Control Of Permanent Magnet Synchronous Motor Research Articles

An Improved Model Predictive Torque Control for PMSM Drives Based on Discrete Space Vector Modulation

In this paper, an improved model predictive torque control (MPTC) method based on discrete space vector modulation (DSVM) is proposed for permanent magnet synchronous motor (PMSM) drives. Aiming at solving the two problems of large torque ripples and high computational complexity in conventional MPTC, the proposed method adopts a second optimization and a new simplified search strategy. The key idea of second optimization is to make the output voltage vector closer to the actual optimal solution. In this case, a more suitable voltage vector is applied in each sampling period. The simplified search strategy reduces the calculation time by cutting down the number of candidate voltage vectors without affecting drives performance. Compared to the conventional MPTC without DSVM and with DSVM, the proposed method can produce superior steady-state performance and lower computational complexity. Simulation and experimental results are presented to validate the effectiveness and feasibility of the proposed method.

Effective Multivector-Operated Predictive Current Control of PMSM Drive With Reduced Torque and Flux Ripple

Model predictive current control (MPCC) is a frequently used method for the control of permanent magnet synchronous motor (PMSM). It has faster execution on modern digital platform than the previous generation micro-controllers. Conventional MPCC fails to provide satisfactory steady-state performance as a single voltage vector (VV) is applied during every sampling interval. This article proposes two novel multi-vector operated MPCC methods for reducing torque and flux ripples, as well as the computational burden. The first proposed method uses one active and one null VV; whereas, the second method uses two active and one null VV to further improve the steady-state performance. Proposed methods determine required change in stator-flux (CSF) to reduce/eliminate error in statorcurrent during every sample and VVs nearer to CSF vector are chosen as optimal VVs. The durations of optimal VVs are calculated using the components of CSF along optimal VVs. CSF, obtained using calculated durations of optimal VVs, significantly reduces torque and flux ripples. The proposed methods are effective and less complex compared to other multi-vector operated methods. The proposed methods are compared with existing two-VV and three-VV based MPCC methods and their effectiveness is experimentally verified for decreased torque and stator-flux ripple in addition to a small rise in switching frequency.

A Novel Active Disturbance Rejection Control of PMSM Based on Deep Reinforcement Learning for More Electric Aircraft

In this article, a novel active disturbance rejection control (ADRC) based on deep reinforcement learning (DRL) is proposed to improve the performance of permanent magnet synchronous motor (PMSM) for more electric aircraft (MEA). MEA motors have the requirements of safety and stability so that a new ADRC method is put forward based on the limitation of nonlinear error attenuation function of traditional ADRC. The flux weakening control model of PMSM is firstly established. Then the ADRC model is built and applied to the speed loop of the control system. In order to reduce the number of control parameters and the jitter of the control law, deep neural network is employed to replace the traditional control law. Markov decision process is integrated into the novel ADRC to establish DRL model. A method based on twin delayed deep deterministic (TD3) policy gradient algorithm is proposed to train the neural network and optimize the DRL model. Model predictive control and traditional ADRC are used as comparison algorithms. Simulation and experiments show the effectiveness and superiority of the proposed method.

A Fast Sliding Mode Speed Controller for PMSM Based on New Compound Reaching Law With Improved Sliding Mode Observer

To reduce the convergence time and improve the anti-disturbance capability of the permanent magnet synchronous motor (PMSM) drivers, a fast sliding mode speed controller based on a new compound reaching law (NCRL) and disturbance observer compensation technique is proposed. Firstly, to solve the conflict between fast convergence rate and chattering reduction in the existing solutions, the NCRL is proposed by introducing the exponential function and the power term piecewise function. The convergence of NCRL is proved and the reaching time is certified to be independent of the system’s initial state. The proposed NCRL can effectively reduce the reaching time, and smooth the output signal while maintaining the high tracking performance of the controller under different conditions. However, external load disturbances may degrade the performance of the proposed NCRL-based speed controller. The proposed controller is then combined with an improved sliding mode observer (ISMO), named the NCRL+ISMO method, to improve the estimation accuracy of the lumped disturbance and the robustness of the system. The stability of the proposed method is analyzed by the Lyapunov function. Experimental results show that the proposed method can reduce speed fluctuation and convergence time, and enhance anti-disturbance capability.

