Planar Switched Reluctance Motor Research Articles

Nonlinear Dynamic Model-Based Position Control Parameter Optimization Method of Planar Switched Reluctance Motors

Currently, there are few systematic position control parameter optimization methods for planar switched reluctance motors (PSRMs); how to effectively optimize the control parameters of PSRMs is one of the critical issues that needs to be urgently solved. Therefore, a nonlinear dynamic model-based position control parameter optimization method of PSRMs is proposed in this paper. First, to improve the accuracy of the motor dynamics model, a Hammerstein–Wiener model based on the BP neural network input–output nonlinear module is established by combining the linear model and nonlinear model structures so that the nonlinear and linear characteristics of the system are characterized simultaneously. Then, a position control parameter optimization system of PSRMs is developed using the established Hammerstein–Wiener model. In addition, with a self-designed simulated annealing adaptive particle swarm optimization algorithm (SAAPSO), the position control parameter optimization system is performed offline iteratively to obtain the optimal position control parameters. Simulations and experiments are carried out and the corresponding results show that the optimal position control parameters obtained by the proposed method can be directly applied in the actual control system of PSRMs and the control performance is improved effectively using the obtained optimal control parameters.

Bipolar-Voltage-Injection-Based Position Estimation Method of Planar Switched Reluctance Motors Using Improved Flux Linkage Model

This article proposes a new position estimation method based on an unsaturated flux linkage model for planar switched reluctance motors (PSRMs). The bipolar-voltage-injection method is used to measure the flux linkage, and it is found that ripples caused by iron loss and aluminum eddy current with different amplitudes appear at the troughs of the flux curve. The effect of the losses on the flux linkage measurement is revealed in this article, and the loss compensation models are built based on the analysis. The improved flux linkage model is proposed with the loss compensation models. Then, the position estimation method is given with the improved flux linkage model. Flux linkage measurement result shows that the model with loss compensation has higher accuracy than the conventional model. Initial and planar-motion position estimation experiments are carried out for the PSRM. The initial position estimation error is from -0.4 to 0.4 mm. The planar-motion position estimation errors are from -1.1 to 1.1 mm in the X-axis and from -1.2 to 1.0 mm in the {Y-axis, and the effectiveness of the proposed flux linkage model is verified.

Sensorless Control of Planar Switched Reluctance Motors Based on Voltage Injection Combined With Core-Loss Calculation

In this article, a position estimation method is proposed to realize sensorless control of planar switched reluctance motor (PSRM) with core loss. First, a square-wave voltage generated through bipolar pulsewidth modulation (PWM) is injected into the idle phase of a PSRM, thereby generating core loss. The corresponding core-loss average power (CLAP), which contains position information, is calculated in real time. Then, depending on the six-phase CLAP, the initial position can be estimated for the PSRM startup. To stabilize the position estimation in different regions of pole pitches, position data measured in a long stroke are utilized to determine a function mapping from the CLAP with respect to position. Furthermore, a sensorless control system and commutation strategy are designed. Finally, the capability of different methods for position estimation and sensorless control of a PSRM system are experimentally investigated. The feasibility and effectiveness of the proposed method are verified through the experimental results.

An Assistant-Mover-Based Position Estimation Method for Planar Switched Reluctance Motors

An accurate mover position is important for a planar switched reluctance motor (PSRM) to achieve precision positioning; however, position sensors are susceptible to the influence from harsh conditions and are relatively expensive. In this article, an assistant-mover-based position estimation method is proposed to increase the reliability and reduce the cost of a PSRM system. The method is based on a mapping relationship between the flux density and position of the assistant mover. First, the configuration of the assistant movers is presented. Then, an analytical model of the flux density of the assistant mover is developed by using an equivalent magnetic circuit method. Based on the analytical model, the parameters of the assistant mover are determined. According to the flux density characteristics, a position estimation algorithm with the advantages of not requiring previous experimental data, simple computation, and small memory consumption is developed. Moreover, considering the deviation in the characteristics of each assistant mover, a compensation strategy is proposed to obtain better position estimation accuracy. Finally, the proposed method is implemented with the PSRM system. The effectiveness of the proposed position estimation method is verified experimentally.

