Finite set model predictive control of permanent magnet synchronous motor current based on super twisting sliding mode observer

This article proposes a unique control strategy for a deadbeat multiple vector finite-set model predictive current control with an embedded integral action (MV-FMPC) for permanent magnet synchronous motor drives. Torque ripple and phase current distortions in permanent magnet synchronous motor (PMSM) drives are minimized with the proposed controller by adopting the multiple vector approach to the finite-set model predictive control. The controller uses a hexagonal co-ordinate system to simplify the location and identification of the virtual vectors created, thereby eliminating the use of large look-up tables and reducing computational burden. When used with the proposed deadbeat prediction model, the overall steady-state performance, system robustness, and quality of disturbance rejection are improved compared to the state-of-the-art finite-set model predictive current control (FS-MPC) methods with pulsewidth modulation. The improvements are due to the modified deadbeat prediction model with integral action, the algorithm used for multiple virtual voltage identification and the retention of the cost function in the proposed method. The proposed deadbeat MV-FMPC method and its improvements over the conventional FS-MPC have been verified through simulation and experiments with an interior-type permanent magnet synchronous machine.

This paper focuses on the model predictive current control of power converters with the aim of indicating the influence of some system parameters used in predictive control on the load current and load voltage. A model predictive current control algorithm is proposed, specifically directed at the utilization of power obtained from renewable energy systems (RESs). In this study the renewable energy systems model is used to investigate system performance when power is supplied to a resistive-inductive load (RL-load). A finite set-model predictive current control (FS-MPCC) method is developed to control the output current of three-phase, voltage source inverter (VSI). The approximation methods for the derivatives of the model differential equations and delay compensation of model predictive control (MPC) system for power converters are assessed. Simulation results of a two-level, three-phase VSI using FS-MPCC are carried out to show the effects of different approximation methods on the load current and voltage regulation as well as on the predictive current control operation with and without delay compensation for different sampling times. It has been noticed that the ripple in the load currents is considerable when the delay compensation is not accounted for and the delay compensation method that reduces the ripple and operation is similar to the ideal case. It is confirmed that for larger sampling times the delay is noticeable, but when the sampling time is smaller it is not visible.

The finite control set model predictive current control (MPCC) method for permanent magnet synchronous motor (PMSM) is a simple control method but there are high current harmonics in the motor's three-phase current because of the limited number of voltage vectors. For this problem, a new amplitude model predictive current control (AMPCC) method based on the voltage amplitude in rotating coordinate reference system is proposed in this paper. By analyzing the motor's voltage model under rotating coordinate reference system, a suitable dynamic range of dq-axis voltage amplitude is designed for cost function. According to this range, the amplitude dynamic control set of prediction model is designed, and the optimal solution is selected by iterative method. The optimal vector is synthesized based on the real rotor position and optimal amplitude, so phase error of it is relatively small. And the dynamic amplitude range can reduce amplitude error, and thus a significant suppression of current ripple and prediction error. Meanwhile, the triangular function's avoidance in iterative calculation makes the algorithm compute less complex. Finally, this method is proved that it effectively reduces the current harmonics of the motor and improves the steady-state performance by building experimental verification.

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.

In this paper, a Lyapunov based finite control set model predictive direct torque control for the permanent magnet synchronous machine (PMSM) is proposed. In the proposed control scheme, the finite control set prediction and the Lyapunov theory are combined to minimize the torque ripple. The 8 voltage vectors of the 2-level converter are utilized as a finite control set for the torque prediction of the PMSM. A cost function considering the torque error, the Maximum Torque per Ampere (MTPA) operation and the current limitation is introduced. Comparing to the conventional finite control set predictive control, the dominant part of the cost function is utilized as a Lyapunov function to estimate the duty cycle of each voltage vector. An optimum voltage can be obtained by the optimum voltage vector from the 8 vectors and their duty cycles. A small sampling frequency and a fixed switching frequency can be realized when compared to the conventional finite set model predictive control. In the end, the simulation and experimental results validate the performance of the proposed control scheme.

