, the total parameter variation and the fixed load torque, a synchronous reluctance motor (SynRM) driving a continuously variable transmission (CVT) system causes a lot of nonlinear effects. Linear control methods make it hard to achieve good control performance. To increase the control performance and reduce the influence of nonlinear time-synthetic uncertainty, an admixed recurrent Gegenbauer orthogonal polynomials neural network (ARGOPNN) with a modified particle swarm optimization (MPSO) control system is proposed to achieve better control performance. The ARGOPNN with a MPSO control system is composed of an observer controller, a recurrent Gegenbauer orthogonal polynomial neural network (RGOPNN) controller and a remunerated controller. To insure the stability of the control system, the RGOPNN controller with an adaptive law and the remunerated controller with a reckoned law are derived according to the Lyapunov stability theorem. In addition, the two learning rates of the weights in the RGOPNN are regulating by using the MPSO algorithm to enhance convergence. Finally, three types of experimental results with comparative studies are presented to confirm the usefulness of the proposed ARGOPNN with a MPSO control system.

• 한국소음진동공학회논문집
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• 제12권1호
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• pp.73-81
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• 2002

This paper introduces a four-Pole Lorentz force type self-bearing motor in which a new winding configuration is proposed to enable the sing1e winding to function both as a synchronous PM motor and as a magnetic bearing. The Lorentz force type has some good points such as the linearity of control force, freedom from flux saturation, and high efficiency, unlike conventional self-bearing motors using a reluctance force. And also, compared with the previously proposed eight-pole type, this four-pole self-bearing motor is more profitable for high rotational speed. In this paper, mathematical expressions of torque and radial force in the proposed self-bearing motor are derived to show that they can be separately controlled regardless of rotational speed and time. For verification of the theory, a prototype is made, where a ring-shape outer rotor is actively controlled in two radial directions while the other motions are passively stable supposing the radial stability. Through some experiments. it is shown that the proposed scheme can provide high capability and feasibility for a small high-speed self-bearing motor.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2000년도 전력전자학술대회 논문집
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• pp.513-516
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• 2000

최근들어 에너지와 가격문제가 대두 되면서 고효율, 저가격의 모터가 절실히 요구되고 있다 이런관점에서 SRM(Switched Reluctanec Motor)는 유도전동기에 비해 기계적으로 견고하고 자기적으로 간단하며 기동 토크가 큰 장점이 있다 가격측면에서 SRM은 BLDC모터에 비해 장점은 있지만 기존 유도기에 비하면 가격의 상승은 피할 수 없는 상황이다. 본 논문은 기존 유도기와 같은 수준의 가격을 제시할 수 있는 인버터 드라이브 방식을 구현하였고 효율은 유도기 대비 월등한 수준을 실현 하였다.