Duty-Cycle Correction-Based Model Predictive Current Control for PMSM Drives Fed by a Three-Level Inverter With Low Switching Frequency

In this paper, a duty-cycle correction-based model predictive current control (DC-MPCC) is proposed for permanent magnet synchronous motor (PMSM) supplied by a neutral-point clamped three-level voltage source inverter (NPC-3LVSI). Unlike the conventional MPCC, which evaluates the impact of basic voltage vectors on the concerned state variables, the proposed DC-MPCC modifies the output voltage levels with optimized duty-cycle corrections. Firstly, the last three-phase voltage levels are assumed to be kept during the next control period. Then, the current tracking error and neutral-point potential are predicted. After that, the voltage levels are modified with zero, one, or two state changes, which formulate seven candidate solutions. Subsequently, the duty-cycle corrections of the modified voltage levels are computed based on the principle of minimizing current tracking error and neutral-point voltage drift. Finally, the optimal switch sequence is generated by evaluating and sorting a cost function with a penalty on switch actions. The proposed DC-MPCC features variable switching instants, relatively lower sampling frequency, and satisfactory performance under low switching frequency. Experimental tests carried out on a NPC-3LVSI fed PMSM drive, with 100 Hz fundamental frequency and 400 Hz switching frequency, accompanied by a video demonstration, validate the effectiveness of the proposed method.

A Less-Invasive Method for Accurately Diagnosing Demagnetization Fault in PMSM Using Rotor Partition

This paper presents a less-invasive method for accurately diagnosing of demagnetization fault in permanent magnet synchronous motors (PMSM) using rotor partition. The rotor PMs are partitioned according to certain rules. The PMs condition of each partition is sequentially diagnosed through the signals measured by two additional toroidal yoke coils, thus the conditions of all rotor PMs are diagnosed. Firstly, the working mechanism of the search coil is analyzed, and the partitioned model of SC residual voltage is also presented. Secondly, the relationship between residual voltage signatures of SC and different demagnetization fault modes is studied by the established model. From the analysis, a demagnetization fault location method is proposed. The simulation and experiment results validate the correctness of the proposed method and indicate the proposed fault location method applies to the online diagnosis of both local and uniform demagnetization faults. In addition, the location of demagnetized PMs can be detected under any demagnetization fault condition and is not affected by other fault signals. Lastly, a comparison with existing methods based on search coil is performed and indicates the proposed method can locate faults more quickly and accurately than that of existing methods when the PM is demagnetized by 10%, and it is less invasive, especially has advantages in locating demagnetization PMs in PMSM with numerous pole-pairs. This article provides a new idea for demagnetization fault location of PMSM, as well as provides a significant reference for a motor maintenance schedule and fault-tolerant control of PMSM.

Optimal Tuning of Fractional Order Sliding Mode Controller for PMSM Speed Using Neural Network with Reinforcement Learning

An improved fractional-order sliding mode control (FOSMC) for PMSM is presented in this study to set the unavoidable parameters and to improve permanent magnet synchronous motors (PMSMs) drive performance, such as current and speed tracking accuracy. To determine the optimal parameters of the FOSMC for control speed in a PMSM drive, a neural network algorithm with reinforcement learning (RLNNA) is proposed. The FOSMC parameters are set by the ANN algorithm and then adapted through reinforcement learning to enhance the results. The proposed controller using RLNNA based on fractional-order sliding mode control (RLNNA-FOSMC) can drive the motor speed to achieve the referred value in a finite period of time, leading to faster convergence and improved tracking accuracy. For a fair comparison and evaluation, the proposed RLNNA-FOSMC is compared with conventional FOSMC by applying the integral of time multiplied absolute error as an objective function. The most commonly used objective functions in the literature were also compared, including the integral time multiplied square error, integral square error, and integral absolute error. To validate the performance of the RLNNA-FOSMC speed controller, different scenarios with different speeds steps were carried out. The computational results are promising and demonstrate the effectiveness of the proposed controller. Overall, the proposed RLNNA-FOSMC controller for the PMSM speed control system performed better than conventional FOSMC in numerical simulations.

