PMSM Speed Research Articles

Enhanced Sliding Mode Control for PMSM Speed Drive Systems Using a Novel Adaptive Sliding Mode Reaching Law Based on Exponential Function

Enhanced Sliding Mode Control for PMSM Speed Drive Systems Using a Novel Adaptive Sliding Mode Reaching Law Based on Exponential Function

Double-Layer Fast Terminal Sliding Mode Predictive Control for PMSM Speed Regulation

Double-Layer Fast Terminal Sliding Mode Predictive Control for PMSM Speed Regulation

Reliability Enhancement of a Double-Switch Single-Ended Primary Inductance–Buck Regulator in a Wind-Driven Permanent Magnet Synchronous Generator Using a Double-Band Hysteresis Current Controller

The wind power exchange system (WECS) covered in this paper consists of a voltage source inverter (VSI), a DSSB regulator, and an uncontrolled rectifier. An AC grid or a heavy inductive or resistive load (RL) can be supplied by this system. The DSSB is a recently developed DC-DC regulator consisting of an improved single-ended primary inductance regulator (SEPIC) followed by a buck regulator. It has a peak efficiency of 95–98% and a voltage gain of (D (1+D)/(1−D). where D is the regulator transistor’s on-to-off switching ratio. The proposed regulator improves the voltage stability and MPPT strategy (optimal or maximum power-point tracking). The combination of the DSSB and the proposed regulator improves the efficiency of the system and increases the power output of the wind turbine by reducing the harmonics of the system voltages and current. This method also reduces the influence of air density as well as wind speed variations on the MPPT strategy. Classical proportional–integral (PI) controllers are used in conjunction with a vector-controlled voltage source inverter, which adheres to the suggested DSSB regulator, to control the PMSM speed and d-q axis currents and to correct for current error. In addition to the vector-controlled voltage source inverter (which follows the recommended DSSB regulator), classical proportional–integral controllers are used to regulate the PMSM speed and d-q axis currents, and to correct current errors. In addition, a model Predictive Controller (PPC) is used with the pitch angle control (PAC) of WECS. This is done to show how well the proposed WECS (WECS with DSSB regulator) enhances voltage stability. A software-based simulation (MATLAB/Simulink) evaluates the results for ideal and unoptimized parameters of the WT and WECS under a variety of conditions. The results of the simulation show an increase in MPPT precision and output power performance.

Robust Predictive Cascaded Speed and Current Control for PMSM Drives Considering Parameter Variations

Robust Predictive Cascaded Speed and Current Control for PMSM Drives Considering Parameter Variations

Hierarchical Nonsingular Terminal Sliding Mode Control With Finite-Time Disturbance Observer for PMSM Speed Regulation System

Hierarchical Nonsingular Terminal Sliding Mode Control With Finite-Time Disturbance Observer for PMSM Speed Regulation System

Iterative Learning Observer-Based Composite SOSM Control for PMSM Speed Regulation Problem With Mismatched Disturbances

Iterative Learning Observer-Based Composite SOSM Control for PMSM Speed Regulation Problem With Mismatched Disturbances

Permanent magnet synchronous motor NFTSM control based on novel exponential convergence law and ESO

Abstract To solve the problems of slow convergence and serious system chatter in PMSM speed regulation of traditional exponential approach law sliding mode control (SMC), a PMSM fast terminal slip mode (NFTSM) beat free predictive current control (DPCC) strategy based on improved exponential control rate and extended sliding mode observer (ESO) is proposed. The non-singular fast terminal slip-mode controller based on improved exponential control rate and ESO is used in the speed loop. A new exponential approach law is proposed. The stability of the system is proved by using the Lyapunov function. The robustness of the speed controller is improved while reducing the vibration. DPCC control strategy based on ESO is adopted for the current loop to compensate comprehensive disturbance of the current loop. The experiment results show that the control strategy has good speed tracking performance and anti-jamming performance.

