High-Precision Position Control of a Linear-Switched Reluctance Motor Using a Self-Tuning Regulator

Zhao, Siyuan; Cheung, N.C.; Gan, Wai-Chuen; Jin, Yang

doi:10.1109/tpel.2010.2051685

Cited by 46 publications

(12 citation statements)

References 11 publications

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“…The position signal x r is compared with the reference position signal x ref , and their corresponding position error e x is processed through a position controller to produce the thrust force command f X . The thrust force commands of each phase f XA , f XB , and f XC are produced by force distribution function (FDF) [11] according to the thrust force command f X and the position signal x r . With the position signal x r and the thrust force commands of each phase f XA , f XB , and f XC , the three-phase current command i XA , i XB , and i XC are obtained via inverse force functions.…”

Section: Control Strategymentioning

confidence: 99%

Nonlinear Modeling of the Inverse Force Function for the Planar Switched Reluctance Motor Using Sparse Least Squares Support Vector Machines

Huang

Cao

et al. 2015

IEEE Trans. Ind. Inf.

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In advanced manufacturing industry, planar switched reluctance motors (PSRMs) have proved to be a promising candidate due to their advantages of high precision, low cost, low heat loss, and ease of manufacture. However, their inverse force function, which provides vital phase current command for precise motion, is highly nonlinear and hard to be accurately modeled. This paper proposes a novel inverse force function using sparse least squares support vector machines (LS-SVMs) to achieve nonlinear modeling for precise motion of a PSRM. The required training and testing sets of sparse LS-SVMs are firstly obtained from experimental measurement. A sparse LS-SVMs regression is further developed using training set to accurately model the inverse force function. Accordingly, the function is tested via the testing set to assess its feasibility. Finally, the proposed approach is applied to the PSRM system with dSPACE controller for trajectory tracking, and its effectiveness and superior performance are verified through experimental results. Her research interests include design and control of planar switched reluctance motors, and control theory and its application.Guang-Zhong Cao (M'15) received the B.Sc., M.Sc., and Ph.D. degrees in electrical engineering and automation from Xi'an Jiaotong University, He has published more than 60 articles in refereed journals and conferences. His research interests include motor control, and control theory and its application.Zheng-You He (M'10-SM'13) received the B.Sc. and M.Sc. degrees in computational mechanics from Chongqing University, Chongqing, China, in 1992 and 1995, respectively, and the Ph.D. degree in electrical engineering from Southwest . His research interests include signal processing and information theory applied to power system, and application of wavelet transforms in power system. J. F. Pan received the B.Sc. degree in electrical engineering from ChangChun

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Section: Control Strategymentioning

confidence: 99%

Nonlinear Modeling of the Inverse Force Function for the Planar Switched Reluctance Motor Using Sparse Least Squares Support Vector Machines

Huang

Cao

et al. 2015

IEEE Trans. Ind. Inf.

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“…To reduce propulsion force pulsations in the LSRM which is essential for elevators, the controlled multiphase excitation using the force distribution functions (FDF) is considered in [13]. To have an accurate position tracking, a self-tuning regulator based on the pole-placement algorithm is developed for the LSRM in [14]. Based on the nonlinear inductance modeling, an improved force distribution function is developed in [15] for the LSRMs to minimize the force ripple.…”

Section: Introductionmentioning

confidence: 99%

Instantaneous Thrust Control of the Linear Switched Reluctance Motors with Segmental Translator

Ganji

Zare

2019

Scientia Iranica

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The linear switched reluctance machine (LSRM) has all advantages of rotary switched reluctance machine including simple and rugged structure, absence of magnetic material and windings on translator, high reliability and appropriate performance over a wide range of speed. Like rotary switched reluctance motor with segmental rotor, segmental translator linear switched reluctance motor (STLSRM) has capability to produce higher output power/weight in comparison to the conventional linear switched reluctance motors. Due to high advantages of the STLSRM drive, various control algorithms including current control, model predictive control, direct force control, universal control and force distribution function are investigated for the first time to control the instantaneous thrust of this motor. Applying these algorithms to a typical three-phase STLSRM, simulation results are presented and they are compared together from the force ripple reduction point of view.

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“…However, force control in LMs still has some limitations. Since the power of any single motor-based control system is limited, the force control performance deteriorates severely if the load is beyond the capacity of the motor [6]. In spite of large load situations, the machine is often required to work for a certain period of time for overload operations with disturbances.…”

Section: Introductionmentioning

confidence: 99%

Complimentary Force Allocation Control for a Dual-Mover Linear Switched Reluctance Machine

et al. 2017

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This paper inspects the complementary force allocation control schemes for an integrated, dual-mover linear switched reluctance machine (LSRM). The performance of the total force is realized by the coordination of the two movers. First, the structure and characteristics of the LSRM are investigated. Then, a complimentary force allocation control scheme for the two movers is proposed. Next, three force allocation methods-constant proportion, constant proportion with a saturation interval and error compensation, and the variable proportion allocation strategies-are proposed and analyzed, respectively. Experimental results demonstrate that the complimentary force interaction between the two movers can effectively reduce the total amount of force ripples from each method. The results under the variable proportion method also show that dynamic error values falling into 0.044 mm and −0.04 mm under the unit ramp force reference can be achieved. With the sinusoidal force reference with an amplitude of 60 N and a frequency of 0.5 Hz, a dynamic force control precision of 0.062 N and 0.091 N can also be obtained.

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High-Precision Position Control of a Linear-Switched Reluctance Motor Using a Self-Tuning Regulator

Cited by 46 publications

References 11 publications

Nonlinear Modeling of the Inverse Force Function for the Planar Switched Reluctance Motor Using Sparse Least Squares Support Vector Machines

Nonlinear Modeling of the Inverse Force Function for the Planar Switched Reluctance Motor Using Sparse Least Squares Support Vector Machines

Instantaneous Thrust Control of the Linear Switched Reluctance Motors with Segmental Translator

Complimentary Force Allocation Control for a Dual-Mover Linear Switched Reluctance Machine

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