Sliding Mode Active Disturbance Rejection Control of Permanent Magnet Synchronous Motor Based on Improved Genetic Algorithm

Sliding mode control has been widely used to control permanent magnet synchronous motors (PMSM). However, the parameters of the sliding mode controller are difficult to be tuned, which makes the control performance of PMSM hard to be improved. A nonlinear sliding mode control method that integrated a nonlinear reaching law (NRLSMC) and extended state observer (ESO) is proposed in this paper, whose parameters are tuned by an improved genetic algorithm (IGA). The control performance of the nonlinear reaching law in the nonlinear sliding mode controller is analyzed, whose stability is verified based on the Lyapunov theorem. An extended state observer is integrated into the above controller to further improve the anti-interference capability, and compensate for the observed external disturbance of the system into the speed controller in sliding mode. The optimal parameters of the above sliding mode control are tuned by IGA combined with the system speed loop model. The performance of the proposed controller is numerically simulated in MATLAB/Simulink and verified in a control system rapid control prototype (RCP) experimental platform built based on dSPACE 1202. Numerical simulation and experimental results show that the proposed controller can make the PMSM control system with the advantages of no overshoot, fast response, and strong robustness.

PMSM non-singular fast terminal sliding mode control with disturbance compensation

A non-singular fast terminal sliding mode control (NFTSMC) strategy is proposed for a permanent magnet synchronous motor control system susceptible to load disturbance. First, an NFTSM surface with fast convergence during the finite time is designed to circumvent the singular point in the TSM surface. Then, a novel reaching law (NRL) is presented to resolve the inconsistency between the system chattering and convergence rate in the traditional reaching law (TRL). Meanwhile, a non-singular fast terminal sliding mode disturbance observer (NFTSMDO) is developed to estimate the disturbance value and compensate the speed controller, further enhancing the system's anti-disturbance performance. Finally, the experiments are conducted jointly with MATLAB/Simulink and the dSPACE platform; accordingly, the experimental results indicate that when the system adds load disturbances, the PI overshoot is 38.7 rpm and the adjustment time is the longest. In addition, when the NFTSMC-TRL and NFTSMC-NRL-NFTSMDO overshoots are 37.4 and 22.1 rpm, respectively, the adjustment time is the shortest and the overall anti-disturbance is the best. Compared to SMDO, NFTSMDO improves the observer's response speed and estimation accuracy while suppressing sliding-mode chattering. It can be inferred that the control strategy proposed in this study can effectively suppress the chattering of the sliding mode control system and improve the anti-disturbance ability of the control system.

Research on internal model control and hybrid modulation strategy of a MW-level direct-drive PMSM for traction drives in electric locomotive

Aiming at the problem of motor control performance degradation caused by the cross-coupling and low switching frequency condition in the high-power direct-drive permanent magnet synchronous motor (PMSM) control system, a robust current control of PMSM based on internal model control (IMC) and hybrid pulse width modulation (PWM) is proposed and applied to the control of a MW-level direct-drive PMSM in electric locomotive traction system. Firstly, combined with the characteristics of the low switching frequency of the electric locomotive inverter, a hybrid PWM strategy is adopted. Secondly, the IMC of PMSM is designed, and the IMC is adopted to solve the problems of more control parameters and cross-coupling of direct-drive PMSM in the d-q axis under low switching frequency, which improves the robustness of the whole locomotive system. Finally, the experiments have been carried out on a 1.2 MW direct-drive PMSM for traction system in electric locomotive, the correctness and effectiveness of IMC and hybrid PWM strategy are verified.

Sensorless PMSM control system based on luenberger observer

At present, sensorless becomes a research hit for its lower cost and smaller size, among the present sensorless methods, Luenberger Observer has outstanding advantages for its dynamic performance, parameter robustness and high system stability. In this paper, the model of Luenberger Observer which is based on the state equation of permanent magnet synchronous motor (PMSM), and the changes of residence and induce which may lead to the error of the system are also analysed, in order to increase the accuracy of the system, current compensator is also added. In addition, 2 conditions which PMSM runs at low speed and high speed are analysed under the MATLAB model, the results show that the Luenberger Observer has better performance at high speed, but the noisy data of the useful signal is more at low speed.

DC-link oscillation suppression method based on q-axis voltage compensation of a 180 kW PMSM traction system for urban rail transit

Under certain working conditions, the permanent magnet synchronous motor (PMSM) traction system of urban rail transit shows negative impedance characteristics, which is easy to cause voltage resonance of DC-link and lead to instability of the system. In order to ensure the stability of the system, a DC-link oscillation suppression method based on q-axis voltage compensation is proposed. Firstly, the PMSM traction system and oscillation mechanism of DC-link are analyzed. Secondly, a stable control method based on q-axis feedforward decoupling voltage compensation is adopted to realize the decoupling control of PMSM and the suppression of DC-link oscillation. Finally, the method is verified on a 180 kW PMSM traction system, simulation and experiment verify the effectiveness of the DC-link oscillation suppression method.

