Control Of Permanent Magnet Synchronous Motor Research Articles

Analysis of Optimization Algorithms Used in Permanent Magnet Synchronous Motor Control According to Different Performance Indices

Permanent magnet synchronous motors (PMSM) can be produced at lower costs with new developments in magnet technology and are widely used in many industrial areas due to their low energy consumption. The widespread use of PMSM brings with it the requirement for high accuracy control performance. In order to achieve high performance accuracy, vector control technique is generally preferred. However, the parameter values of the controllers used in this technique are very important for motor performance. Tuning these parameters by optimization techniques instead of classical methods has become a popular topic. Nowadays, modern control methods show more effective control behavior than classical control methods, which has made the use of modern control methods widespread and studies on modern control methods have intensified. In this study, the analysis of different optimization algorithms used in the control of an PMSM according to their performance indices is investigated in Matlab-Simulink environment. As a result of simulation with different optimization algorithms under the same conditions, the analysis of optimization algorithms using different performance indices such as integral of the absolute value of the error (IAE), integral of the square of the error (ISE), Integral of the Square of the Error Multiplied by Time (ITSE), and Integral of the Absolute Error Multiplied by Time (ITAE) is carried out.

Model Predictive Current Control for Six-Phase PMSM with Steady-State Performance Improvement

The application of finite control set model predictive control (FCS-MPC) in six-phase permanent magnet synchronous motors (PMSMs) often faces a trade-off between computational burden and accurate voltage vector selection, as well as challenges related to harmonic components and torque generation. This paper introduces an improved model predictive current control (MPCC) method to address these problems. Firstly, 12 virtual voltage vectors are synthesized to improve torque output performance while suppressing harmonic currents. Then, to generate symmetrical switching signals and reduce switching loss, the largest basic vector used to synthesize the virtual vector is replaced by two medium vectors. Secondly, to solve the problem of the increased computational burden caused by the increase in discrete virtual vectors, a two-step vector selection method is proposed. In this method, each part is divided into several parts according to N, and the traditional cost function is also replaced by two-step functions. Different control performances can be achieved according to different values of N. Experimental results show that the proposed control scheme not only achieves stable current quality but also significantly improves steady-state performance throughout the entire speed range.

Advanced Venturini control for PMSM with modular multilevel matrix converter

This paper provides a comprehensive analysis of control strategies for modular multilevel matrix converters (MMMC) utilizing advanced second-order sliding mode control (ASOSMC) within the context of permanent magnet synchronous motor (PMSM) applications. The research introduces a novel control framework based on the Venturini method, which, when integrated with ASOSMC, achieves a unity input power factor while generating sinusoidal phase current waveforms with markedly reduced harmonic distortion. These advancements not only enhance overall system performance but also significantly improve power quality, addressing critical requirements in contemporary electrical engineering. Additionally, the study conducts a rigorous comparative analysis between classical Proportional Integral (PI) control and ASOSMC, elucidating the substantial limitations of PI control in nonlinear environments where dynamic adaptability is paramount. In contrast, ASOSMC demonstrates superior capability in managing disturbances and nonlinearities, thereby offering enhanced reliability and efficiency for MMMC systems. The findings illustrate that ASOSMC not only addresses the challenges posed by traditional control techniques but also contributes to the development of more robust control methodologies within power electronics. By establishing a clear superiority of ASOSMC over conventional methods, this research paves the way for future innovations in control strategies specifically tailored for high-performance applications that require resilience under varying operational conditions. Ultimately, this work underscores the necessity of integrating advanced control techniques to optimize the operational capabilities of modular multilevel converters, facilitating the creation of sophisticated solutions that meet the evolving demands of electrical systems and power quality enhancement in diverse applications. The implications of these findings are significant, offering foundational insights for both theoretical exploration and practical implementation in the field.

Robust model-based control and stability analysis of PMSM drive with DC-link voltage and parameter variations

To ensure a stable operation of Permanent Magnet Synchronous Motor (PMSM) drive under both DC link voltage and parameter variations, a robust control technique based on a new dynamic model that includes both drive’s and motor’s specifications is proposed in this paper. In the proposed controller, the first component of the drive’s control law consists of the d-component error of the stator current, and the second one is shaped based on the error in the square value of q-component of the stator current. To further deal with the dynamic alterations of the drive system, compensators are designed to reduce the adverse effects of rotor angular frequency variations and the difference between electrical and load torque errors. Another compensator based on the drive’s output power error is also placed at the q-component of the proposed control law. Moreover, a general operation curve (GOC) for the stator current is introduced to further assess the operation of the PMSM. In the next step, a comprehensive stability analysis verifying the stable operation of both d- and q-components of the stator current is performed using two closed-loop descriptions of the proposed control strategy. Several simulation results in MATLAB/SIMULINK environment are provided to verify the validity of the proposed control technique under various dynamic scenarios. It is worth mentioning that comparative results show that the proposed control technique compared to conventional PI controller has enabled the PMSM speed and torque to reach its 50% and 95% of their desirable values with respectively 42.9% and 28.6% less time. Also, the PMSM speed and torque responses due to proposed control technique have 75% less undershoot compared to conventional PI controller.

