Synchronous Motor System Research Articles

Model Reference Adaptive System of Permanent Magnet Synchronous Motor Based on Current Residual Compensation Without Position Measurement

Model Reference Adaptive System of Permanent Magnet Synchronous Motor Based on Current Residual Compensation Without Position Measurement

A Compact Wireless Permanent Magnet Synchronous Motor System With Precise Speed and Position Control

A Compact Wireless Permanent Magnet Synchronous Motor System With Precise Speed and Position Control

A sensorless control system of permanent magnet synchronous motor based on observation error threshold EKF

A sensorless control system of permanent magnet synchronous motor based on observation error threshold EKF

Improved Sliding Mode Model Reference Adaptive System Observer

In order to improve the accuracy and stability of sensorless control system of permanent magnet synchronous motor, considering the influence of external load torque on system performance, the symbol function of sliding mode control system of vehicle-mounted permanent magnet synchronous motor is prone to chattering and the robustness of traditional PI control is insufficient. In this paper, a method of combining Non-singular Fast Terminal Sliding Mode (NFTSM) and Model Reference Adaptive System (MRAS) is proposed. A Non-singular Fast Terminal Sliding Mode Controller (NFTSMC) is designed. A control strategy combining NFTSMC and Model Reference Adaptive System Observer (MRASO) (NFTSMC-MRASO) converts the observed torque value into torque current feedforward compensation to the current loop input. The large sliding mode gain is avoided, and the chattering problem of the system is overcome when the external disturbance is suddenly added. At the same time, the robustness of the system is improved under the premise of suppressing the chattering.

Vector control of permanent magnet synchronous motor based on self-disturbance rejection and PI parallel connection

Abstract Addressing the issue of susceptibility to disturbances in PMSM systems, a vector control system for permanent magnet synchronous motors with a self-disturbance rejection controller and PI parallel connection was designed. Firstly, the system’s speed error, electromagnetic torque, and load error are used as inputs for the self-disturbance rejection controller and PI control, respectively. Then, the self-disturbance rejection controller is connected in parallel with the PI and designed as a speed loop for PMSM to improve system stability. Finally, we use the improved sparrow algorithm to optimize the parameters of ADRC and enhance the overall performance of the system. The simulation results in Simulink indicate that parallel systems have fewer overshoots, higher stability, and better overall performance compared to ADRC and PI control.

Novel flexible fixed-time stability theorem and its application to sliding mode control nonlinear systems.

For the fixed-time nonlinear system control problem, a new fixed-time stability (FxTS) theorem and an integral sliding mode surface are proposed to balance the control speed and energy consumption. We discuss the existing fixed time inequalities and set up less conservative inequalities to study the FxTS theorem. The new inequality differs from other existing inequalities in that the parameter settings are more flexible. Under different parameter settings, the exact upper bound on settling time in four cases is discussed. Based on the stability theorem, a new integral sliding mode surface and sliding mode controller are proposed. The new control algorithm is successfully applied to the fixed-time control of chaotic four-dimensional Lorenz systems and permanent magnet synchronous motor systems. By comparing the numerical simulation results of this paper's method and traditional fixed-time sliding mode control (SMC), the flexibility and superiority of the theory proposed in this paper are demonstrated. Under the same parameter settings, compared to the traditional FxTS SMC, it reduces the convergence time by 18%, and the estimated upper bound of the fixed time reduction in waiting time is 41%. In addition, changing the variable parameters can improve the convergence velocity.

