Search Results (167)

The force ripple of a permanent magnet synchronous linear motor (PMSLM) caused by multi-source disturbances in practical applications seriously restricts its high-precision motion control performance. The traditional single-mechanism model has difficulty fully characterizing the nonlinear disturbance factors, while the data-driven method has real-time limitations. Therefore, this paper proposes a hybrid modeling framework that integrates the physical mechanism and measured data and realizes the dynamic compensation of the force ripple by constructing a collaborative suppression algorithm. At the mechanistic level, based on electromagnetic field theory and the virtual displacement principle, an analytical model of the core disturbance terms such as the cogging effect and the end effect is established. At the data level, the acceleration sensor is used to collect the dynamic response signal in real time, and the data-driven ripple residual model is constructed by combining frequency domain analysis and parameter fitting. In order to verify the effectiveness of the algorithm, a hardware and software experimental platform including a multi-core processor, high-precision current loop controller, real-time data acquisition module, and motion control unit is built to realize the online calculation and closed-loop injection of the hybrid compensation current. Experiments show that the hybrid framework effectively compensates the unmodeled disturbance through the data model while maintaining the physical interpretability of the mechanistic model, which provides a new idea for motor performance optimization under complex working conditions. Full article

In integrated permanent magnet synchronous motors (IPMSMs) coupled with mechanical devices such as ball screws and reducers, complex nonlinear friction characteristics often arise, leading to asymmetrical distortions such as position “flat-top” and speed “ramp-up”. These phenomena significantly degrade the system’s positioning accuracy. To address this issue, this paper introduces a symmetry-inspired nonlinear predictive speed control approach based on the Stribeck piecewise linearized friction compensation and a generalized proportional integral (GPI) observer. The proposed method leverages the inherent symmetry in the Stribeck friction model to describe the nonlinear behavior, employing online piecewise linearization via the least squares method. A GPI observer was designed to estimate the lumped disturbance, including time-varying components in the speed dynamics, friction model deviations, and external loads. By incorporating these estimates, a nonlinear predictive controller was developed, employing a quadratic cost function to derive the optimal control law. The experimental results demonstrate that, compared to traditional integral NPC and PI controllers, the proposed method effectively restores system symmetry by eliminating the “flat-top” and “ramp-up” distortions while maintaining computational efficiency. Full article

The permanent magnet synchronous motor (PMSM) is a critical device that converts kinetic energy into mechanical energy. However, it faces issues such as nonlinearity, time-varying uncertainties, and external disturbances, which may degrade the system control performance. To address these challenges, this paper proposes a prescribed performance model-free adaptive fast integral terminal sliding mode control (PP-MFA-FITSMC) method. This approach replaces conventional techniques such as parameter identification, function approximation, and model reduction, offering advantages such as quantitative constraints on the PMSM tracking error, reduced chattering, strong disturbance rejection, and ease of engineering implementation. The method establishes a compact dynamic linearized data model for the PMSM system. Then, it uses a discrete small-gain extended state observer to estimate the composite disturbances in the PMSM online, effectively compensating for their adverse effects. Meanwhile, an improved prescribed performance function and error transformation function are designed, and a fast integral terminal sliding surface is constructed along with a discrete approach law that adaptively adjusts the switching gain. This ensures finite-time convergence of the control system, forming a model-free, low-complexity, high-performance control approach. Finally, response surface methodology is applied to conduct a sensitivity analysis of the controller’s critical parameters. Finally, controller parameter sensitivity experiments and comparative experiments were conducted. In the parameter sensitivity experiments, the response surface methodology was employed to design the tests, revealing the impact of individual parameters and parameter interactions on system performance. In the comparative experiments, under various operating conditions, the proposed strategy consistently constrained the tracking error within ±0.0028 rad, demonstrating superior robustness compared to other control methods. Full article