Experimental Implementation of a TD3 Agent Based Speed Controller for Direct Torque Control of PMSM Drives

This manuscript presents a novel control approach for Permanent Magnet Synchronous Motors (PMSMs) by integrating the widely used Direct Torque Control (DTC) method with Deep Reinforcement Learning (DRL), specifically the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm. The TD3 algorithm is well-suited to address the challenges posed by high-dimensional state and action spaces in PMSM drives. The conventional Proportional–Integral (PI) controller in the outer loop of DTC is replaced with the DRL based TD3 agent to overcome the limitations of traditional PI controllers, such as model dependency and complex parameter tuning. The DRL technique allows the agent to learn optimal control policies from experience, making it suitable for complex and nonlinear control problems. Extensive simulation studies demonstrate the effectiveness of the TD3-based control in achieving accurate speed tracking under varying operating conditions. Real-time experimental validation using a TMS320F28379D digital signal processor confirms the feasibility of the proposed DRL based approach. The research offers new insights into improving the performance of PMSM drives and paves the way for future advancements in electric drive control.

Study of permanent magnet synchronous motor control based on sliding mode observer

Study of permanent magnet synchronous motor control based on sliding mode observer

Experimental Passivity-based Control for PMSM

Abstract This paper presents the design, simulation and experimental validation of a Permanent-Magnet Synchronous Motor (PMSM) speed control. The technique applied was passivity based-control. All the process of design, simulation and experimental test is described for each state. The experimental test is carried out with the system TMDSHVMTRPFCKIT of Texas Instruments, all processes for implementation are described and the final diagram for obtaining the code. The simulation and experimental results validating the control strategy are illustrated and analysed.

Adaptive current decoupling control scheme based on online multi-parameter identification for high-speed permanent magnet synchronous motor in fuel cell

The precise control of centrifugal hydrogen compressor (CHC) driven by high-speed permanent magnet synchronous motor (PMSM) is the key to the stable and efficient operation of hydrogen fuel cell (HFC). In this paper, an adaptive current deviation decoupling control (CDDC) strategy based on variable step size affine projection algorithm (VSS-APAs) is proposed to solve the high-speed PMSM control problem caused by current cross-coupling and parameter perturbation under complex operating conditions. Firstly, the step size is dynamically adjusted by VSS-APA through a normalized gradient descent to respond to system fluctuations, achieving rapid parameter identification during dynamic changes and accurate tracking in steady states. Secondly, stator inductance, magnetic flux linkage, stator resistance, and disturbance torque are identified in two-time-scale based on the characteristics of parameter changes, overcoming the rank deficiency in motor mathematical equations. Finally, utilizing online-identified motor parameters, the gains of the CDDC are adjusted, and compensation is applied for back electromotive force (BEMF) and disturbance torque, thereby ensuring the control accuracy of the motor under parameter perturbations and system disturbances. Experimental results demonstrate that the proposed method enhances the responsiveness and accuracy of the control strategy through efficient parameters identification. Consequently, it guarantees high-efficiency and stable performance of the CHC across different working conditions, markedly advancing the overall functionality and dependability of hydrogen energy system.

Sensorless Control of Surface-Mount Permanent-Magnet Synchronous Motors Based on an Adaptive Super-Twisting Sliding Mode Observer

The Sliding Mode Observer (SMO) is widely used for the sensorless control of Permanent-Magnet Synchronous Motors (PMSMs) due to its simple structure and strong parameter robustness. However, traditional SMOs have a limited speed range and suffer from chattering issues, which affect the accuracy of rotor position estimation. To address these problems, this paper proposes an Adaptive Super-Twisting SMO (AST-SMO) method. First, a fast super-twisting function is designed to resolve the step problem that occurs at the zero-crossing of the traditional sign function. Next, an adaptive-tracking high-order Sliding Mode Observer is constructed to extend the speed range of the SMO. The stability of the system is proven using the Lyapunov theorem. Finally, a sensorless control system for PMSMs is implemented and validated in MATLAB/SIMULINK. The results indicate that, compared to the traditional SMO, the AST-SMO reduces the back EMF THD from 20.03% to 14.2%. Additionally, the rotor estimation error across all speed ranges is less than 0.01. Therefore, AST-SMO offers a higher tracking accuracy, a wider speed range, and effectively suppresses sliding mode chattering and harmonic interference.