Optimal position collaborative control of dual permanent magnet synchronous motor system

In order to improve the control accuracy and synchronous performance of the multi-motor control system, this paper proposes an optimal position collaborative control strategy for dual permanent magnet synchronous motor system. Firstly, based on the mathematical model of permanent magnet synchronous motor, an incremental predictive model is established to suppress constant and slow time-varying disturbances caused by changes in rotational inertia and load torque. Afterwards, the predicted compensation amount after multi-step prediction is obtained by minimizing the cost function which contains the synchronous error and tracking error simultaneously, and compensated to the given current loop in advance without changing the original dual motor system structure. Then the controllability and observability of the system are analyzed, and it can be proved that the system is asymptotically stable based on the optimal control theory. Secondly, considering the constraints such as maximum voltage and current limits, the optimal solution under the constraints is output to obtain the reference currents i q1 and i q2. Finally, it is demonstrated through the experiments that the proposed control strategy can achieve advance prediction compensation control of synchronous error, and the dynamic response speed is improved, while ensuring its steady-state performance remains unchanged.

Hybrid FOT2F-FOPD controller for permanent magnet synchronization motor based on ILA optimization with SRF-PLL

Permanent magnet synchronous motor (PMSM) systems have gained popularity in various fields due to their advantages such as high speed, high accuracy, low maintenance, and high reliability. This paper presents the speed tracking control of a permanent magnet synchronous motor (PMSM) using a hybrid fractional order PI and type 2 fuzzy control with fractional order PD control (FOT2F-FOPD). The SRF-PLL observes the motor speed and estimates the rotor's position by interpreting the input voltages of the motor instead of using a sensor. Then, the controller parameters (gain, μ and λ) are tuned based on a novel optimization algorithm called Incomprehensible but Intelligible-in-time (IbI) Logics algorithm (ILA). The proposed controller enhances the performance of the system and regulates the speed of the motor under parameter variations such as the speed and the load. So, the proposed ILA (FOT2F-FOPD) controller is assessed using MATLAB/Simulink simulation and compared with other controller techniques. The proposed technique reduces the settling time, steady state error and overshoot by at least 65%, 54% and 53% respectively under load conditions compared with (PSO, optimized FOPD, FOPI and PI). While at no load condition, the settling time and the error are reduced by 31% and 12.5% respectively with no overshoot in output response. The results show a significant improvement in the performance of motors used with the application of the proposed controller and the employment of the (ILA) optimization compared with FOPI and PI controllers.

Composite control based on FNTSMC and adaptive neural network for PMSM system

In this paper, a novel fixed-time non-singular terminal sliding mode control (NFNTSMC) method with an adaptive neural network (ANN) is proposed for permanent magnet synchronous motor (PMSM) system to improve PMSM performance. For nominal PMSM system without disturbance, a novel fixed-time non-singular terminal sliding mode control is designed to achieve fixed-time convergence property to improve the dynamic performance of the system. However, parameters mismatch and external load disturbances generally exist in PMSM system, the controller designed by NFNTSMC requires a large switching gain to ensure the robustness of the system, which will cause high-frequency sliding mode chattering. Therefore, an adaptive radial basis function (RBF) neural network is designed to approximate the unknown nonlinear lumped disturbance including parameters mismatch and external load disturbances online, and then the output of the neural network can be compensated to the NFNTSMC controller to reduce the switching gain and sliding mode chattering. Finally, the fixed-time convergence property and stability of the system are proved by Lyapunov method. The simulation and experimental results show that the presented strategy possesses satisfactory dynamic performance and strong robustness for PMSM system. And the proposed control scheme also provides an effective and systematic idea of the controller design for PMSM.

Sliding mode observer-based fault diagnosis and continuous control set fault tolerant control for PMSM with demagnetization fault

A fault detection, estimation and fault tolerant control scheme for demagnetization fault in the permanent magnet synchronous motor systems is proposed in this paper. When demagnetization fault occurs, the system will deviate from the normal state severely. To facilitate the calculation, the demagnetization fault is converted to the dq coordinate system for processing and the resistance change is modeled as the system uncertainty, and the effect of the uncertainty on the system is analyzed. Then a fault detection observer is designed to detect the fault occurrence time, and a sliding mode observer based fault estimation algorithm is designed to estimate the fault and disturbance information. The observer parameters are determined by linear matrix inequality. When the fault information is obtained, a continuous control set fault tolerant control scheme is presented to minimize the impact of fault as far as possible. Finally, experimental results provide evidence of the feasibility of the suggested algorithm.