Fractional-Order PID Control of Permanent Magnet Synchronous Motors Based on Based on Improved Squirrel Algorithm

An adaptive differential squirrel algorithm fractional order PID controller is proposed to address the problems of instability and poor accuracy of Permanent Magnet Synchronous Motor PID control systems. In order to improve the global optimisation of the squirrel search algorithm, the crossover operation of the difference algorithm was combined, adaptive predation probability factor, dynamic crossover probability and Gaussian distribution perturbation operation are added to the squirrel search algorithm to improve its exploration and exploitation capability. In the comparative experiment of PMSM speed control, ADESA fractional-order PID was contrasted with conventional PID and other intelligent optimization algorithms. The results indicate that the PMSM control utilizing fractional-order PID through ADESA demonstrated minimal overshoot, the fastest response time, and superior anti-disturbance capabilities compared to PID and other intelligent optimization algorithms. This significantly enhanced the control performance of the permanent magnet synchronous motor.

A Variable Structure ADRC for Enhanced Disturbance Rejection and Improved Noise Suppression of PMSM Speed System

A Variable Structure ADRC for Enhanced Disturbance Rejection and Improved Noise Suppression of PMSM Speed System

Fixed-time Generalized Active Disturbance Rejection with Quasi-resonant control for PMSM Speed Disturbances Suppression

Fixed-time Generalized Active Disturbance Rejection with Quasi-resonant control for PMSM Speed Disturbances Suppression

Different Model-Based ADRCs Satisfying Performance Independent Control for PMSM Speed Servo System

Different Model-Based ADRCs Satisfying Performance Independent Control for PMSM Speed Servo System

Optimization of an ANN-based speed and position estimator for an FOC-controlled PMSM using genetic algorithm

Optimization of an ANN-based speed and position estimator for an FOC-controlled PMSM using genetic algorithm

Improved cascaded model-free predictive speed control for PMSM speed ripple minimization based on ultra-local model

This paper presents an improved cascaded model-free predictive speed and current control with the periodic and aperiodic disturbances suppression to achieve a smooth speed. The cascaded structure has an external speed loop and an internal current loop, both implemented with model-free predictive control to enhance the robustness of the controller. The current loop is designed based on the finite control set model-free predictive current control (FCS-MFPCC) strategy with an ultra-local model to regulate the stator currents, and the speed loop uses the proposed continuous control set model-free predictive speed control (CCS-MFPSC) to make full use of the excellent dynamic performance of the current-loop controller. To suppress the periodic disturbance that exists in the PMSM system, an improved parallel quasi-resonant controller (QRC) with an error limitation is embedded into the CCS-MFPSC, which can generate the compensated current. Based on the stability condition, the stability of the proposed MFPSC-QRC strategy is directly analyzed in the z-domain. Finally, the effectiveness and feasibility of the proposed cascaded model-free predictive speed and current strategy are validated on a PMSM test platform.

A Novel Technique to Correct the Unwanted Zero Position Signal of Faulty Encoder for Accurate Speed and Position Estimation of PMSM Drive

A Novel Technique to Correct the Unwanted Zero Position Signal of Faulty Encoder for Accurate Speed and Position Estimation of PMSM Drive

Research on PMSM Speed Performance Based on Fractional Order Adaptive Fuzzy Backstepping Control

A permanent magnet synchronous motor (PMSM) is a nonlinear, strongly coupled, controlled object with time-varying, fractional-order characteristics. It is difficult to achieve the ideal control effect by using the traditional control method when motor parameter changes and load perturbations occur during the operation of the PMSM, so a fractional-order adaptive fuzzy backstepping control method is proposed to improve the system’s fast response and anti-jamming ability in the case of sudden changes in rotational speed, load perturbations and other conditions. Initially, the fractional order theory is introduced, backstepping control is utilized to decompose the system into multiple subsystems, and a fractional order-based Lyapunov function is designed for each subsystem to ensure the system’s stability. Suitable control laws, as well as parameter adaptive laws, are derived through rigorous mathematical derivation. Finally, a fractional order adaptive fuzzy backstepping controller (FOAB-FPID) is designed by combining the advantages of fuzzy control. Then a mechanical simulation model of the PMSM is established to verify the validity of the designed controller, followed by three sets of comparative experiments: PID, fuzzy PID (F-PID), and integer-order adaptive fuzzy backstepping (IOAB-FPID), which are selected to simulate the PMSM under the control of the four controllers. Finally, it is validated on the constructed PMSM experimental platform. Simulation and experimental results show that FOAB-FPID can adaptively adjust system parameters during sudden speed changes, achieve real-time speed tracking, and maintain speed stability under load perturbations and internal parameter uptake. Compared with the three control strategies, reached PMSM system has better acceleration, fast response performance, and better anti-disturbance ability, which proves the rationality and effectiveness of the FOAB-FPID control method.