Disturbance observer-based sliding mode control strategy of PMSM against mismatched disturbance

This paper presents a disturbance observer-based sliding mode control strategy of PMSM to address overcurrent and mismatched disturbances. A time-varying disturbance observer is proposed to reduce the influence of mismatched disturbances and estimated peaks. Then, an integral sliding mode control strategy with nonlinear term is designed in permanent magnet synchronous motor control output. Then, the sliding mode surface is constructed by combining the estimates of the mismatched disturbances and the integral sliding mode control. Furthermore, the stability proof of the proposed control strategy is developed. Experimental results are given to validate effectiveness of the proposed control strategy. The proposed control strategy can improve speed control performance under the mismatched disturbances and overcurrent.

An Improved Predictive Controller for PMSM based on Dual-Channel Feedback

Abstract High-performance and high-power-density DC servo drives of permanent magnet synchronous motors (PMSM) are applied to the military, especially in airborne optoelectronic pods, light mines, and launch turntables in the aerospace field. The above application scenarios require the volume of drivers to be smaller and have large power outputs. In the field of pods and light mines, high bandwidth and good tracking performance are required, especially in terms of steady-state accuracy. Since light mines are used for target tracking scanning, the errors at the end of the optical rotating mechanism are amplified tens or even hundreds of times after transmission through the line of sight to the target end. Therefore, the requirements for steady-state accuracy are extremely high. In this article, a predictive control method is proposed, using a sliding mode variable structure controller to make up for the error arising from system parameter changes in predictive control. Finally, a dual-channel rotary transformer feedback position coarse-fine combination algorithm method is studied to reduce the angular measurement error and further improve steady-state accuracy.

Improved control of permanent magnet synchronous motors using adaptive nonlinear control with Deadbeat Observer

Permanent Magnet Synchronous Motor (PMSM) control optimization is crucial for a variety of applications, including electric vehicles, industrial automation, and renewable energy systems (RESs). However, traditional control methods often struggle to adapt to the dynamic and non-linear nature of PMSMs, leading to sub-optimal performance. To address these challenges, this paper proposes a hybrid adaptive nonlinear control strategy with a deadbeat observer (DO) designed to improve the performance of PMSMs. This approach aims to improve the accuracy and robustness of the control while taking into account the system parameters variations and disturbances. Simulation tests comparing the proposed method with an adaptive nonlinear control (ANLC) are presented, highlighting its superior effectiveness in controlling PMSMs under varying load conditions and speed fluctuations. The proposed strategy achieves a maximum relative speed error around of 6% at 0.4 s under gradually varying load torque disturbances, which is better than the ANLC with 8%. Furthermore, under large speed variations, the suggested method maintains a maximum relative speed error of 0.82% at 0.85 s. Furthermore, the robustness assessment under system parameters variations, stator resistance, and inductance, shows extraordinary performances of the proposed scheme. These results highlight the effectiveness and robustness of the proposed strategy in achieving precise PMSM control while dynamically adapting to changing conditions. This research underscores the potential of our approach to advance key technologies, including electric vehicles, industrial automation, and renewable energy systems. By optimizing PMSM control, this strategy contributes to increased efficiency, reliability, and adaptability, facilitating broader adoption of electric propulsion systems and sustainable energy solutions.

Inductance Estimation Based on Wavelet-GMDH for Sensorless Control of PMSM

In permanent magnet synchronous motor (PMSM) sensorless drive systems, the motor inductance is a crucial parameter for rotor position estimation. Variations in the motor current induce changes in the inductance, leading to core magnetic saturation and degradation in the accuracy of rotor position estimation. In systems with constant load torque, the saturated inductance remains constant. This inductance error causes a consistent error in rotor position estimation and some performance degradation, but it does not result in speed estimation errors. However, in systems with periodic load torque, the error in the saturated inductance varies, consequently causing fluctuations in both the estimated position and speed errors. Periodic speed errors complicate speed control and degrade the torque compensation performance. In this paper, we propose a wavelet denoising-group method of data handling (GMDH) based method for accurate inductance estimation in PMSM sensorless control systems with periodic load torque compensation. We present a method to analyze and filter the collected three-phase current signals of the PMSM using wavelet transformation and utilize the filtered results as inputs to GMDH for training. Additionally, a method for magnetic saturation compensation using the inductance parameter estimator is proposed to minimize periodic speed fluctuations and improve control accuracy. To replicate the load conditions and parameter variations equivalent to the actual system, experiments were conducted to measure the speed ripples, inductance variations, and torque component of the current. Finally, software simulation was performed to confirm the inductance estimation results and verify the proposed method by simulating load conditions equivalent to the experimental results.