Real-time and hardware in the loop validation of electric vehicle performance: Robust nonlinear predictive speed and currents control based on space vector modulation for PMSM

The transport industry's environmental impact has prompted various stakeholders to focus more on electric vehicles as a potential solution. Extensive research on electric vehicle motor control reveals their complexity, highlighting the crucial role of the traction motor control mechanism being one of their essential subsystems. This study presents a novel approach to control the drive system of an electric vehicle's permanent magnet synchronous motor, using a robust non-linear model predictive control in a cascaded structure combined with a space vector modulation technique. The formulation of the robust non-linear model predictive control law involves optimizing a new cost function with the inclusion of an integral action in the controller to ensure zero steady-state error. An important aspect of this control approach is its ability to enhance robustness without needing information about external perturbations and parameter uncertainties. Moreover, the space vector modulation technique is designed to address the issue of current harmonic distortion by carefully selecting appropriate switching vectors. The appropriate selection for space voltage vectors for every sampling period maintains a consistent switching frequency. As a result, the SVM can enhance torque-rippled regulation and accomplish effective flux and torque control. The performance of the proposed control system is evaluated through a series of numerical simulations using MATLAB/Simulink. The simulation results are analyzed and compared to assess the effectiveness of the proposed control system in terms of tracking accuracy, disturbance rejection, robustness against parameter uncertainties, reduction of torque, and current ripples. To further validate the numerical simulation results, a hardware-in-the-loop (HIL) setup is established using the OPAL-RT platform. Furthermore, experimental validation on a PMSM utilizing the dSPACE DS1202 board is carried out, demonstrating the efficacy of the proposed control system. These findings validate the suggested control technique's robustness and efficiency.

An Adaptive Robust Control Method for Chaotic State of Permanent Magnet Synchronous Motor

In this paper, a chaotic control method based on adaptive robust controller is proposed to solve the chaos phenomenon of the permanent magnet synchronous motor system by mathematically analyzing the dynamic model of the permanent magnet synchronous motor system to eliminate or suppress chaos in the permanent magnet synchronous motors. This method also takes into account the parameter uncertainties (structural uncertainties) of the system and the external load torque interference (unstructured uncertainty).The former is compensated by adaptive control, and the latter by robust term. Feedforward elimination technology can integrate them together, and effectively reduce the influence of chaos on system performance and realize the high precision position tracking of the permanent magnet synchronous motor system. The Lyapunov method is used to prove the stability of the controller. The simulation results show that the method is better in robustness and control precision.

Two-stage Active Disturbance Rejection Control for Coupled Permanent Magnet Synchronous Motors System With Mismatched Disturbance

Two-stage Active Disturbance Rejection Control for Coupled Permanent Magnet Synchronous Motors System With Mismatched Disturbance

Adaptive Speed Regulation for Permanent Magnet Synchronous Motor Systems With Speed and Current Constraints

Adaptive Speed Regulation for Permanent Magnet Synchronous Motor Systems With Speed and Current Constraints

Sliding-mode Active Disturbance Rejection Permanent Magnet Synchronous Motor Control System

Aiming at the permanent magnet synchronous motor with external perturbations and internal uncertainties such as external load, rotational inertia and armature resistance changes, a servo control system based on sliding mode self-immunity controller is designed. By constructing a mathematical model of the servo system of the permanent magnet synchronous motor, considering the internal uncertainty caused by the change of the system parameters and the external random disturbance as the "total disturbance", and designing the transition process and the linear expansion state observer to observe and compensate for it, the system response can track the input signal quickly and without overshooting, and the sliding-mode state feedback makes the closed-loop servo system achieve fast and stable control, and the sliding-mode Active Disturbance Rejection control controller can be used to control the system. The sliding mode state feedback enables the closed-loop servo system to realize fast and stable control, and its consistent stability is proved by the Lyapunov method. Simulations show that this sliding- mode Active Disturbance Rejection control control strategy improves the system response speed and load carrying capability compared with the traditional sliding-mode control.