Robustness Optimization of Model Predictive Current Control for PMSM Drives Considering Dynamic Response Influence

In order to enhance the parameter robustness of model predictive current control (MPCC) for permanent-magnet synchronous motor (PMSM) drive, a novel robust MPCC considering dynamic response influence is proposed in this article. First, the parameter sensitivity effects on dynamic control capability of MPCC are analyzed theoretically. Second, the data acquisition methods of inductance and flux-linkage based on current errors are presented, respectively. Furthermore, the accurate parameters can be calculated by the proposed data acquisition methods and compensated into the predictive model in real time. Finally, an experimental platform is built to verify the effectiveness of the proposed method and the experimental results illustrate that the proposed method can effectively erase the destructive effect of parameter mismatches and enhance the robustness of the system ultimately.

Static-Errorless Deadbeat Predictive Current Control for PMSM Current Harmonics Suppression Based on Vector Resonant Controller

The traditional deadbeat predictive current control (DPCC) is sensitive to the unmodeled disturbances in permanent magnet synchronous motor (PMSM) drives, including alternating current (AC) and direct current (DC) disturbances, which can lead to intolerable current deviations, especially the current harmonics caused by the AC disturbance. To address the problem, a static-errorless DPCC is proposed for the current loop of PMSM drives. In the studied scheme, a vector resonant controller is used in parallel with the control law of the DPCC to compensate for the AC disturbance, while an extended state observer is used to compensate for the DC disturbance. Thus, the studied scheme is robust to both the AC and DC disturbances. The stability of the proposed scheme is systematically analyzed by the Jury criterion, while the parameter tuning is discussed in detail based on the stability analysis. Compared with the traditional DPCC, the studied scheme can effectively eliminate the current deviations to achieve static-errorless current control in PMSM drives. Finally, the effectiveness of the proposed scheme is validated on a 2.2-kW PMSM platform.

Adjacent-Vector-Based Model Predictive Control for Permanent Magnet Synchronous Motors With Full Model Estimation

The finite-control-set model predictive control (FCS-MPC) shows appealing features in permanent magnet synchronous motor control but suffers from high current ripples. Multiple-vector-based MPC (MVB-MPC) methods reduce the ripples but may lose some of the merits possessed by the FCS-MPC. Furthermore, the performance of both the FCS-MPC and the MVB-MPC is dependent on the accurate knowledge of the system parameters. This article proposes an adjacent-vector-based MPC (AVB-MPC) combining the FCS-MPC and the MVB-MPC. Instead of finding a solution with minimum cost, the AVB-MPC searches from a lookup table of adjacent vectors for the solution with the least switching actions to keep the cost within a tolerable band. Hence, the current ripple is reduced under the same switching frequency, while the merits of fast dynamic responsiveness and inherent overmodulation ability are retained. In addition, a full model estimation method is proposed so that the knowledge of the machine parameters is not required. The rank deficiency problem of multiparameter identification is also solved by the tolerable band. And these benefits are gained without adding much computational effort. Finally, the effectiveness and benefits of the AVB-MPC are validated by comparative experimental results comparing with several other typical predictive controllers.

Model-Free Predictive Current and Disturbance Rejection Control of Dual Three-Phase PMSM Drives Using Optimal Virtual Vector Modulation

Model-based predictive current control (MBPCC) relies heavily on adequate system modeling and accurate parameters. The detailed models of dual three-phase permanent magnet synchronous motors (PMSMs) contain mutual cross-coupling dynamics which make it difficult to extract accurate parameters. Also, some of the physical parameters of PMSMs are generally nonlinear functions of current and rotor position. In this article, a model-free predictive current control (MFPCC) based on an ultralocal model and an extended state observer is proposed for an asymmetrical dual three-phase (ADTP) PMSM. The MFPCC method is shown to provide superior current regulation when compared to the standard MBPCC approach under uncertain parameter conditions. Furthermore, the harmonic currents and the current ripple in the ADTP PMSM drive have been regulated to near-zero values by using optimized voltage vectors comprised of virtual vectors and null vectors. A generalized center-aligned pulsewidth modulation (PWM) scheme is presented to facilitate the synthesis of the optimal virtual voltage vectors for implementation on a low-cost digital signal processing platform. The performance improvements of the MFPCC with optimal virtual vector modulation are verified and compared with the conventional MBPCC method in both simulations and experiments on a surface-mount type dual three-phase PMSM.