This study addresses the challenge of ride height control in linear motor-based active suspension systems by proposing a control strategy based on linear active disturbance rejection control (LADRC). The effectiveness of the proposed approach is experimentally validated using a high-precision test platform built on the NI cRIO-9014 real-time controller. The platform integrates a permanent magnet synchronous linear motor, a motor driver, acceleration sensors, and a vibration control system to realize closed-loop control of vehicle body height. Experimental results demonstrate that, compared with conventional PID control, LADRC achieves superior performance in height regulation accuracy, dynamic responsiveness, vertical acceleration suppression, and steady-state stability. In step response experiments, LADRC reduces the regulation time by 53.8% (from 1.3 s to 0.6 s) and lowers the steady-state error from 0.502 mm to 0.05 mm. In sinusoidal trajectory tracking tests, the LADRC approach reduces peak and RMS tracking errors by 81.5% and 80.3%, respectively. Moreover, under random road excitation, LADRC effectively attenuates high-frequency body vibrations, with reductions of 29.58% in peak vertical acceleration and 12.23% in RMS acceleration. Full article

The application fields of high-speed submersible permanent magnet synchronous motors (PMSM) are constantly expanding. Especially in high-risk and complex environments such as oil exploration, offshore oil exploitation, and deep well operation, the reliability, stability, and efficiency of motor drive systems are more and more prominent. The submersible motor is greatly affected by load disturbance, pressure change, and external oil flow, and the traditional method may not perform well in complex disturbance problems. Therefore, a three-order adaptive nonlinear extended state observer is proposed to collect the input and output information of the system in real time, and estimate the motor speed, position, and total disturbance. A linear feedback control law is designed to eliminate the disturbance. The superiority of the proposed algorithm under complex operating conditions is verified by the Simulink model and experiments, which provide a theoretical basis for the control of submersible motors. Full article

Positioning servo systems utilizing permanent magnet synchronous linear motors (PMSLMs) are conventionally governed by cascaded P-PI controllers, which, despite their simplicity and robustness, suffer from limited tracking and anti-disturbance performance due to their single-degree-of-freedom (1-DOF) structure. This paper introduces a novel two-degree-of-freedom (2-DOF) control algorithm that integrates explicit model predictive control (EMPC) with a differential-compensated extended state observer (DCESO). The EMPC framework leverages position and velocity as state variables, eliminating the need for integral terms and thereby enhancing dynamic response. By employing an offline optimization approach, a control law is explicitly formulated to handle system constraints while minimizing online computational overhead. Additionally, a velocity feedforward term derived from the MPC framework is incorporated to further reduce tracking errors. To bolster disturbance rejection, the proposed DCESO introduces a differential compensator that mitigates the low-pass effects inherent in traditional ESOs, thereby improving estimation dynamics. Experimental results demonstrate that the proposed method significantly outperforms the conventional P-PI controller, increasing the position loop bandwidth from 147 Hz to 208 Hz and markedly enhancing anti-disturbance performance. The algorithm’s low online computational demand makes it highly suitable for industrial applications. Full article

To optimize the modulated vibration generated by the integer-slot interior permanent magnet synchronous motor (IPMSM), a stepwise segmented skewed pole method was proposed, using an 8-pole 48-slot IPMSM as an example. First, the vibration characteristics of the motor were studied, and the theoretical mechanisms of the magnetic field modulation effect and radial force modulation effect were explained. The study showed that high-order radial forces can excite larger low-order vibrations under the influence of radial force modulation. Then, in response to the axial spacing in the linear skewed pole structure when canceling the 48th-order radial force, a stepwise skewed pole structure was proposed. The suppression mechanism of this skewed pole structure on the motor’s modulated vibration was analyzed, and the optimization effect of different segment numbers on the motor’s vibration acceleration at $12f_e$ was discussed. Finally, models for the motor’s magnetic field, structural field, and acoustic field before and after skewing were established, and simulations were conducted to compare the magnitudes of the radial forces at each order and their vibration noise performance. The results showed that after stepwise skewed pole optimization, the radial force that excites the modulated vibration was reduced by 68%, the maximum vibration acceleration on the casing surface was reduced by 84%, and the overall noise was reduced by 7.491 dB, effectively suppressing electromagnetic vibration noise. Full article

This paper introduces an enhanced approach for optimizing the flux-weakening performance of a non-salient permanent magnet synchronous machine (PMSM), by incorporating the maximum torque per voltage (MTPV) region into a conventional voltage magnitude feedback control strategy. The MTPV control strategy is initially optimized for steady-state performance by incorporating the effect of resistance, which plays a crucial role in small power motors. To maintain stability and good dynamics in the flux-weakening region, a current command feedback MTPV controller is utilized, as opposed to a voltage command feedback approach. Additionally, to address stability concerns in the MTPV region, a feedback type proportional-integral (PI) MTPV controller is designed and implemented. The stability in both the over-modulation and various flux-weakening regions is further enhanced using a voltage vector modifier (VVM). Therefore, the proposed feedback-based flux-weakening control enhances system steady-state performance, dynamic response, and stability across both linear and over modulation regions under various flux-weakening conditions, making it suitable for general-purpose applications. The effectiveness of the proposed method is validated through experimental results. Full article