In order to improve the performance of pulse current source and to ensure the safe and stable of the system, Model Predictive Current Control (MPCC) method is adopted to pulse current source. However, there is a large amount of online calculation and high computational complexity, which is especially prominent in systems with a long and complex prediction time domain. To solve these problems, an explicit model predictive current control (EMPCC) method to reduce the online operation time is proposed. By using the state vector of the system as the parameter vector, the optimal control problem is equivalent to a multiparameter quadratic programming problem. The valid set method is used to solve the multiparameter quadratic optimization problem. The mapping relationship between the output voltage, output current and the state partition is obtained. The relationship between the state partition and the duty cycle is further deduced and stored in the lookup table. Based on the system state, the sequential search method is applied to find the duty cycle online, and the optimal control quantity at the current moment is obtained. This method pre-computes the online prediction and duty cycle calculation process offline, which solves the disadvantage of the model predictive current control method with large online computation. Meanwhile, this method can effectively improve the response speed of the pulse current source to the pulse load and improve the output current quality. The simulation and experimental results demonstrated the feasibility and validity of the proposed method.

In order to improve the control performance of the permanent magnet synchronous machine (PMSM) drives in electric vehicles, this paper proposes a novel finite control set (FCS) model predictive current control (MPCC) method to reduce the adverse impacts caused by the low control frequency (LCF) and flux linkage mismatch (FLM). Firstly, the disadvantages of the traditional FCS-MPCC methods are illustrated in detail. Then, aiming at the LCF problem, the implementation of the FCS-MPCC algorithm based on tripartite predictions but single actuation is specially designed. In terms of the FLM issue, this paper develops a direct handling strategy by using the parameter identification technology. In detail, a stable sliding mode flux linkage (SM-FL) observer is designed to detect the realtime flux linkage. Finally, the simulation results prove that the proposed FCS-MPCC algorithm is effective.

This paper proposes two model predictive current control (MPCC) methods utilizing two output voltages with variable application durations in one sampling period to control the output currents of single-phase voltage source inverters (VSIs). In the proposed methods, the application durations of the two voltages, as well as the selection of two output voltages used in the future sampling period, are determined by an optimization process to minimize current error inside the future sampling period and to eliminate current error at the end of the future sampling instant. By utilizing the two voltages with variable durations, the two proposed MPCC methods can reduce steady-state current errors and decrease output current ripples without increasing the sampling frequency in comparison with the conventional MPCC method, despite only three distinctive output voltages being allowed in the single-phase VSI. The two proposed methods along with the conventional MPCC method are compared in terms of current errors and total harmonic distortion. The effectiveness of the two proposed methods for the single-phase VSIs is verified with both simulation and experimental results.

A direct torque control (DTC) with a modified finite set model predictive strategy is proposed in this paper. The eight voltage space vectors of two-level inverters are taken as the finite control set and applied to the model predictive direct torque control of a permanent magnet synchronous motor (PMSM). The duty cycle of each voltage vector in the finite set can be estimated by a cost function, which is designed based on factors including the torque error, maximum torque per ampere (MTPA), and stator current constraints. Lyapunov control theory is introduced in the determination of the weight coefficients of the cost function to guarantee stability, and thus the optimal voltage vector reference value of the inverter is obtained. Compared with the conventional finite control set model predictive control (FCS-MPC) method, the torque ripple is reduced and the robustness of the system is clearly improved. Finally, the simulation and experimental results verify the effectiveness of the proposed control scheme.

This paper proposes a finite set model predictive control (FS-MPC) based thrust maximization technique for linear induction machines used in linear metros. For modeling of the proposed control method, the end effect is taken into consideration. The proposed control method is used to achieve maximum thrust per ampere and to reduce the thrust ripples. It differs from the FS-MPC methods, where the cost function consists of the thrust and angle errors. The thrust error is calculated from the difference between the reference thrust and the predicted thrust, and the angle error is calculated from the difference between the angle of predicted primary current and the angle of the predicted secondary flux in one side and π/4 on the other side. A comparison between the proposed method and the finite set model predictive direct thrust control (FS-MPDTC) is presented to illustrate the superiority of the proposed method. Both simulation and experimental analysis are conducted to validate the effectiveness of the proposed finite set model predictive direct angle control (FS-MPDAC). A prototype test platform is developed in the laboratory with two 3 kW arc induction motors. The simulation model, experimental test platform, and test results are presented in this paper.

In finite control set model predictive control (FCS-MPC) strategy only one basic voltage vector is to be selected in per periodic time, which causes big current ripple as well as the torque ripple of permanent magnet synchronous motor (PMSM). To solve this problem, an improved model predictive control method, named modulated model predictive control (M2PC) is proposed. The proposed control strategy can produce a modulated waveform, which can reduce torque ripple and improve power quality. Simulation results verify that the proposed current controller has a better control performance than the classical FCS-MPC strategy.

