• Title/Summary/Keyword: vector tracking loop

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Sensorless Control of Non-salient PMSM using Rotor Position Tracking PI Controller (회전자 위치 추정 PI 제어기를 이용한 비돌극형 PMSM 센서리스 제어)

  • Lee Jong-Kun;Seok Jul-Ki;Lee Dong-Choon;Kim Heung-Geun
    • The Transactions of the Korean Institute of Electrical Engineers B
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    • v.53 no.11
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    • pp.664-670
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    • 2004
  • This paper presents a new velocity estimation strategy of a non-salient permanent magnet synchronous motor (PMSM) drive without high frequency signal injection or special PWM pattern. This approach is based on the d-axis current regulator output voltage of the drive system that has the information of rotor position error. The rotor velocity can be estimated through a rotor position tracking PI controller that controls the position error to zero. For zero and low speed operation, PI controller gains of rotor position tracking controller have a variable structure according to the estimated rotor velocity. In order to boost the bandwidth of PI controller around zero speed, a loop recovery technique is applied to the control system. The proposed method only requires the flux linkage of permanent magnet and is insensitive to the parameter estimation error and variation. The designers can easily determine the possible operating range with a desired bandwidth and perform the vector control even at low speeds. The experimental results show the satisfactory operation of the proposed sensorless algorithm under rated load conditions.

Hierarchical State Feedback Control of Large-Scale Discrete-Time Systems with Time-Delays (시간지연이 있는 대규모 이산시간 시스템의 계층적 상태궤환제어)

  • 김경연;전기준
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.26 no.8
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    • pp.1161-1166
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    • 1989
  • In this paper, a hierarchical state feedback control method is proposed for the optimal tracking of large-scale discrete-time systems with time-delays. The state feedback gain matrix and the compensation vector are computed from the optimal trajectories of the state variables and control inputs obtained hierarchically by the open-loop control method based on the interaction prediction method. The resulting feedback gain matrix and the compensation vector are optimal for the given initial condition. Computer simulation results show that the proposed method has better control performance and fewer second level iterations than the Tamura method.

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An Improvement in Adaptive Estimation for a Tracking System with Additive Measurement Impulse noise (충격성 잡음이 혼입되는 추적계통의 적응 추정 개선)

  • 윤현보;박희창
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.12 no.5
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    • pp.519-526
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    • 1987
  • An adaptive estimation system which operates propoerly in the environments corrupted by additive impulse noise in addition to the white Gaussian noise has been proposed. A feed forward loop is inserted into the adaptive estimator proposed by R. L. Moose for a system with an unknown measurement bias by which the improved adaptive estimator is processed successfully without the sum of the time varying weights being zero even when the measurement system is added impulue noise. Successfully processed adaptive estimator has been obtained under the large impulse noise in addition to randomly varying unknown biases condition by giving sufficient large value to the elements of discrete vector on the computer simulation.

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Smart tracking design for aerial system via fuzzy nonlinear criterion

  • Wang, Ruei-yuan;Hung, C.C.;Ling, Hsiao-Chi
    • Smart Structures and Systems
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    • v.29 no.4
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    • pp.617-624
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    • 2022
  • A new intelligent adaptive control scheme was proposed that combines the control based on interference observer and fuzzy adaptive s-curve for flight path tracking control of unmanned aerial vehicle (UAV). The most important contribution is that the control configurations don't need to know the uncertainty limit of the vehicle and the influence of interference is removed. The proposed control law is an integration of fuzzy control estimator and adaptive proportional integral (PI) compensator with input. The rated feedback drive specifies the desired dynamic properties of the closed control loop based on the known properties of the preferred acceleration vector. At the same time, the adaptive PI control compensate for the unknown of perturbation. Additional terms such as s-surface control can ensure rapid convergence due to the non-linear representation on the surface and also improve the stability. In addition, the observer improves the robustness of the adaptive fuzzy system. It has been proven that the stability of the regulatory system can be ensured according to linear matrix equality based Lyapunov's theory. In summary, the numerical simulation results show the efficiency and the feasibility by the use of the robust control methodology.

Position Control of Induction Motor using Variable Structure Vector Control (가변구조 벡터제어를 이용한 유도전동기의 위치제어)

  • Lee, Y.J.;Kim, H.J.;Son, Y.D.;Kwon, W.J.
    • Proceedings of the KIEE Conference
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    • 1992.07b
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    • pp.1218-1220
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    • 1992
  • This paper presents the three section sliding mode control algorithm based on variable structure current controller design in a synchronous frame and indirect field oriented control method, and applies it to the position control of induction motor. This control scheme solves the problem of robustness loss during the reaching phase that occurs in a conventional VSC strategy, and ensures the stable sliding mode and robustness enhancement throughout an entire response. As the performance of a VSI fed induction motor drives depends on the characteristics of inner loop current controller, it is desired that the current controller have the fast tracking and robust nature. Therefore, we introduced the voltage mapping table based on the concept of voltage space vector for variable structure current control, and implemented fully digital control system using 16-bit microcontroller with on-chip peripherals without additional processing circuits. Simulation and experimental results confirm the validity of this control scheme for robust AC servo drive system of VSI fed induction motor.

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A Vector-Controlled PMSM Drive with a Continually On-Line Learning Hybrid Neural-Network Model-Following Speed Controller

  • EI-Sousy Fayez F. M.
    • Journal of Power Electronics
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    • v.5 no.2
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    • pp.129-141
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    • 2005
  • A high-performance robust hybrid speed controller for a permanent-magnet synchronous motor (PMSM) drive with an on-line trained neural-network model-following controller (NNMFC) is proposed. The robust hybrid controller is a two-degrees-of-freedom (2DOF) integral plus proportional & rate feedback (I-PD) with neural-network model-following (NNMF) speed controller (2DOF I-PD NNMFC). The robust controller combines the merits of the 2DOF I-PD controller and the NNMF controller to regulate the speed of a PMSM drive. First, a systematic mathematical procedure is derived to calculate the parameters of the synchronous d-q axes PI current controllers and the 2DOF I-PD speed controller according to the required specifications for the PMSM drive system. Then, the resulting closed loop transfer function of the PMSM drive system including the current control loop is used as the reference model. In addition to the 200F I-PD controller, a neural-network model-following controller whose weights are trained on-line is designed to realize high dynamic performance in disturbance rejection and tracking characteristics. According to the model-following error between the outputs of the reference model and the PMSM drive system, the NNMFC generates an adaptive control signal which is added to the 2DOF I-PD speed controller output to attain robust model-following characteristics under different operating conditions regardless of parameter variations and load disturbances. A computer simulation is developed to demonstrate the effectiveness of the proposed 200F I-PD NNMF controller. The results confirm that the proposed 2DOF I-PO NNMF speed controller produces rapid, robust performance and accurate response to the reference model regardless of load disturbances or PMSM parameter variations.