In the control system of a permanent magnet synchronous motor (PMSM) driven by an inverter, the conventional space vector pulse width modulation (SVPWM) strategy introduces high-frequency current harmonics at the switching frequency and its multiples, resulting in significant high-frequency vibrations during motor operation. To address this issue, a dual-random SVPWM strategy is proposed in this paper, which combines a random switching frequency and random zero-vector to spread the spectrum of high-frequency current harmonics. This approach effectively disperses the high-frequency harmonics concentrated at the switching frequency and its multiples, thereby significantly reducing the motor’s high-frequency vibrations. Furthermore, to overcome the limitations of the traditional linear congruential method in generating random numbers, the Beta distribution is introduced and improved in this study. The particle swarm optimization (PSO) algorithm is employed to optimize the shape parameters of the Beta distribution, to achieve the optimal random number performance. Finally, experimental validation is conducted under various speed conditions. Compared with the conventional SVPWM strategy, the results demonstrate that the proposed dual-random SVPWM strategy exhibits superior suppression of both high-frequency harmonics and high-frequency vibrations. Full article

Conventional active vehicle height control systems predominantly employ hydraulic or pneumatic suspension mechanisms. Although these established approaches have achieved widespread adoption in automotive applications, they remain fundamentally constrained by three critical drawbacks: (1) inadequate dynamic response characteristics, (2) high energy consumption, and (3) inherent mechanical complexity. The ongoing electrification revolution in vehicle technologies has spurred significant research interest in linear electromagnetic suspension systems. Nevertheless, their practical implementation encounters dual technical barriers: (a) complex multi-phase motor configurations requiring precise coordination, and (b) substantial thrust ripple generation under dynamic operating conditions. To address these critical limitations, our research proposes a novel motor structure, known as the flat rectangular slot structure, which offers advantages such as simple installation and high thrust with low current. Additionally, we have designed a double-vector control strategy for the motor control section, which modifies the finite-set model predictive control and enhances the accuracy of the model’s calculations. By integrating the vehicle model, we have developed a multi-layer hierarchical control strategy for the vehicle height controller. In the first layer, a PI controller is used to convert the target height into current, which is then input into the value function. In the second layer, we improve the control strategy for the linear motor by optimizing the finite-set model predictive control through the double-vector control. Through multi-step predictive calculations, we determine the optimal sector, enabling the motor to receive the corresponding control force. In the third layer, the motor thrust is input into the vehicle model to achieve closed-loop control of the vehicle body. Finally, we conduct simulation verification of the proposed control strategy. The simulation results indicate that the double-vector control significantly reduces the fluctuation in the sprung mass displacement by approximately 70% compared to single-vector control, the response speed is increased by approximately 20%, and the thrust required to achieve the target vehicle height is reduced by 5.7%. Therefore, the proposed double-vector control strategy can significantly enhance the stability of the automotive electronic control suspension, opening up new research avenues for the study of suspension stability control and energy saving in vehicles. Full article

This article investigates the adaptive output regulation problem of a permanent magnet synchronous motor (PMSM) speed servo system with unknown time-varying exosystems and aims to achieve multiple objectives including speed tracking, disturbance rejection, and robustness simultaneously. Existing linear or nonlinear internal model designs are not applicable to the output regulation problem under the time-varying situation. Hence, we first construct a time-varying internal model to transform this control problem into a robust stabilization problem for a time-varying augmented system, and then design a stabilization controller integrating robust control and adaptive control techniques to stabilize this system. Finally, the validity of the proposed approach is verified through simulations and experiments. It is worth mentioning that our approach can achieve high-precision speed tracking of PMSM under parameter uncertainties and load torque disturbance with unknown time-varying frequencies. Full article

