This article presents the application of model predictive control (MPC) in high-performance drives. A wide variety of machines have been considered: Induction machines, synchronous machines, linear motors, switched reluctance motors, and multiphase machines. The control of these machines has been done by introducing minor and easy-to-understand modifications to the basic predictive control concept, showing the high flexibility and simplicity of the strategy. The second part of the article is dedicated to the performance comparison of MPC with classical control techniques such as field-oriented control and direct torque control. The comparison considers the dynamic behavior of the drive and steady-state performance metrics, such as inverter losses, current distortion in the motor, and acoustic noise. The main conclusion is that MPC is very competitive concerning classic control methods by reducing the inverter losses and the current distortion with comparable acoustic noise. 

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Latest Advances of Model Predictive Control in Electrical Drives—Part II: Applications and Benchmarking With Classical Control Methods

This two-part survey presents the recent advances and developments of predictive control in switched reluctance machine drives. The aim is to highlight the potential of using predictive control to enhance the performance of these drives and make them more competitive with respect to conventional AC drives. The second part of this review presents the contributions in predictive torque control. The different approaches adopted in the literature regarding phase torque distribution, modelling and switching behaviour are discussed and analyzed in order to identify the current challenges and suggest future research. Further applications of predictive control are also described and a general conclusion on future applications and potential research based on the literature review are directed.

A Review of Predictive Control Techniques for Switched Reluctance Machine Drives. Part II: Torque Control, Assessment and Challenges

A model predictive position control (MPPC) method based on a parametric regression model is proposed in this paper, to achieve high-precision positioning for a planar switched reluctance motor (PSRM) developed in the laboratory. First, the mechanism model of the PSRM system represented by a discrete-time state space model is given. To reduce modeling error caused by the uncertainty, a two-order parametric regression model is then used to describe the PSRM. With the thrust force input signal and the position output signal, the parameters of this model are obtained by using a recursive least squares method with forgetting factor. Based on the built model, a predictive model is established to predict the future position. By defining a cost function, an optimized control action sequence is obtained with the predictive model. Additionally, a comparison is performed experimentally. The experimental results verify the effectiveness of the proposed MPPC for high-precision positioning.

Model Predictive Position Control for a Planar Switched Reluctance Motor Using Parametric Regression Model

Minimization of torque ripple in switched reluctance motor based on MPC and TSF

This document presents the development of a Proportional Integral Derivative (PID) and a Fuzzy-PID, for the control of the level of the MPS PA plant, which is constituted by industrial sensors and actuators. The mathematical model and the parameters of the system were obtained using the software the MATLAB environment using a STM32F4 card. The experimental results show the robustness of the Fuzzy PID, because it improves the response of the system and its parameters are tuned automatically according to the state of the process, thus enhancing the performance of the system. Besides, the conventional PID controller requires an adjustment of its parameters to operate in an optimal for each change of variable, and it does not respond efficiently to disturbances.

Development and Analysis of a PID Controller and a Fuzzy PID

This paper proposes a fuzzy proportional-integral-derivative (PID) control for the planar switched reluctance motor (PSRM) to realize precision positioning. The mathematical model of the PSRM is first given. Then a fuzzy proportional-derivative (PD) controller is designed for the PSRM, which features strong robustness to parametric variation, uncertainty, and interference. The fuzzy PD control of the PSRM is carried out via simulation based on MATLAB. Compared with the PD controller, the control performance of the PSRM with the fuzzy PD controller is superior. The effectiveness of the proposed control is verified through the simulation results.

Fuzzy PID control of the planar switched reluctance motor for precision positioning

This paper proposes a multi-segment sliding mode (MSSMC) method for the planar switched reluctance motor (PSRM) developed in the laboratory to achieve precision positioning. The mechanical structure, the mathematic model and the control strategy are first given. Based on the mathematic model, the MSSMC strategy is then designed, which consists of an acceleration segment, a deceleration segment, and a positioning segment. Additionally, the stability analysis is discussed for the closed-loop system with the designed MSSMC strategy. Simulation is carried out based on MATLAB/Simulink. Compared to the conventional sliding mode control (SMC), the MSSMC is capable of weakening and better steady-state and dynamic performances were achieved. The effectiveness of the proposed MSSMC method is verified through simulation.

Multi-Segment Sliding Mode Control of the Planar Switched Reluctance Motor for Precision Positioning

This paper presents an analytical nonlinear model of a magnetic levitation system (MLS)developed in the laboratory for applications of contactless operations at a microscale. Cylindrical permanent magnets and iron-core electromagnetics are used to build a desired hybrid magnetic field of the MLS. Three linear Hall-effect sensors are employed to detect the position of the levitation object, in which two sensors are used to detect the two-dimensional horizontal position of the levitation object and the third sensor is used to detect the levitation object whether it is in the working space. The nonlinear magnetic flux density model of the MLS is first deduced and then the magnetic force of the levitation object is derived by using the deduced model. Based on the deduced model, the mathematical relation of the current supplied to the electromagnet, the magnetic force and position of the levitation object is obtained and analyzed. Furthermore, the installation of the linear Hall-effect sensors was determined theoretically. Finally, the effectiveness of the nonlinear modeling of the MLS developed in the laboratory is validated by finite element analysis.

Nonlinear Modeling of a Magnetic Levitation System

The embodiment of the invention discloses a magnetic levitation motor and a stator structure thereof. The stator structure of the magnetic levitation motor comprises a plurality of first multiphase coil units arranged along a first direction, wherein the total length occupied by any first multi-phase coil unit in the first direction is equal to the polar distance, any first multi-phase coil unit comprises a plurality of first single-phase coils which are arranged in a lap winding mode in the first direction, any first single-phase coil comprises a plurality of first single-turn coils connectedin series, and the plurality of first single-turn coils are arranged in at least one layer along a third direction; the first single-turn coil is in a pattern with two straight edges which extend along the second direction and are arranged along the first direction; and the first direction, the second direction and the third direction are perpendicular to one another. According to the technical scheme of the embodiment of the invention, the influence of the coil skin effect can be reduced, the eddy current of the stator coil array is reduced, the copper loss of the stator coil array is reduced, the electromagnetic damping force of the stator coil array is reduced, and the motor thrust density is improved.

Fu Xingdong

Papers

Model Predictive Position Control for a Planar Switched Reluctance Motor Using Parametric Regression Model

Fuzzy PID control of the planar switched reluctance motor for precision positioning

Multi-Segment Sliding Mode Control of the Planar Switched Reluctance Motor for Precision Positioning

Nonlinear Modeling of a Magnetic Levitation System

Magnetic levitation motor and stator structure thereof