Speed Control for Variable Speed PMSM Drive System Using Nonlinear Variable-Horizon Predictive Functional Control

Electrohydrostatic actuators (EHAs) adopted variable speed permanent magnet synchronous motor (PMSM) drive systems are widely used by surface actuation systems in more electrical aircraft. However, the dynamic performance and the antidisturbance performance of EHA need to be improved due to the limited dynamic response of variable speed PMSM drive systems and uncertain aerodynamic disturbance. To improve the transient-state operation, nonlinear variable-horizon predictive functional control (NVHPFC) is proposed for the speed controller of the variable speed PMSM drive system. By analyzing the relationship between the prediction horizon and the electromagnetic torque, a nonlinear variable predictive horizon strategy is presented, which replaces the fixed predictive horizon in classical PFC. Aiming to improve the prediction accuracy and antidisturbance performance of NVHPFC, a discrete prediction error compensation strategy is incorporated with the NVHPFC. Meanwhile, the stability of the proposed method is verified by the Lyapunov function in the discrete domain. Finally, simulation and experimental results of the proposed method show stronger antidisturbance, smaller overshoot, and shorter settling time performance compared with the classical PFC method based on a field-programmable gate array (FPGA) test bench.

Field-programmable gate array-based field-oriented control for permanent magnet synchronous motor drive

Permanent magnet synchronous motor (PMSM) is a special type of synchronous electric motor that has many applications such as in the manufacturing industry of robots, self-propelled mechanisms, in the medical fiel. In this paper, the permanent magnet synchronous motor motor control structure according to the field-oriented control (FOC) algorithm will be implemented on the field-programmable gate array (FPGA) card. Function blocks in FOC algorithm for example PI controller, space vector pulse width modulation (SVPWM) algorithm will be integrated into individual itegrated circuit (Ics) then will be connected to form an IC with the function of implementing FOC algorithm. Furthermore, this algorithm will be used for powertrains using gallium nitride (GaN). GaN technology provides switching frequencies up to 100 kHz instead of the upper 2 to 20 kHz like insulated gate bipolar transistor (IGBT) transistors. With GaN technology, it is possible to reduce switching losses as well as increase the efficiency of the power converter. The performance results will be verified through the typhoon hardware in the loop (HIL) device.

Vector Control of PMSM Based on Improved Sliding Mode Observer and Controller

This paper presents a sensorless speed control method of permanent magnet synchronous motor (PMSM) applying sliding-mode control theory, to enhance the observation precision and improve robustness of control system. Firstly, an improved full-order sliding mode observer (FSMO) with sigmoid function is gifted to weaken the high-frequency (HF) chattering caused by conventional sliding mode observer (SMO). The quadrature phase-locked loop (PLL) is used to calculate high-precision rotor location and speed, avoiding the use of filter. Then the nonsingular fast terminal sliding mode controller (NFTSMC) in speed controller is introduced to replace traditional proportional integral (PI) controller to improve the dynamic performance of control system. The outcomes verify that the presented control method enhances the overall observation precision, suppresses HF chattering, and increases dynamic and stable state response of PMSM.

A Cascaded Band Based Model Predictive Current Control for PMSM Drives

Conventional model predictive control for permanent magnet synchronous motor (PMSM) drives often introduces a weighting factor for lowering the switching frequency, which unfortunately leads to the tedious tuning works on weighting factors. Moreover, the computational burden is quite heavy since all the voltage candidates have to be enumerated. In this work, a cascaded band-based model predictive current control is proposed, which can reduce the switching frequency without the use of weighting factor as well as alleviate the computational burden. In this method, the latest applied voltage vector will be adopted to predict the current error prior to the iterative prediction process. Next, a band is defined to compare with the pre-calculated current error to determine whether it is to be maintained. As a result, the iterative cost function minimization turns to be an event triggered process. In addition, the hard switch constraint for the candidate voltage vectors are developed to combine with the cascaded band, which can effectively reduce the iterations and avoid the sub-optimum. The effectiveness of the proposed method is verified on a PMSM platform fed by 3-level T-type inverter.