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Permanent magnet synchronous motors (PMSM) have become prevalent in industry and play an essential role in managing industrial processes, automation systems, and renewable energy sources due to their superior efficiency, torque, and power density. However, because it operates like a non‐linear system with quick dynamics, variable parameters during operation, and unknown disturbances, PMSM presents challenges for machine control. Non‐linear controls are required to account for the non‐linearities of the permanent magnet synchronous machine. Recently, predictive control techniques for non‐linear multi‐variable systems have gained popularity. In this work, a novel approach to robust non‐linear generalized predictive control (RNGPC) has been developed for PMSM, with the aim of tracking the reference speed while maintaining minimum reactive power, robustness to external disturbances, and parameter uncertainties. A new finite horizon cost function is integrated, with an integral action introduced in the control law. The main advantage of this technique is that it does not require the measurement and observation of external disturbance as well as parametric uncertainties. The control strategy method has been tested in the MATLAB/Simulink environment with various operating conditions. The results showed good robustness against parameter changes and ensured fast convergence. In this work, a new approach of robust non‐linear generalized predictive controller (RNGPC) has been developed for permanent magnet synchronous motors (PMSM). The control objective is tracking the reference speed while maintaining minimum reactive power and robustness to external disturbances and parameter uncertainties.

This work uses multi-material topology optimization (MMTO) to maximize the average torque of a 3-phase permanent magnet synchronous machine (PMSM). Eight materials are considered in the stator: air, soft magnetic steel, three electric phases, and their three returns. To address the challenge of designing a 3-phase PMSM stator, a generalized density-based framework is used. The proposed methodology places the prescribed material candidates on the vertices of a convex polytope, interpolates material properties using Wachspress shape functions, and defines Cartesian coordinates inside polytopes as design variables. A rational function is used as penalization to ensure convergence towards meaningful structures, without the use of a filtering process. The influences of different polytopes and penalization parameters are investigated. The results indicate that a hexagonal-based diamond polytope is a better choice than the classical orthogonal domains for this MMTO problem. In addition, the proposed methodology yields high-performance designs for 3-phase PMSM stators by implementing a continuation method on the electric load angle.

Multiphase electrical machines are advantageous for many industrial applications that require a high power rating, smooth torque, power/torque sharing capability, and fault-tolerant capability, compared with conventional single three-phase electrical machines. Consequently, a significant number of studies of multiphase machines has been published in recent years. This paper presents an overview of the recent advances in multiphase permanent magnet synchronous machines (PMSMs) and drive control techniques, with a focus on dual-three-phase PMSMs. It includes an extensive overview of the machine topologies, as well as their modelling methods, pulse-width-modulation techniques, field-oriented control, direct torque control, model predictive control, sensorless control, and fault-tolerant control, together with the newest control strategies for suppressing current harmonics and torque ripples, as well as carrier phase shift techniques, all with worked examples.

This article established with the modeling and the field oriented control of permanent magnet synchronous machines, with a focus on their applications in variable speed domain in photovoltaic source.

This paper presents research on an unconventional electric machine. It is a hybrid excited machine which includes the features of three types of machines: the Permanent Magnet Synchronous Machine, the Synchronous Machine, and the Synchronous Reluctance Machine. Therefore, a broad literature review related to the above-mentioned types of machines was constructed. The well-known Permanent Magnet assisted Synchronous Reluctance Machine joins features of Permanent Magnet Synchronous Machine and Synchronous Reluctance Machine topologies. This paper shows the results of the innovative design of the Hybrid Excited Permanent Magnet assisted Synchronous Reluctance Machine, which additionally has advantages of the Synchronous Machine. In the article the basic methods of electromagnetic flux control and the designs using them are also presented. Finally, the results of simulation studies of the effect of the stator skew on the machine performance are described.

Self-bearing machines do not contain physical bearings but magnetic bearings. Both rotor rotary and spatial positions displacement are required in these types of machines to control the rotor position while it is levitating. Self-bearing machines often use external sensors for x (horizontal) and y (vertical) spatial position measurement, which will result in additional cost, volume, complexity, and number of parts susceptible to failure. To overcome these issues, this paper proposes a xy-position estimation self-sensing technique based on both main- and cross-inductance variation. The proposed method estimates x and y position based on inductive saliency between two sets of three-phase coils. The proposed idea is applied on a combined winding self-bearing machine which does not require additional suspension force winding. No additional search coil placement for xy-position estimation is required. Therefore, the proposed algorithm can result in a compact size self-bearing machine that does not require external sensors for xy-position measurement and suspension force winding.