Sliding-Mode-Observer-Based Position Estimation for Sensorless Control of the Planar Switched Reluctance Motor

This paper proposes a position estimation method for a planar switched reluctance motor (PSRM). In the method, a second-order sliding mode observer (SMO) is used to achieve sensorless control of a PSRM for the first time. A sensorless closed-loop control strategy based on the SMO without a position sensor for the PSRM is constructed. The SMO mainly consists of a flux linkage estimation, an adaptive current estimation, an observing error calculation, and a position estimation section. An adaptive current observer is applied in the current estimation section to minimize the error between the measured and estimated currents and to increase the accuracy of the position estimation. The flux linkage is estimated by the voltage equation of the PSRM, and the estimated flux linkage is then used to estimate the phase current in the adaptive current observer. To calculate the observing error of the SMO using the measured and estimated phase currents, the observing error of the thrust force is introduced to replace the immeasurable state error of the position and speed of the mover. The sliding surface is designed based on the error of the thrust force, and stability analysis is given. Once the sliding surface is reached, the mover position is then estimated accurately. Finally, the effectiveness of the proposed method for the PSRM is verified experimentally.

Design and Analysis of a Long-Stroke Planar Switched Reluctance Motor for Positioning Applications

This paper presents the design, control, and experimental performance evaluation of a long-stroke planar switched reluctance motor (PSRM) for positioning applications. Based on comprehensive consideration of the electromagnetic and mechanical characteristics of the PSRM, a motor design is first developed to reduce the force ripple and deformation. A control scheme with LuGre friction compensation is then proposed to improve the positioning accuracy of the PSRM. Furthermore, this control scheme is proven to ensure the stable motion of the PSRM system. Additionally, the response speed and steady-state error of the PSRM system with this control scheme are theoretically analyzed. Finally, the experimental results are presented and analyzed. The effectiveness of the precision long-stroke motion of the PSRM and its promise for use in precision positioning applications are verified experimentally.

Nonlinear Modeling of the Flux Linkage in 2-D Plane for the Planar Switched Reluctance Motor

This paper proposes a nonlinear flux linkage model in 2-D plane for the planar switched reluctance motor (PSRM). The inputs of the proposed model are the 2-D positions and the current, and the output is the flux linkage. The proposed model is established via a cascade-forward backpropagation neural network (CFNN). The designed CFNN consists of four layers: one input layer, two hidden layers, and one output layer. The first hidden layer has 20 neurons with a tan-sigmoid transfer function, and the second hidden layer has 20 neurons with a log-sigmoid transfer function. The output layer is a pure linear layer. The sample set with 179 755 samples is obtained experimentally in a dSPACE-based PSRM system by applying the dc excitation method. The sample set is divided into three sets. 35% and 30% of the samples are randomly chosen as the training sample set and validation sample set, respectively, and the remaining samples are utilized as the test sample set to assess the generalization performance of the CFNN-based model. According to the results of the test sample set, the maximum relative error is 11.05% and the mean relative error is 0.42% when the current ranges from 1 to 9 A. The CFNN has the capability to build a multi-input nonlinear model. The CFNN-based model is capable of reflecting the variations of flux linkage in 2-D plane caused by manufacturing tolerances. The effectiveness of the CFNN-based model is finally verified.

Noise characteristics of the planar switched reluctance motor

This article presents the analysis of the noise characteristics for the planar switched reluctance motor to enrich performance evaluation of the planar switched reluctance motor. The mechanical str...