Fixed-time anti-disturbance constraint fuzzy synchronization control for PMSM based four-wheel-independent-drive EVs

A fixed-time anti-disturbance constraint fuzzy synchronization control method is proposed, for the sake of solving the problem of fast recovery of synchronization between in-wheel permanent magnet synchronous motors (PMSMs) in four-wheel-independent drive electric vehicles. The system model of in-wheel PMSM is presented in the beginning, and fuzzy logic systems are used for approximating the uncertainty parts of the PMSM model. Based on the PMSM model, a fixed-time disturbance-observer is designed to account for fast estimation of fluctuating load torque. Then, the neighborhood synchronization error is constructed based on a directed-graph, and a performance function is designed to guarantee the neighborhood synchronization error evolves strictly within the prescribed bound. Besides, the fixed-time bound of all signals is proved. Finally, the hardware-in-the-loop platform is built, and the electronic differential and the nonlinear vehicle model are employed to validate the advanced performance of the design control method.

Direct torque control for PMSM based on the RBFNN surrogate model of electromagnetic torque and stator flux linkage

Direct Torque Control (DTC) is widely used in motion control of motors. Classical DTC utilizes the Park transformation(dq-model) or observer to estimate the stator fluxlinkage and electromagnetic torque. However, the dq-model and observer lack descriptions of the cogging torque and magnetic saturation in permanent magnet synchronous motors (PMSM). This paper proposes a novel method based on the surrogate model to estimate stator fluxlinkage and torque for PMSM DTC. First, a finite element model (FEM) was established based on the parameters of PMSM. Using the FEM and Latin hypercube sampling (LHS), a surrogate model for estimating the stator fluxlinkage and torque of PMSM was constructed. The stator fluxlinkage and torque surrogate model, active flux observer, and dq current model under different control methods are constructed, respectively. The servo control parameters were tuned using the extended symmetric optimum algorithm, and simulation and experiments were conducted. Finally, electromechanical coupling models with a ball screw feed system were built based on various control and feedback methods. Simulation and experiment results indicate that the surrogate model reduces torque ripple, stator fluxlinkage offset, and feed system tracking error.

Synergizing Battery-Powered Permanent Magnet Synchronous Motor Control with Integrated Modular Multilevel Converter Systems

This proposed work presents a comprehensive examination of a modular multilevel converter (MMC) combined with a permanent magnet synchronous motor (PMSM) for battery energy management in applications. In order to provide effective energy transfer and dynamic control, the Modular Multilevel Converter serves as a bridge between the battery system and the Permanent Magnet Synchronous Motor drive. By cleverly controlling energy flow and minimizing losses during charging and discharging cycles, the combination of MMC with PMSM seeks to increase energy efficiency and prolong battery life. Since the energy source provides all of the power for the motor, it runs at a constant pace. When the accelerating mode finishes, the energy storage receives just enough power to maintain a steady voltage. The energy storage system utilizes the majority of the renewable power generated by the electric motor when it is in deceleration mode to raise the voltage in the system. During the subsequent acceleration mode, the stored energy might be released the MMC-BESS, which combines a modular multilevel converter with a battery energy storage system, is gaining popularity due to its high adaptability and dependability. This system integrates batteries into a sub module. Sub-modular capacitor voltage fluctuations are caused by the significant reactive power that is generated through the workings of modular multilevel converters. To reduce the fluctuation, large capacitance capacitors is required, which would significantly increase the system's capacity. The proposed approach means to upgrade energy proficiency and execution in electric vehicle applications. By joining the benefits of battery power with the flexibility of MMC frameworks, the arrangement offers upgraded control accuracy, decreased misfortunes, and further developed adaptation to non-critical failure. This combination works with consistent power the executives, guaranteeing ideal use of assets while meeting severe execution prerequisites. Through exhaustive examination and recreation, the adequacy of this incorporated framework is illustrated, displaying propelling the field of electric vehicle impetus and power conversion potential.