Optimal Fuzzy PI Approach for PMSM Speed Control Using Modified Jaya Optimization Technique

Optimal Fuzzy PI Approach for PMSM Speed Control Using Modified Jaya Optimization Technique

Comparative Performance Evaluation of Swarm Intelligence-Based FOPID Controllers for PMSM Speed Control

Comparative Performance Evaluation of Swarm Intelligence-Based FOPID Controllers for PMSM Speed Control

Rotor Speed and Position Estimation Analysis of Interior PMSM Machines in Low and Medium-High Speed Regions Adopting an Improved Flux Observer for Electric Vehicle Applications

This paper proposes a nonlinear flux linkage observer for the PMSM speed controls without motion sensors, introducing the deviation among the real stator flux linkage and an estimated stator flux linkage to suppress feedback and integral flux drift. In the position detection of an interior PMSM without a speed sensor, the traditional back EMF integration method uses a pure integrator, or LPF, to estimate the stator flux. Its inherent defects inevitably lead to inaccurate flux estimation, which directly affects the estimation of the motor mover position, resulting in the decline in motor control operation and the distortion of phase current. This paper uses an improved integrator with adaptive compensation. The projected value of the stator flux linkage has been derived from the estimated value of the rotor permanent magnetic flux linkage position angle and the algebraic model (m-model) of the stator flux linkage, along with a synchronous coordinate system. The IPMSM stator coil flux linkage obtained from the stator coil current and integral voltage models in the static coordinate system is compared to form a feedback closed-loop to suppress the integral drift, and using the cross-product approach of the actual and estimated flux linkage yields the projected value of the IPMSM rotor speed and position through a PLL. Compared with the existing motion-sensorless observers, the methodology proposed in this article is simple and exhibits better dynamic and static estimation performance. Extensive and comprehensive MATLAB computer simulation and experimental findings validate the proposed motion-sensorless control mechanism.

Full-order adaptive sliding mode control with extended state observer for high-speed PMSM speed regulation

In order to achieve speed control of high-speed permanent magnet synchronous motor with high precision, the sliding mode control (SMC) is usually adopted. However, the inherent chattering phenomenon affects the speed control performance. In order to solve this problem, a composite speed regulator is proposed in this paper, which is made up of two parts: the adaptive full-order SMC and extended state observer (ESO). Switching gain adaption law is proposed for minimizing chattering as much as possible while ensuring the robustness of sliding mode control. The total disturbance is estimated by the ESO and through feedforward, thus improving the system anti-disturbance ability. Finally, the effectiveness of the proposed speed regulator has been validated in the test bench.

Modified ADRC Design of Permanent Magnet Synchronous Motor Based on Improved Memetic Algorithm

In this paper, a novel modified auto disturbance rejection control (ADRC) design of a permanent magnet synchronous motor based on the improved memetic algorithm (IMA) is proposed. Firstly, there is an obvious system ripple caused by the defect that the optimal control function used in traditional ADRC cannot be differentiable and smooth at the segment point; aiming at weakening the system ripple effectively, the proposed method constructs a novel differentiable and smooth optimal control function to modify the ADRC design. Furthermore, aiming at improving the integration parameters optimization effect effectively, a novel improved memetic algorithm is proposed for obtaining the optimal parameters of ADRC. Specifically, an IMA with high-quality balance based on an adaptive nonlinear decreasing strategy for the convergence factor, Gaussian mutation mechanism, improved learning mechanism with the high-quality balance between competitive and opposition-based learning (OBL) and an elite set maintenance mechanism based on fusion distance is proposed so that these strategies can improve the optimization precision by a large margin. Finally, the experiment results of the PMSM speed control practical cases show that the ADRC based on IMA has an apparent better optimization effect than that of fuzzy PI, traditional ADRC based on the genetic algorithm and an improved ADRC based on improved moth-flame optimization.