Dual-port direct drive wave energy power generation systems (DP-DDWEPGS) have received widespread attention due to their smooth and zero-free output power, compared to single-port direct drive wave energy power generation systems (SP-DDWEPGS) which have the disadvantage of large out-put power fluctuations. To further enhance the performance of the DP-DDWEPGS, optimal power capture control is proposed to achieve maximum power point tracking. Meanwhile, a multiport converter is applied to the DP-DDWEPGS to solve the problem caused by an excessive number of switching devices in the overall system converter. The multiport converter fulfills all the functional requirements of the DP-DDWEPGS while reducing the number of switching devices. However, switch multiplexing of the multiport converter also introduces coupling relationships between each port and the wave force exhibits time-varying characteristics, necessitating advanced control methods with superior fast-tracking capability. Therefore, in this paper, a decoupling duty cycle optimization model predictive control for DP-DDWEPGS is proposed. Based on the characteristics of switching multiplexing, NSC finite control set model predictive control (FCS-MPC) decouples the current prediction and the cost function, reduces the number of candidate voltage vectors in each operation, and shortens the operation time by 70%. To address the issues of high ripple value and increased error due to decoupling in FCS-MPC, duty cycle optimization control is added, greatly reducing the fluctuations in electromagnetic force and power of the permanent magnet linear generator (PMLG). Based on the established simulation model, the feasibility and superiority of the multiport converter and decoupling duty cycle optimization model predictive current control method are verified.

This paper introduces the comparison of four predictive torque control schemes for a permanent-magnet synchronous machine (PMSM). The first method is the finite-set model predictive control (FS-MPC). In FS-MPC, the optimal switching state is selected based on the evaluation and minimization of a cost function for all possible voltage space vectors (VSVs) of the inverter. The second method performs a simplified FS-MPC where the selection and evaluation of the possible VSVs are reduced to only three. The third method is based on the principle of predictive direct torque control (PDTC), where the duty cycle of the switching state is optimized for application in the inverter. Finally, a method that combines FS-MPC and PDTC named model predictive torque control is presented. This paper introduces the methodology and the results of a comprehensive comparison of the four predictive schemes based on different criterions. The control schemes are implemented on a field-programmable gate array and are applied to a PMSM. Experimental results are presented to validate the presented comparison and discussion.

Parameter mismatch will result in inaccurate motion behavior prediction, which will reduce the performance of the predictive algorithm. To increase the system’s robustness against dynamic changes of parameters and disturbances, a disturbance preview based multistep finite control set model predictive current control (DP-MPCC) method is created for a permanent magnet synchronous motor (PMSM) system controlled by a two-level voltage-source inverter (2L-VSI), in which the disturbance observer is implemented by the reduced-order generalized proportional integrated observer (Reduced-order GPIO). This strategy can prepare heavy computations for the long horizons optimization problem offline without increasing the computational burden. Additionally, the multistep prediction algorithm can now be real-time embedded with the estimation of the disturbance sequence and the dynamic parameter changes in the PMSM, which greatly enhances prediction accuracy and control effectiveness. Simulated results are shown, which support the effectiveness of the proposed methodology.

A model predictive current control (MPCC) method that does not employ a cost function is proposed. The MPCC method can decrease common-mode voltages in loads fed by three-phase voltage-source inverters. Only non-zero-voltage vectors are considered as finite control elements to regulate load currents and decrease common-mode voltages. Furthermore, the three-phase future reference voltage vector is calculated on the basis of an inverse dynamics model, and the location of the one-step future voltage vector is determined at every sampling period. Given this location, a non-zero optimal future voltage vector is directly determined without repeatedly calculating the cost values obtained by each voltage vector through a cost function. Without utilizing the zero-voltage vectors, the proposed MPCC method can restrict the common-mode voltage within ± Vdc/6, whereas the common-mode voltages of the conventional MPCC method vary within ± Vdc/2. The performance of the proposed method with the reduced common-mode voltage and no cost function is evaluated in terms of the total harmonic distortions and current errors of the load currents. Simulation and experimental results are presented to verify the effectiveness of the proposed method operated without a cost function, which can reduce the common-mode voltage.