Adaptive PMSM Control of Ship Electric Propulsion with Energy-Saving Features

Electric ship propulsion is considered one of the most promising alternatives to conventional combustion systems. Its goal is to reduce the carbon footprint and increase a ship’s maneuverability, operational safety, and reliability. The high requirements for ship propulsion make permanent magnet synchronous motors (PMSMs) an attractive solution due to their characteristics. This paper discusses the control problem of a PMSM based on the input–output feedback linearization method combined with the optimal and adaptive control techniques. The method presented here integrates the parameter tuning process with the optimal design of the baseline controller. Since the load disturbances are treated as an additional unknown parameter, there is no need to introduce an integral action to deal with the resulting steady-state error. An important feature of the designed controller is the so-called energetic optimization of the system; i.e., in addition to the aforementioned adaptive and optimal controller, it has a feature of ensuring zero reactive power consumed by the system. The performed simulations of the machine speed stabilization process confirmed the high efficiency of the proposed controller despite the assumed uncertainty of the system parameters and environmental (load) disturbances. Besides achieving high-quality control, an essential feature of this approach is the elimination of the tuning problem.

Improved current control for PMSM via an active disturbance rejection controller

This article proposes an active disturbance rejection controller (ADRC) for regulating the dq axis currents of permanent magnet synchronous motors (PMSM). First, we establish actual PMSM model by considering ineluctable disturbances due to the variation of parameters, abrupt change of load, etc. Initially, we design dq axis current ADRCs incorporating an extended state observer (ESO). Compared to the commonly used proportional integral (PI) controller, the ADRC exhibits superior anti-interference capabilities in load and speed regulation. Secondly, we conduct a comprehensive analysis of ADRC’s key features, including ESO stability, dq-axis current tracking, and its anti-interference effectiveness in PMSM applications. Additionally, we offer methods for selecting parameters for both ADRC and ESO. Concurrently, we also examine the ADRC algorithm that utilizes a reduced-order extended state observer (RESO). The control performance of ADRC using RESO will be better than ESO. Finally, to verify the effectiveness of this method, we construct an experimental platform using the TMS320F28035. The results confirm the proposed method’s effectiveness.

Research on a Sensorless ADRC Vector Control Method for a Permanent Magnet Synchronous Motor Based on the Luenberger Observer

A sensorless vector active disturbance rejection control (ADRC) method for permanent magnet synchronous motors (PMSM) utilizing a Luenberger observer is presented. This method aims to address the challenges associated with weak active disturbances, substantial steady-state speed amplitude fluctuations, and difficulty in achieving a balance between overshoot and speed control in the sensorless PMSM control system. Mathematical models of the Luenberger observer and the ADRC were analyzed, leading to the proposal of a second-order ADRC control method based on the Luenberger observer. A mathematical model of the permanent PMSM has been introduced. Additionally, the necessary conditions for the convergence of the Luenberger observer were derived and examined. The allowable range of error feedback gain values was determined, and rotor position data were acquired using a phase-locked loop. The principle of the ADRC was analyzed, and the ADRC simulation results, along with the PI simulation results, were detailed. When the target speed is 1000 r/min, the steady-state error and load disturbance resistance of the ADRC control method outperform those of the PI control method. Finally, the control method was experimentally tested on an STM32F4 chip, demonstrating the advantages of small steady-state error and strong active disturbance ability.

FPGA-Based Speed Control Strategy of PMSM Using Improved Beetle Antennae Search Algorithm

To improve performance in terms of overshoot and motor response speed when a permanent-magnet synchronous motor (PMSM) with a proportional–integral (PI) controller is subjected to external disturbances, this paper proposes a speed control strategy based on an enhanced Beetle Antennae Search algorithm, which allows for adjustable parameters of the PI controller within a certain range. Firstly, to enhance the global and local search capabilities of each individual beetle, the step size was improved by linearly decreasing it. Secondly, a simulation model of a PMSM closed-loop control system was built to verify the effectiveness of the improved Beetle Antennae Search (BAS) algorithm. Finally, a linear feedback shift register model that generates four random numbers was developed on a field-programmable gate array (FPGA). The improved BAS algorithm for the PMSM control system was implemented on an FPGA using the Verilog hardware description language, and the feasibility of the system was verified through hardware simulation. Additionally, the hardware resource consumption on different FPGA platforms was analyzed. The simulation results demonstrate that the proposed new speed control strategy can reduce the overshoot and improve the motor response speed.