Permanent magnetic linear synchronous motors (PMLSMs) have emerged as a promising solution for low-carbon urban rail transit systems due to their superior energy efficiency. However, their widespread adoption is hindered by significant challenges in achieving high-precision cooperative control and fault-tolerant operation across multi-PMLSMs. To address these issues, this paper proposed a novel composite observer-based adaptive fault-tolerant cooperative control framework, which enables reliable speed synchronization in multi-PMLSM urban rail traction systems through three key innovations. Initially, the stuck fault of the actuator is modeled based on the PMLSM dynamic model, and a composite observer is proposed to estimate lumped disturbances and actuator faults simultaneously, enhancing the system’s robustness against uncertainties and faults. A novel sliding mode control scheme with adaptive parameters is subsequently developed to compensate for disturbances and improve tracking accuracy. Furthermore, two event-triggered schemes are devised to reduce the communication burden, ensuring efficient data transmission without compromising control performance. The proposed method ensures high-precision synchronization and fault tolerance under actuator stuck faults, bias faults, and external disturbances, as validated by simulation results. By improving energy efficiency and reducing communication load, the proposed method contributes to the development of low-carbon urban rail transit systems, aligning with global sustainability goals. Full article

To address the mismatch between materials and operational speed in mine scraper conveyors under time-varying load conditions, this paper proposes a methodology for the regulation of speed based on the quantity of coal transported by the scraper conveyor. Furthermore, a vector control strategy for permanent magnet synchronous motors (PMSMs) is presented, underpinned by a global fast terminal sliding mode controller. Firstly, a calculation model for the real-time coal volume of the scraper conveyor was developed based on the double-end oblique cutting coal mining technology in fully mechanized mining operations. This model takes into account the operational condition of the shearer and the scraper conveyor. In addition, a graded speed regulation control method was introduced. Secondly, a global fast terminal controller was developed by integrating the features of linear and terminal sliding mode surfaces. An enhanced sliding mode vector control strategy for the permanent magnet drive motor of the scraper conveyor was subsequently proposed. Finally, a simulation and ground test were subsequently performed on the PMSM experimental bench and SGZ2×1200 scraper conveyor to validate the proposed control strategy. The results indicated that the proposed control strategy not only diminished the overshoot of the rotational speed and decreased the dynamic response time but also improved the anti-interference capabilities of the PMSM relative to the original PI control. Moreover, the ground test validated the feasibility of the suggested speed regulation method. Full article

Permanent magnet synchronous motors (PMSMs) are widely used in industrial automation and electric vehicles due to their high efficiency and excellent dynamic performance. However, controlling PMSMs presents challenges such as parameter variations and system nonlinearities. This paper proposes a twin delayed deep deterministic policy gradient (TD3)-based energy-saving optimization control method for PMSM drive systems. The TD3 algorithm uses double networks, target policy smoothing regularization, and delayed actor network updates to improve training stability and accuracy. Simulation experiments under two operating conditions show that the TD3 algorithm outperforms traditional proportional–integral (PI) controllers and linear active disturbance rejection control (LADRC) controllers in terms of reference trajectory tracking, q-axis current regulation, and speed tracking error minimization. The results demonstrate the TD3 algorithm’s effectiveness in enhancing motor efficiency and system robustness, offering a novel approach to PMSM drive system control through deep reinforcement learning. Full article

This paper presents a cost-efficient estimation method, the filtering observer (FOBS), which provides a smooth estimation through prior estimation, enhancing the field-oriented control (FOC) performance of motion control systems by estimating the angular rotor position, angular rotor velocity, and disturbance torque of permanent magnet synchronous motors (PMSMs). The cost-effective FOBS demonstrates characteristics akin to optimal estimating methods and employs arbitrary pole placement, facilitating more straightforward adjustment of the FOBS gain. The non-linear characteristics of low-resolution and low-cost encoders, the computation of angular rotor velocity using traditional techniques, and disturbances over broad frequency ranges in the servo drive system impair the efficacy of the motion control system. As a cost-effective solution, the FOBS minimizes the deficiencies of the low-cost encoder, reduces oscillations and measurement delays in the speed feedback signal, and provides smooth estimation of disturbance torque. Based on the results from experiments, the FOBS was compared against traditional approaches and the performance of the motion control system was examined. Also, the performance of the motion control system was investigated. The results indicate that these enhancements were achieved with low processing power and an easily implementable estimate technique suitable for low-cost industrial systems. Full article