Permanent magnet synchronous machines (PMSMs) are widely used in high-performance drive systems. However, parasitic torque ripple remains a critical limitation, causing acoustic noise, mechanical vibration, and speed fluctuations. This study presents a compact, model-based torque control strategy for surface-mounted PMSMs (SPMSMs) that suppresses torque ripple by generating a structured current reference. Grounded in the magnetic co-energy principle, the proposed method utilizes a deterministic analytical model to compensate for cogging torque and inductance harmonics, avoiding computationally intensive iterative estimators. A primary contribution involves adapting the harmonic injection profile to varying loads and magnetic saturation levels. Comprehensive finite element analysis (FEA) co-simulations demonstrate that the proposed method reduces torque ripple by approximately 87.5% and speed ripple by over 90% at 1500 RPM compared to conventional maximum torque per ampere (MTPA) strategies. Furthermore, extended dynamic analysis confirms superior robustness during start-up, transients, and low-speed operation (100 RPM), maintaining high control authority even under deep magnetic saturation (2.0 p.u.). Performance evaluations verify that this significant enhancement in torque quality is achieved with a negligible increase in total power losses (~2.1%), presenting a computationally feasible solution for industrial embedded platforms.

In this paper, the optimization of a harmonic-excited synchronous machine (HESM) is carried out. A two-phase harmonic exciter winding of the HESM provides brushless excitation and sufficient starting torque at any rotor position. The HESM under consideration is intended to be used for applications requiring speed control, especially in the field-weakening region. The novelty of the proposed approach is that a two-level optimization based on a two-stage model is used to reduce the computational burden. It includes a finite-element model that takes into account only the fundamental current harmonic (basic model). Using the output of the basic model, a reduced-order model (ROM) is parametrized. The ROM considers pulse-width-modulated components of the inverter output current, zero-sequence current injected into the stator winding, and harmonic excitation winding currents. A two-level optimization technique is developed based on the Nelder–Mead method, taking into account the significantly different computational complexity of the basic and reduced-order models. Optimization is performed considering two operating points: base and maximum speed. The results show that an optimized design provides significantly higher efficiency and reduced inverter power requirements. This allows the use of more compact and cheaper power switches. Therefore, the advantage of the presented approach lies in the computationally effective optimization of HESMs (optimization time is reduced by approximately three orders of magnitude compared to calculations using FEA alone), which enhances HESMs’ performance in various applications.

This paper deals with an optimal twisting sliding mode controller (OT-SMC) for the operation of a three phase permanent magnet synchronous machine (PMSM) in an electric vehicle (EV). In order to drive these vehicles, optimal performance is needed with robust control against real-time disturbances such as the variable load torque, uncertainties such as the parameters variation and speed variations between medium, low, and high speed as well as good performance characteristics for enhanced drive quality and longer battery time. Several conventional techniques have been applied to PMSM but they suffer from the problem of uncertainties and disturbances due to the PI regulator. A hybrid approach comprising of a robust nonlinear and optimal controller to achieve these objectives is attempted for driving electrical vehicles. This advanced hybrid controller obtained after the merger of sliding mode control (SMC) and a linear quadratic controller (LQR) is found to outperform existing controllers due to their superb performance characteristics. Furthermore, SMC is designed based on the exponential reaching law for the twisting sliding mode control (T-SMC) in order to ensure stability of the system while reducing the chattering, accelerating the rate of convergence with higher accuracy of the control performance, and the LQR is developed using the steady-state error method (N-LQR) in order to obtaining better performance characteristics. In addition, the hybridization between a twisting SMC and an optimal LQR is characterized by stabilizing and minimizing the oscillations in the permanent regime thus optimizing the system’s performance. Extensive simulation results illustrate the effectiveness and validity of the proposed control for achieving the highest performance of the PMSM.

An important characteristic of permanent magnet synchronous machines is that they are extremely efficient due to the absence of rotor losses, such as in induction motors, and the use of permanent magnets for field excitation. This makes them a superb choice for applications involving motors and generators. In motor applications, key considerations revolve around speed, torque, and how machine parameters are affected by changes in ambient circumstances. Regrettably, using permanent magnet synchronous motor is influenced by all these aspects. This allows researchers to develop successful hybridization approaches combining different advanced controls to achieve optimal control mechanisms for these motors. This work presents a hybridization of nonlinear and optimum controls for optimal performance of permanent magnet synchronous motor under varying operating conditions by combining backstepping control and linear quadratic regulator control. By including the error as a state variable and applying the linear quadratic regulator technique to determine the control law, the steady-state error is reduced. The optimal linear quadratic regulator technique is defined by stabilizing and reducing oscillations in the permanent magnet while increasing system performance based on steady-state error. Meanwhile, the backstepping control helps maintain the regime's stability in the face of disturbances, which are represented by variations in load torque, speed, and motor parameters. A comparison study was performed to assess the efficacy of the suggested system against two contemporary control techniques: Exponential reaching law-sliding mode control and model predictive control. The findings indicate the superiority of the recommended method. All simulations were performed using MATLAB/SIMULINK.