Super-Twisting Extended State Observer-Based Quasi-Proportional-Resonant Controller for Permanent Magnet Synchronous Motor Drive System

For the purpose of realizing permanent magnet synchronous motor (PMSM) systems with strong robustness and smooth speed, the quasi-proportional-resonant (QPR) controller is combined with super-twisting extended state observer (STESO) in this paper. Although traditional active disturbance rejection control scheme generally selects a sufficiently large bandwidth of linear extended state observer (LESO) to enhance the time-varying disturbance rejection capacity, the bandwidth of LESO is limited by system stiffness. To solve this tough issue, the STESO using generalized super-twisting technique is developed to optimize the stability and anti-disturbance capacity of motor drive system. In addition, the QPR controller is combined with the proposed STESO to suppress the motor speed fluctuation. Experimental results show that the proposed STESO-based QPR control algorithm has satisfactory characteristics.

Fault Diagnosis Method of Inter-Turn Short Circuit of Permanent Magnet Synchronous Motor Based on Third Harmonic

In order to realize the effective diagnosis of turn to turn short circuit fault of permanent magnet synchronous motor, a method of turn to turn short circuit fault diagnosis of permanent magnet synchronous motor based on third harmonic is proposed in this paper. Establish the system frequency oscillation analysis model of permanent magnet synchronous motor under the condition of turn to turn short circuit, collect the turn to turn harmonic of permanent magnet synchronous motor, then realize the third harmonic detection of permanent magnet synchronous motor under turn to turn short circuit fault, and detect the inertia of permanent magnet synchronous motor system. Based on the transient energy analysis and fault feature extraction, the turn to turn short circuit fault of permanent magnet synchronous motor is diagnosed. The test results show that this method has high reliability and good detection performance, and can improve the output stability and condition monitoring ability of permanent magnet synchronous motor.

Fractional order second-order sliding mode MRASO for SPMSM

To improve the accuracy of the sensorless control system for permanent magnet synchronous motors, this paper proposes the based on fractional order integral sliding mode theory in the model reference adaptive system observer. The purpose of this approach is to enhance the robustness of the system. Furthermore, this paper introduces the second-order sliding mode reaching law to suppress chattering phenomena and improve the control accuracy of the observer. Simulation results show that this strategy achieves excellent dynamic and static performance.

Fuzzy PID control of permanent magnet synchronous motor electric steering engine by improved beetle antennae search algorithm.

The accuracy of control in permanent magnet synchronous motor system significantly affects overall mechanical structure safety. To satisfy high-performance control for the position servo of the electric steering engine, this study selects a suitable vector control model for permanent magnet synchronous motor. Additionally, an enhanced beetle antennae search algorithm is designed and employed to optimize the fuzzy proportional-integral-derivative controller. The hybrid fuzzy proportional-integral-derivative controller is then implemented in the control model of the permanent magnet synchronous motor, resulting in the establishment of a novel control model for the electric steering engine driven by the permanent magnet synchronous motor. The test results showed that root-mean-square error of this control model was 0.03 mm and 0.02 mm respectively under the conditions of sinusoidal response, square wave response and step response, which was obviously shorter than all the selected control models. In addition, the standard deviation of the control model designed in this study accounted for less than 4% of root-mean-square error of electric steering engine position under the sinusoidal response condition, so the calculation stability was high. The research results show that the designed control model has a certain reference value for improving servo control performance of permanent magnet synchronous motor.

Current Control of Electrolytic Capacitor-Less Variable Frequency Drive System for Synchronous Reluctance Motors Based on Power Balancing and Compensation

Current Control of Electrolytic Capacitor-Less Variable Frequency Drive System for Synchronous Reluctance Motors Based on Power Balancing and Compensation