Maximum-Force-per-Ampere Strategy of Current Distribution for Efficiency Improvement in Planar Switched Reluctance Motors

This paper proposes a novel maximum-force-per-ampere strategy for the current distribution of planar switched reluctance motors (PSRMs) for efficiency improvement. This strategy is the first of its kind for planar motors, and it is used to generate the desired thrust force with the minimum sum of squares of the three-phase current. To formulate this strategy, a constrained optimization problem with time-varying parameters is first developed. Then, the problem is transformed into an unconstrained problem with a barrier function. Additionally, a self-designed adaptive genetic algorithm is introduced to solve the unconstrained optimization problem for locating the optimal currents. Comparative studies of the proposed and conventional strategies for a PSRM system are carried out via simulation and experiment, and planar trajectory tracking for the system with the proposed strategy is experimentally performed. The validity of the proposed strategy is also verified.

Nonlinear Modeling of Electromagnetic Forces for the Planar-Switched Reluctance Motor

Planar switched reluctance motors (PSRMs) have the merits of simple structure, low cost, low heat loss, high precision, ease of manufacture, and strong adaptability of harsh environment, which directly transform the mechanical energy to electromagnetic energy available to planar motions without mechanical transmissions. Therefore, PSRMs are an attractive candidate in high-precision two-dimensional positioning devices [1], [2]. For PSRMs, accurate modeling of electromagnetic forces is the theoretical foundation of the design and control. However, electromagnetic forces are highly nonlinear and hard to be accurately modeled due to the inherently complex magnetic characteristics of PSRMs. There are primarily three methods utilized to model electromagnetic forces of switched reluctance motors (SRMs) up to now, which are the equivalent magnetic circuit method, the Maxwell stress method, and the virtual work method [3]-[5]. Additionally, the neuron network is also employed to model electromagnetic forces for a SRM [6]. Nevertheless, the modeling of electromagnetic forces for SRMs cannot be directly applied to PSRMs owing to their unique structure of magnetic circuit. For linear switched reluctance motors (LSRMs) and PSRMs, electromagnetic forces including thrust force and normal force have been modeled under linear magnetic circuit [7], [8], but the modeling of electromagnetic forces has not been formulated so far with consideration of magnetic saturation. Furthermore, the finite-element method (FEM) is frequently used to establish electromagnetic force model for SRMs, LSRMs and PSRMs [9]-[11], whereas FEM takes a long calculating time. Based on aforementioned analysis, the nonlinear modeling of electromagnetic forces has not been built analytically for PSRMs. Hence, it is necessary to derive the nonlinear modeling of electromagnetic forces for deeper investigation of PSRMs.

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

In the 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 first 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.

Optimization Design of the Planar Switched Reluctance Motor on Electromagnetic Force Ripple Minimization

In planar switched reluctance motors (PSRMs), the electromagnetic force ripple minimization is important to reduce the noise and vibration for high-precision motions. In this paper, an improved PSRM by optimization design for minimization of the electromagnetic force ripple is proposed. The structure, principle, and mathematical model of the PSRM are clarified. Based on Ansoft Maxwell, optimization design of the PSRM is performed by improved structure with smaller pole pitch and incremental number of mover poles. Experiments of the improved PSRM are implemented based on dSPACE. The experimental results verify that the improved PSRM effectively reduces electromagnetic force ripple with planar trajectory tracking.

Core Loss Analysis for the Planar Switched Reluctance Motor

Core loss is one of the key factors for performance evaluation of switched reluctance machines. In this paper, core loss analysis of the planar switched reluctance motor (PSRM) is calculated based on the 3-D time-stepping finite element methods. The numerical analysis for the computation of the core loss is discussed, also its transient and average core loss in the mover and the stator are calculated. The corresponding experiments of measurement loss for a PSRM prototype are conducted and the results validate the accuracy from the numerical analysis. It can be concluded that core loss dominates around the corner of the mover and stator cores.

A dual-loop position controller for the improved planar-switched reluctance motor

In industry, a precise two-dimensional, high-precision motion control system is in high demand. Compared with other types of two-dimensional direct-drive machines available, the planar-switched reluctance motor has the advantages of low-cost, simple structure and it can operate in wide temperature ranges. Considering the machine structure of the planar-switched reluctance motor prototype, mechanical improvements are performed and a compact planar-switched reluctance motor has been constructed with more mechanical robustness. Since dynamic response errors for the planar-switched reluctance motor-based position control system under a typical proportional–differential controller increases with the frequency of position reference, a dual-loop position controller cascaded to the proportional–differential regulator is proposed. Both simulation analysis and experimental results verify the position controller’s effectiveness of reduced dynamic errors with increased frequency and precise tracking of reciprocating motion command.

An adaptive controller for the novel planar switched reluctance motor

This paper proposes an adaptive control method for the planar switched reluctance motor (PSRM). Regarding to the mechanical deficiencies and control problems that exist in the prototype, a new machine with compact size and improved performance has been built. Following a brief simulation with finite element analysis (FEA), detailed adaptive controller design with online parameter identification is performed. Experimental results prove that the controller has good position control performance over PID algorithm in dynamic, static and robustness to disturbances. It is expected that the novel two-dimensional (2D) direct-drive machine with adaptive control strategy find its potential use in industrial applications.

On Control of Planar Switched Reluctance Motor

By using the energy dissipation theory and the property of the switched reluctance motor, this paper presents a nonlinear controller for the planar switched reluctance motors (PSRM). Based on the fact that the electrical time constant is much smaller than the mechanical time constant, the whole PSRM driving system is treated as a two-time-scale system and can be decomposed into two subsystems (electrical and mechanical) that are negative feedback interconnection. The controllers are designed for two subsystems respectively to ensure that they are passive. In view of the fact that the system made of two passive subsystem connected through negative feedback is still passive. Therefore, the stability of PSRM driving system is ensured in large scale. This control strategy possesses a simple structure and can be implemented easily. The experimental results show that the proposed control is effective for the position control of PSRM.

A Novel Planar Switched Reluctance Motor for Industrial Applications

A Novel Planar Switched Reluctance Motor for Industrial Applications

Auto-disturbance rejection controller for novel planar switched reluctance motor

A novel planar motor based on the switched reluctance (SR) principle has been developed. This motor has the advantages of simple structure, low cost and ease of manufacture. The motor is highly reliable and can work in hostile working environments. However, in many industrial applications, the motor's performance is subject to practical constraints, such as mechanical noise, load disturbance and friction. The motor cannot cope with these difficulties under classical PID control scheme. Therefore an auto-disturbance rejection control (ADRC) strategy is proposed to overcome these problems. An ADRC velocity control strategy is implemented on the planar motor, and its performance is then compared with a classical PID controller. Experiment results demonstrate that the motor is more resistant to disturbances under this new control scheme. It confirms that ADRC is an effective solution to overcome the inherent control problems of the SR planar motor. It is expected that the same method can be applied to other SR machines with the same promising results.

High-Precision Position Control of a Novel Planar Switched Reluctance Motor

This paper presents the position control of a novel two-dimensional (2-D) switched reluctance (SR) planar motor. The planar motor consists of a six-coil moving platform and a flat stator base made from laminated mild steel blocks. Unlike conventional x-y tables, which stack two moving slides on top of each other, the proposed 2-D planar motor has the advantages of simple mechanical construction, high reliability, and the ability to withstand harsh operating conditions. Together with the two linear encoders attached to the x-axis and y-axis, the motor can be controlled under closed-loop mode. To combat the problem of force nonlinearity, this paper proposes a cascade controller with force linearization technique to implement the drive controller. Due to the unique structure of the planar motor's magnetic circuit, there is very little coupling between the x-axis and y-axis, and no decoupling compensation is needed. Preliminary results show that the proposed SR planar motor has a positional accuracy of 5 /spl mu/m and a maximum acceleration/deceleration rate of 2 G.